#include "RPhiFeatureTool.h"

Inheritance diagram for lar_content::RPhiFeatureTool:

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Classes
class	KernelEstimate
	Kernel estimate class. More...

Public Types
typedef std::vector< MvaFeatureTool< Ts... > * >	FeatureToolVector

typedef std::map< std::string, MvaFeatureTool< Ts... > * >	FeatureToolMap

Public Member Functions
	RPhiFeatureTool ()
	Default constructor.

void	Run (LArMvaHelper::MvaFeatureVector &featureVector, const VertexSelectionBaseAlgorithm const pAlgorithm, const pandora::Vertex const pVertex, const VertexSelectionBaseAlgorithm::SlidingFitDataListMap &, const VertexSelectionBaseAlgorithm::ClusterListMap &, const VertexSelectionBaseAlgorithm::KDTreeMap &kdTreeMap, const VertexSelectionBaseAlgorithm::ShowerClusterListMap &, const float beamDeweightingScore, float &bestFastScore)
	Run the tool.

virtual void	Run (MvaTypes::MvaFeatureVector &featureVector, Ts... args)=0
	Run the algorithm tool.

virtual void	Run (MvaTypes::MvaFeatureMap &featureMap, pandora::StringVector &featureOrder, const std::string &featureToolName, Ts...)

const std::string &	GetType () const
	Get the type.

const std::string &	GetInstanceName () const
	Get the instance name.

const Pandora &	GetPandora () const
	Get the associated pandora instance.

Protected Member Functions
virtual StatusCode	Initialize ()
	Perform any operations that must occur after reading settings, but before running the process.

virtual StatusCode	Reset ()
	Perform any operations when pandora is reset, typically at the end of each event.

StatusCode	RegisterDetails (const Pandora *const pPandora, const std::string &type, const std::string &instanceName)
	Register i) the pandora instance that will run the process and ii) the process type.

Protected Attributes
const Pandora *	m_pPandora
	The pandora object that will run the process.

std::string	m_type
	The process type.

std::string	m_instanceName
	The process instance name.

Private Member Functions
pandora::StatusCode	ReadSettings (const pandora::TiXmlHandle xmlHandle)
	Read the algorithm settings.

float	GetFastScore (const KernelEstimate &kernelEstimateU, const KernelEstimate &kernelEstimateV, const KernelEstimate &kernelEstimateW) const
	Get the score for a trio of kernel estimations, using fast histogram approach.

float	GetMidwayScore (const KernelEstimate &kernelEstimateU, const KernelEstimate &kernelEstimateV, const KernelEstimate &kernelEstimateW) const
	Get the score for a trio of kernel estimations, using kernel density estimation but with reduced (binned) sampling.

float	GetFullScore (const KernelEstimate &kernelEstimateU, const KernelEstimate &kernelEstimateV, const KernelEstimate &kernelEstimateW) const
	Get the score for a trio of kernel estimations, using kernel density estimation and full hit-by-hit sampling.

void	FillKernelEstimate (const pandora::Vertex *const pVertex, const pandora::HitType hitType, VertexSelectionBaseAlgorithm::HitKDTree2D &kdTree, KernelEstimate &kernelEstimate) const
	Use hits in clusters (in the provided kd tree) to fill a provided kernel estimate with hit-vertex relationship information.

bool	AcceptVertexLocation (const pandora::Vertex *const pVertex, const pandora::VertexList &selectedVertexList) const
	Whether to accept a candidate vertex, based on its spatial position in relation to other selected candidates.

float	atan2Fast (const float y, const float x) const
	Fast estimate of std::atan2 function. Rather coarse (max \|error\| > 0.01) but should suffice for this use-case.

Private Attributes
bool	m_fastScoreCheck
	Whether to use the fast histogram based score to selectively avoid calling full or midway scores.

bool	m_fastScoreOnly
	Whether to use the fast histogram based score only.

bool	m_fullScore
	Whether to use the full kernel density estimation score, as opposed to the midway score.

float	m_kernelEstimateSigma
	The Gaussian width to use for kernel estimation.

float	m_kappa
	Hit-deweighting offset, of form: weight = 1 / sqrt(distance + kappa), units cm.

float	m_maxHitVertexDisplacement1D
	Max hit-vertex displacement in any one dimension for contribution to kernel estimation.

float	m_minFastScoreFraction
	Fast score must be at least this fraction of best fast score to calculate full score.

unsigned int	m_fastHistogramNPhiBins
	Number of bins to use for fast score histograms.

float	m_fastHistogramPhiMin
	Min value for fast score histograms.

float	m_fastHistogramPhiMax
	Max value for fast score histograms.

bool	m_enableFolding
	Whether to enable folding of -pi -> +pi phi distribution into 0 -> +pi region only.

