#include "NeutrinoIdTool.h"

Inheritance diagram for lar_content::NeutrinoIdTool:

Classes
class	SliceFeatures
	Slice features class. More...

Public Member Functions
	NeutrinoIdTool ()
	Default constructor. More...

void	SelectOutputPfos (const pandora::Algorithm *const pAlgorithm, const SliceHypotheses &nuSliceHypotheses, const SliceHypotheses &crSliceHypotheses, pandora::PfoList &selectedPfos)
	Select which reconstruction hypotheses to use; neutrino outcomes or cosmic-ray muon outcomes for each slice. More...

Private Types
typedef std::pair< unsigned int, float >	UintFloatPair

typedef std::vector< SliceFeatures >	SliceFeaturesVector

Private Member Functions
void	GetSliceFeatures (const NeutrinoIdTool *const pTool, const SliceHypotheses &nuSliceHypotheses, const SliceHypotheses &crSliceHypotheses, SliceFeaturesVector &sliceFeaturesVector) const
	Get the features of each slice. More...

bool	GetBestMCSliceIndex (const pandora::Algorithm *const pAlgorithm, const SliceHypotheses &nuSliceHypotheses, const SliceHypotheses &crSliceHypotheses, unsigned int &bestSliceIndex) const
	Get the slice with the most neutrino induced hits using Monte-Carlo information. More...

bool	PassesQualityCuts (const pandora::Algorithm *const pAlgorithm, const float purity, const float completeness) const
	Determine if the event passes the selection cuts for training and has the required NUANCE code. More...

void	Collect2DHits (const pandora::PfoList &pfos, pandora::CaloHitList &reconstructedCaloHitList, const pandora::CaloHitSet &reconstructableCaloHitSet) const
	Collect all 2D hits in a supplied list of Pfos and push them on to an existing hit list, check so not to double count. More...

unsigned int	CountNeutrinoInducedHits (const pandora::CaloHitList &caloHitList) const
	Count the number of neutrino induced hits in a given list using MC information. More...

int	GetNuanceCode (const pandora::Algorithm *const pAlgorithm) const
	Use the current MCParticle list to get the nuance code of the neutrino in the event. More...

void	SelectAllPfos (const pandora::Algorithm *const pAlgorithm, const SliceHypotheses &hypotheses, pandora::PfoList &selectedPfos) const
	Select all pfos under the same hypothesis. More...

void	SelectPfosByProbability (const pandora::Algorithm *const pAlgorithm, const SliceHypotheses &nuSliceHypotheses, const SliceHypotheses &crSliceHypotheses, const SliceFeaturesVector &sliceFeaturesVector, pandora::PfoList &selectedPfos) const
	Select pfos based on the probability that their slice contains a neutrino interaction. More...

void	SelectPfos (const pandora::PfoList &pfos, pandora::PfoList &selectedPfos) const
	Add the given pfos to the selected Pfo list. More...

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

Private Attributes
bool	m_useTrainingMode
	Should use training mode. If true, training examples will be written to the output file. More...

std::string	m_trainingOutputFile
	Output file name for training examples. More...

bool	m_selectNuanceCode
	Should select training events by nuance code. More...

int	m_nuance
	Nuance code to select for training. More...

float	m_minPurity
	Minimum purity of the best slice to use event for training. More...

float	m_minCompleteness
	Minimum completeness of the best slice to use event for training. More...

float	m_minProbability
	Minimum probability required to classify a slice as the neutrino. More...

unsigned int	m_maxNeutrinos
	The maximum number of neutrinos to select in any one event. More...

SupportVectorMachine	m_supportVectorMachine
	The support vector machine. More...

std::string	m_filePathEnvironmentVariable
	The environment variable providing a list of paths to svm files. More...

Detailed Description

NeutrinoIdTool class.

Compares the neutrino and cosmic hypotheses of all of the slices in the event. Uses an SVM to calculate the probability of each slice containing a neutrino interaction. The N slices with the highest probabilities are identified as a neutrino (if sufficiently probable) all other slices are deemed cosmogenic.