Detailed Description

RPhiFeatureTool class.

Definition at line 21 of file RPhiFeatureTool.h.

Member Typedef Documentation

◆ FeatureToolMap

template<typename... Ts>

typedef std::map<std::string, MvaFeatureTool<Ts...> *> lar_content::MvaFeatureTool< Ts >::FeatureToolMap

inherited

Definition at line 37 of file LArMvaHelper.h.

◆ FeatureToolVector

template<typename... Ts>

typedef std::vector<MvaFeatureTool<Ts...> *> lar_content::MvaFeatureTool< Ts >::FeatureToolVector

inherited

Definition at line 36 of file LArMvaHelper.h.

Constructor & Destructor Documentation

◆ RPhiFeatureTool()

lar_content::RPhiFeatureTool::RPhiFeatureTool ( )

Default constructor.

Definition at line 21 of file RPhiFeatureTool.cc.

Member Function Documentation

◆ AcceptVertexLocation()

bool lar_content::RPhiFeatureTool::AcceptVertexLocation	(	const pandora::Vertex *const	pVertex,
		const pandora::VertexList &	selectedVertexList
	)		const

private

Whether to accept a candidate vertex, based on its spatial position in relation to other selected candidates.

Parameters

pVertex	the address of the vertex
selectedVertexList	the selected vertex list

Returns: boolean

◆ atan2Fast()

float lar_content::RPhiFeatureTool::atan2Fast	(	const float	y,
		const float	x
	)		const

private

Fast estimate of std::atan2 function. Rather coarse (max |error| > 0.01) but should suffice for this use-case.

Parameters

y	the y coordinate
x	the x coordinate

Returns: estimate of std::atan2

Definition at line 198 of file RPhiFeatureTool.cc.

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◆ FillKernelEstimate()

void lar_content::RPhiFeatureTool::FillKernelEstimate	(	const pandora::Vertex *const	pVertex,
		const pandora::HitType	hitType,
		VertexSelectionBaseAlgorithm::HitKDTree2D &	kdTree,
		KernelEstimate &	kernelEstimate
	)		const

private

Use hits in clusters (in the provided kd tree) to fill a provided kernel estimate with hit-vertex relationship information.

Parameters

pVertex	the address of the vertex
hitType	the relevant hit type
kdTree	the relevant kd tree
kernelEstimate	to receive the populated kernel estimate

Definition at line 166 of file RPhiFeatureTool.cc.

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◆ GetFastScore()

float lar_content::RPhiFeatureTool::GetFastScore	(	const KernelEstimate &	kernelEstimateU,
		const KernelEstimate &	kernelEstimateV,
		const KernelEstimate &	kernelEstimateW
	)		const

private

Get the score for a trio of kernel estimations, using fast histogram approach.

Parameters

kernelEstimateU	the kernel estimate for the u view
kernelEstimateV	the kernel estimate for the v view
kernelEstimateW	the kernel estimate for the w view

Returns: the fast score

Definition at line 82 of file RPhiFeatureTool.cc.

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◆ GetFullScore()

float lar_content::RPhiFeatureTool::GetFullScore	(	const KernelEstimate &	kernelEstimateU,
		const KernelEstimate &	kernelEstimateV,
		const KernelEstimate &	kernelEstimateW
	)		const

private

Get the score for a trio of kernel estimations, using kernel density estimation and full hit-by-hit sampling.

Parameters

kernelEstimateU	the kernel estimate for the u view
kernelEstimateV	the kernel estimate for the v view
kernelEstimateW	the kernel estimate for the w view

Returns: the full score

Definition at line 148 of file RPhiFeatureTool.cc.

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◆ GetInstanceName()

const std::string & pandora::Process::GetInstanceName ( ) const

inlineinherited

Get the instance name.

Returns: The instance name

Definition at line 109 of file Process.h.