If training mode is switched on, then the tool will write SVM training exmples to the specified output file. The events selected for training must pass (user configurable) slicing quality cuts. Users may also select events based on their interaction type (nuance code).

Definition at line 30 of file NeutrinoIdTool.h.

Member Typedef Documentation

typedef std::vector<SliceFeatures> lar_content::NeutrinoIdTool::SliceFeaturesVector

private

Definition at line 149 of file NeutrinoIdTool.h.

typedef std::pair<unsigned int, float> lar_content::NeutrinoIdTool::UintFloatPair

private

Definition at line 148 of file NeutrinoIdTool.h.

Constructor & Destructor Documentation

lar_content::NeutrinoIdTool::NeutrinoIdTool ( )

Default constructor.

Definition at line 28 of file NeutrinoIdTool.cc.

                                :
     m_useTrainingMode(false),
     m_selectNuanceCode(false),
     m_nuance(-std::numeric_limits<int>::max()),
     m_minPurity(0.9f),
     m_minCompleteness(0.9f),
     m_minProbability(0.0f),
     m_maxNeutrinos(1),
     m_filePathEnvironmentVariable("FW_SEARCH_PATH")
 {
 }

Member Function Documentation

void lar_content::NeutrinoIdTool::Collect2DHits	(	const pandora::PfoList &	pfos,
		pandora::CaloHitList &	reconstructedCaloHitList,
		const pandora::CaloHitSet &	reconstructableCaloHitSet
	)		const

private

Collect all 2D hits in a supplied list of Pfos and push them on to an existing hit list, check so not to double count.

Parameters

pfos	input list of pfos
reconstructedCaloHitList	output list of all 2d hits in the input pfos
reconstructableCaloHitSet	set of reconstructable calo hits

Definition at line 150 of file NeutrinoIdTool.cc.

References lar_content::LArPfoHelper::GetCaloHits().

Referenced by GetBestMCSliceIndex().

 {
     CaloHitList collectedHits;
     LArPfoHelper::GetCaloHits(pfos, TPC_VIEW_U, collectedHits);
     LArPfoHelper::GetCaloHits(pfos, TPC_VIEW_V, collectedHits);
     LArPfoHelper::GetCaloHits(pfos, TPC_VIEW_W, collectedHits);
 
     for (const CaloHit *const pCaloHit : collectedHits)
     {
         if (!reconstructableCaloHitSet.count(pCaloHit))
             continue;
 
         // Ensure no hits have been double counted
         if (std::find(reconstructedCaloHitList.begin(), reconstructedCaloHitList.end(), pCaloHit) == reconstructedCaloHitList.end())
             reconstructedCaloHitList.push_back(pCaloHit);
     }
 }

unsigned int lar_content::NeutrinoIdTool::CountNeutrinoInducedHits ( const pandora::CaloHitList & caloHitList ) const

private

Count the number of neutrino induced hits in a given list using MC information.

Parameters

caloHitSet input list of calo hits

Returns: the number of neutrino induced hits in the input list

Definition at line 170 of file NeutrinoIdTool.cc.

References lar_content::LArMCParticleHelper::GetParentMCParticle(), and lar_content::LArMCParticleHelper::IsNeutrino().

Referenced by GetBestMCSliceIndex().

 {
     unsigned int nNuHits(0);
     for (const CaloHit *const pCaloHit : caloHitList)
     {
         try
         {
             if (LArMCParticleHelper::IsNeutrino(LArMCParticleHelper::GetParentMCParticle(MCParticleHelper::GetMainMCParticle(pCaloHit))))
                 nNuHits++;
         }
         catch (const StatusCodeException &)
         {
         }
     }
 
     return nNuHits;
 }

bool lar_content::NeutrinoIdTool::GetBestMCSliceIndex	(	const pandora::Algorithm *const	pAlgorithm,
		const SliceHypotheses &	nuSliceHypotheses,
		const SliceHypotheses &	crSliceHypotheses,
		unsigned int &	bestSliceIndex
	)		const

private

Get the slice with the most neutrino induced hits using Monte-Carlo information.

Parameters

pAlgorithm	address of the master algorithm
nuSliceHypotheses	the input neutrino slice hypotheses
crSliceHypotheses	the input cosmic slice hypotheses
bestSliceIndex	the index of the slice with the most neutrino hits

Returns: does the best slice pass the quality cuts for training?

Definition at line 87 of file NeutrinoIdTool.cc.

References Collect2DHits(), CountNeutrinoInducedHits(), f, lar_content::LArMCParticleHelper::GetMCPrimaryMap(), lar_content::LArMCParticleHelper::PrimaryParameters::m_maxPhotonPropagation, lar_content::LArMCParticleHelper::PrimaryParameters::m_selectInputHits, PassesQualityCuts(), and lar_content::LArMCParticleHelper::SelectCaloHits().

Referenced by SelectOutputPfos().

 {
     unsigned int nHitsInBestSlice(0), nNuHitsInBestSlice(0);
 
     // Get all hits in all slices to find true number of mc hits
     const CaloHitList *pAllReconstructedCaloHitList(nullptr);
     PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::GetCurrentList(*pAlgorithm, pAllReconstructedCaloHitList));
 
     const MCParticleList *pMCParticleList(nullptr);
     PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::GetCurrentList(*pAlgorithm, pMCParticleList));
 
     // Obtain map: [mc particle -> primary mc particle]
     LArMCParticleHelper::MCRelationMap mcToPrimaryMCMap;
     LArMCParticleHelper::GetMCPrimaryMap(pMCParticleList, mcToPrimaryMCMap);
 
     // Remove non-reconstructable hits, e.g. those downstream of a neutron
     CaloHitList reconstructableCaloHitList;
     LArMCParticleHelper::PrimaryParameters parameters;
     LArMCParticleHelper::SelectCaloHits(pAllReconstructedCaloHitList, mcToPrimaryMCMap, reconstructableCaloHitList, parameters.m_selectInputHits, parameters.m_maxPhotonPropagation);
 
     const int nuNHitsTotal(this->CountNeutrinoInducedHits(reconstructableCaloHitList));
     const CaloHitSet reconstructableCaloHitSet(reconstructableCaloHitList.begin(), reconstructableCaloHitList.end()); 
 
     for (unsigned int sliceIndex = 0, nSlices = nuSliceHypotheses.size(); sliceIndex < nSlices; ++sliceIndex)
     {
         CaloHitList reconstructedCaloHitList;
         this->Collect2DHits(crSliceHypotheses.at(sliceIndex), reconstructedCaloHitList, reconstructableCaloHitSet);
 
         for (const ParticleFlowObject *const pNeutrino : nuSliceHypotheses.at(sliceIndex))
         {
             const PfoList &nuFinalStates(pNeutrino->GetDaughterPfoList());
             this->Collect2DHits(nuFinalStates, reconstructedCaloHitList, reconstructableCaloHitSet);
         }
 
         const unsigned int nNuHits(this->CountNeutrinoInducedHits(reconstructedCaloHitList));
 
         if (nNuHits > nNuHitsInBestSlice)
         {
             nNuHitsInBestSlice = nNuHits;
             nHitsInBestSlice = reconstructedCaloHitList.size();
             bestSliceIndex = sliceIndex;
         }
     }
 
     // ATTN for events with no neutrino induced hits, default neutrino purity and completeness to zero
     const float purity(nHitsInBestSlice > 0 ? static_cast<float>(nNuHitsInBestSlice) / static_cast<float>(nHitsInBestSlice) : 0.f);
     const float completeness(nuNHitsTotal > 0 ? static_cast<float>(nNuHitsInBestSlice) / static_cast<float>(nuNHitsTotal) : 0.f);
 
     return this->PassesQualityCuts(pAlgorithm, purity, completeness);
 }

int lar_content::NeutrinoIdTool::GetNuanceCode ( const pandora::Algorithm *const pAlgorithm ) const

private

Use the current MCParticle list to get the nuance code of the neutrino in the event.