◆ GetMidwayScore()

float lar_content::RPhiFeatureTool::GetMidwayScore	(	const KernelEstimate &	kernelEstimateU,
		const KernelEstimate &	kernelEstimateV,
		const KernelEstimate &	kernelEstimateW
	)		const

private

Get the score for a trio of kernel estimations, using kernel density estimation but with reduced (binned) sampling.

Parameters

kernelEstimateU	the kernel estimate for the u view
kernelEstimateV	the kernel estimate for the v view
kernelEstimateW	the kernel estimate for the w view

Returns: the midway score

Definition at line 118 of file RPhiFeatureTool.cc.

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◆ GetPandora()

const Pandora & pandora::Process::GetPandora ( ) const

inlineinherited

Get the associated pandora instance.

Returns: the associated pandora instance

Definition at line 116 of file Process.h.

◆ GetType()

const std::string & pandora::Process::GetType ( ) const

inlineinherited

Get the type.

Returns: The type

Definition at line 102 of file Process.h.

◆ Initialize()

StatusCode pandora::Process::Initialize ( )

inlineprotectedvirtualinherited

Perform any operations that must occur after reading settings, but before running the process.

Reimplemented in lar_content::BdtBeamParticleIdTool, lar_content::BeamParticleIdTool, lar_content::CosmicRayTaggingTool, lar_content::EventReadingAlgorithm, lar_content::EventWritingAlgorithm, lar_content::LArPseudoLayerPlugin, lar_content::LArRotationalTransformationPlugin, EventReadingAlgorithm, and EventWritingAlgorithm.

Definition at line 126 of file Process.h.

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◆ ReadSettings()

StatusCode lar_content::RPhiFeatureTool::ReadSettings ( const pandora::TiXmlHandle xmlHandle )

privatevirtual

Read the algorithm settings.

Parameters

xmlHandle the relevant xml handle

Implements pandora::Process.

Definition at line 243 of file RPhiFeatureTool.cc.

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◆ RegisterDetails()

StatusCode pandora::Process::RegisterDetails	(	const Pandora *const	pPandora,
		const std::string &	type,
		const std::string &	instanceName
	)

inlineprotectedinherited

Register i) the pandora instance that will run the process and ii) the process type.

Parameters

pPandora	address of the pandora object that will run the process
type	the process type
instanceName	the process instance name

Definition at line 146 of file Process.h.

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◆ Reset()

StatusCode pandora::Process::Reset ( )

inlineprotectedvirtualinherited

Perform any operations when pandora is reset, typically at the end of each event.

Reimplemented in lar_content::MasterAlgorithm, lar_content::PostProcessingAlgorithm, and lar_content::PreProcessingAlgorithm.

Definition at line 133 of file Process.h.

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◆ Run() [1/3]

void lar_content::RPhiFeatureTool::Run	(	LArMvaHelper::MvaFeatureVector &	featureVector,
		const VertexSelectionBaseAlgorithm *const	pAlgorithm,
		const pandora::Vertex *const	pVertex,
		const VertexSelectionBaseAlgorithm::SlidingFitDataListMap &	,
		const VertexSelectionBaseAlgorithm::ClusterListMap &	,
		const VertexSelectionBaseAlgorithm::KDTreeMap &	kdTreeMap,
		const VertexSelectionBaseAlgorithm::ShowerClusterListMap &	,
		const float	beamDeweightingScore,
		float &	bestFastScore
	)

Run the tool.

Parameters

pAlgorithm	address of the calling algorithm
pVertex	address of the vertex
kdTreeMap	map of the hit kd trees
beamDeweightingScore	the beam deweighting score for this vertex
bestFastScore	the best fast score

Returns: the r/phi feature

Definition at line 38 of file RPhiFeatureTool.cc.

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◆ Run() [2/3]

template<typename... Ts>

virtual void lar_content::MvaFeatureTool< Ts >::Run	(	MvaTypes::MvaFeatureMap &	featureMap,
		pandora::StringVector &	featureOrder,
		const std::string &	featureToolName,
		Ts...
	)

inlinevirtualinherited

Definition at line 51 of file LArMvaHelper.h.

◆ Run() [3/3]

template<typename... Ts>

virtual void lar_content::MvaFeatureTool< Ts >::Run	(	MvaTypes::MvaFeatureVector &	featureVector,
		Ts...	args
	)

pure virtualinherited

Run the algorithm tool.