Parameters

pAlgorithm address of the master algorithm

Returns: the nuance code of the event

Definition at line 190 of file NeutrinoIdTool.cc.

References lar_content::LArMCParticleHelper::GetNuanceCode(), and lar_content::LArMCParticleHelper::GetTrueNeutrinos().

Referenced by PassesQualityCuts().

 {
     const MCParticleList *pMCParticleList = nullptr;
     PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::GetCurrentList(*pAlgorithm, pMCParticleList));
 
     MCParticleVector trueNeutrinos;
     LArMCParticleHelper::GetTrueNeutrinos(pMCParticleList, trueNeutrinos);
 
     if (trueNeutrinos.size() != 1)
     {
         std::cout << "NeutrinoIdTool::GetNuanceCode - Error: number of true neutrinos in event must be exactly one" << std::endl;
         throw StatusCodeException(STATUS_CODE_OUT_OF_RANGE);
     }
 
     return LArMCParticleHelper::GetNuanceCode(trueNeutrinos.front());
 }

void lar_content::NeutrinoIdTool::GetSliceFeatures	(	const NeutrinoIdTool *const	pTool,
		const SliceHypotheses &	nuSliceHypotheses,
		const SliceHypotheses &	crSliceHypotheses,
		SliceFeaturesVector &	sliceFeaturesVector
	)		const

private

Get the features of each slice.

Parameters

pTool	the address of the this NeutrinoId tool
nuSliceHypotheses	the input neutrino slice hypotheses
crSliceHypotheses	the input cosmic slice hypotheses
sliceFeaturesVector	vector to hold the slice features

Definition at line 79 of file NeutrinoIdTool.cc.

Referenced by SelectOutputPfos().

 {
     for (unsigned int sliceIndex = 0, nSlices = nuSliceHypotheses.size(); sliceIndex < nSlices; ++sliceIndex)
         sliceFeaturesVector.push_back(SliceFeatures(nuSliceHypotheses.at(sliceIndex), crSliceHypotheses.at(sliceIndex), pTool));
 }

bool lar_content::NeutrinoIdTool::PassesQualityCuts	(	const pandora::Algorithm *const	pAlgorithm,
		const float	purity,
		const float	completeness
	)		const

private

Determine if the event passes the selection cuts for training and has the required NUANCE code.

Parameters

pAlgorithm	address of the master algorithm
purity	purity of best slice
completeness	completeness of best slice

Returns: does the evenr pass the quality cuts on purity and completeness and has the required NUANCE code

Definition at line 140 of file NeutrinoIdTool.cc.

References GetNuanceCode(), m_minCompleteness, m_minPurity, m_nuance, and m_selectNuanceCode.

Referenced by GetBestMCSliceIndex().

 {
     if (purity < m_minPurity || completeness < m_minCompleteness) return false;
     if (m_selectNuanceCode && (this->GetNuanceCode(pAlgorithm) != m_nuance)) return false;
 
     return true;
 }

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

private

Definition at line 515 of file NeutrinoIdTool.cc.

References lar_content::LArFileHelper::FindFileInPath(), lar_content::SupportVectorMachine::Initialize(), m_filePathEnvironmentVariable, m_maxNeutrinos, m_minCompleteness, m_minProbability, m_minPurity, m_nuance, m_selectNuanceCode, m_supportVectorMachine, m_trainingOutputFile, and m_useTrainingMode.

 {
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "UseTrainingMode", m_useTrainingMode));
 
     if (m_useTrainingMode)
     {
         PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle,
             "TrainingOutputFileName", m_trainingOutputFile));
     }
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "MinimumPurity", m_minPurity));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "MinimumCompleteness", m_minCompleteness));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "SelectNuanceCode", m_selectNuanceCode));
 
     if (m_selectNuanceCode)
     {
         PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle,
             "NuanceCode", m_nuance));
     }
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "MinimumNeutrinoProbability", m_minProbability));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "MaximumNeutrinos", m_maxNeutrinos));
 