Parameters

featureVector	the vector of features to append
args	arguments to pass to the tool

Member Data Documentation

◆ m_enableFolding

bool lar_content::RPhiFeatureTool::m_enableFolding

private

Whether to enable folding of -pi -> +pi phi distribution into 0 -> +pi region only.

Definition at line 178 of file RPhiFeatureTool.h.

◆ m_fastHistogramNPhiBins

unsigned int lar_content::RPhiFeatureTool::m_fastHistogramNPhiBins

private

Number of bins to use for fast score histograms.

Definition at line 174 of file RPhiFeatureTool.h.

◆ m_fastHistogramPhiMax

float lar_content::RPhiFeatureTool::m_fastHistogramPhiMax

private

Max value for fast score histograms.

Definition at line 176 of file RPhiFeatureTool.h.

◆ m_fastHistogramPhiMin

float lar_content::RPhiFeatureTool::m_fastHistogramPhiMin

private

Min value for fast score histograms.

Definition at line 175 of file RPhiFeatureTool.h.

◆ m_fastScoreCheck

bool lar_content::RPhiFeatureTool::m_fastScoreCheck

private

Whether to use the fast histogram based score to selectively avoid calling full or midway scores.

Definition at line 165 of file RPhiFeatureTool.h.

◆ m_fastScoreOnly

bool lar_content::RPhiFeatureTool::m_fastScoreOnly

private

Whether to use the fast histogram based score only.

Definition at line 166 of file RPhiFeatureTool.h.

◆ m_fullScore

bool lar_content::RPhiFeatureTool::m_fullScore

private

Whether to use the full kernel density estimation score, as opposed to the midway score.

Definition at line 167 of file RPhiFeatureTool.h.

◆ m_instanceName

std::string pandora::Process::m_instanceName

protectedinherited

The process instance name.

Definition at line 89 of file Process.h.

◆ m_kappa

float lar_content::RPhiFeatureTool::m_kappa

private

Hit-deweighting offset, of form: weight = 1 / sqrt(distance + kappa), units cm.

Definition at line 170 of file RPhiFeatureTool.h.

◆ m_kernelEstimateSigma

float lar_content::RPhiFeatureTool::m_kernelEstimateSigma

private

The Gaussian width to use for kernel estimation.

Definition at line 169 of file RPhiFeatureTool.h.

◆ m_maxHitVertexDisplacement1D

float lar_content::RPhiFeatureTool::m_maxHitVertexDisplacement1D

private

Max hit-vertex displacement in any one dimension for contribution to kernel estimation.

Definition at line 171 of file RPhiFeatureTool.h.

◆ m_minFastScoreFraction

float lar_content::RPhiFeatureTool::m_minFastScoreFraction

private

Fast score must be at least this fraction of best fast score to calculate full score.

Definition at line 173 of file RPhiFeatureTool.h.

◆ m_pPandora

const Pandora* pandora::Process::m_pPandora

protectedinherited

The pandora object that will run the process.

Definition at line 87 of file Process.h.

◆ m_type

std::string pandora::Process::m_type

protectedinherited

The process type.

Definition at line 88 of file Process.h.

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

LArContent/larpandoracontent/LArVertex/RPhiFeatureTool.h
LArContent/larpandoracontent/LArVertex/RPhiFeatureTool.cc

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

◆ FeatureToolMap

◆ FeatureToolVector

Constructor & Destructor Documentation

◆ RPhiFeatureTool()

Member Function Documentation

◆ AcceptVertexLocation()

◆ atan2Fast()

◆ FillKernelEstimate()

◆ GetFastScore()

◆ GetFullScore()

◆ GetInstanceName()

◆ GetMidwayScore()

◆ GetPandora()

◆ GetType()

◆ Initialize()

◆ ReadSettings()

◆ RegisterDetails()

◆ Reset()

◆ Run() [1/3]

◆ Run() [2/3]

◆ Run() [3/3]

Member Data Documentation

◆ m_enableFolding

◆ m_fastHistogramNPhiBins

◆ m_fastHistogramPhiMax

◆ m_fastHistogramPhiMin

◆ m_fastScoreCheck

◆ m_fastScoreOnly

◆ m_fullScore

◆ m_instanceName

◆ m_kappa

◆ m_kernelEstimateSigma

◆ m_maxHitVertexDisplacement1D

◆ m_minFastScoreFraction

◆ m_pPandora

◆ m_type