     PANDORA_RETURN_RESULT_IF_AND_IF(STATUS_CODE_SUCCESS, STATUS_CODE_NOT_FOUND, !=, XmlHelper::ReadValue(xmlHandle,
         "FilePathEnvironmentVariable", m_filePathEnvironmentVariable));
 
     if (!m_useTrainingMode)
     {
         std::string svmName;
         PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle,
             "SvmName", svmName));
 
         std::string svmFileName;
         PANDORA_RETURN_RESULT_IF(STATUS_CODE_SUCCESS, !=, XmlHelper::ReadValue(xmlHandle,
             "SvmFileName", svmFileName));
 
         const std::string fullSvmFileName(LArFileHelper::FindFileInPath(svmFileName, m_filePathEnvironmentVariable));
         m_supportVectorMachine.Initialize(fullSvmFileName, svmName);
     }
 
     return STATUS_CODE_SUCCESS;
 }

void lar_content::NeutrinoIdTool::SelectAllPfos	(	const pandora::Algorithm *const	pAlgorithm,
		const SliceHypotheses &	hypotheses,
		pandora::PfoList &	selectedPfos
	)		const

private

Select all pfos under the same hypothesis.

Parameters

pAlgorithm	address of the master algorithm
hypotheses	the lists of slices under a certain hypothesis
selectedPfos	the list of pfos to populate

Definition at line 209 of file NeutrinoIdTool.cc.

References SelectPfos().

Referenced by SelectOutputPfos().

 {
     for (const PfoList &pfos : hypotheses)
     {
         for (const ParticleFlowObject *const pPfo : pfos)
         {
             object_creation::ParticleFlowObject::Metadata metadata;
             metadata.m_propertiesToAdd["NuScore"] = -1.f;
             PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::ParticleFlowObject::AlterMetadata(*pAlgorithm, pPfo, metadata));
         }
 
         this->SelectPfos(pfos, selectedPfos);
     }
 }

void lar_content::NeutrinoIdTool::SelectOutputPfos	(	const pandora::Algorithm *const	pAlgorithm,
		const SliceHypotheses &	nuSliceHypotheses,
		const SliceHypotheses &	crSliceHypotheses,
		pandora::PfoList &	selectedPfos
	)

virtual

Select which reconstruction hypotheses to use; neutrino outcomes or cosmic-ray muon outcomes for each slice.

Parameters

pAlgorithm	the address of the master instance, used to access MCParticles when in training mode
nuSliceHypotheses	the parent pfos representing the neutrino outcome for each slice
crSliceHypotheses	the parent pfos representing the cosmic-ray muon outcome for each slice
sliceNuPfos	to receive the list of selected pfos

Implements lar_content::SliceIdBaseTool.

Definition at line 42 of file NeutrinoIdTool.cc.

References GetBestMCSliceIndex(), lar_content::NeutrinoIdTool::SliceFeatures::GetFeatureVector(), GetSliceFeatures(), m_trainingOutputFile, m_useTrainingMode, max, lar_content::LArMvaHelper::ProduceTrainingExample(), SelectAllPfos(), and SelectPfosByProbability().

 {
     if (nuSliceHypotheses.size() != crSliceHypotheses.size())
         throw StatusCodeException(STATUS_CODE_INVALID_PARAMETER);
 
     const unsigned int nSlices(nuSliceHypotheses.size());
     if (nSlices == 0) return;
 
     SliceFeaturesVector sliceFeaturesVector;
     this->GetSliceFeatures(this, nuSliceHypotheses, crSliceHypotheses, sliceFeaturesVector);
 
     if (m_useTrainingMode)
     {
         // ATTN in training mode, just return everything as a cosmic-ray
         this->SelectAllPfos(pAlgorithm, crSliceHypotheses, selectedPfos);
 
         unsigned int bestSliceIndex(std::numeric_limits<unsigned int>::max());
         if (!this->GetBestMCSliceIndex(pAlgorithm, nuSliceHypotheses, crSliceHypotheses, bestSliceIndex)) return;
 
         for (unsigned int sliceIndex = 0; sliceIndex < nSlices; ++sliceIndex)
         {
             const SliceFeatures &features(sliceFeaturesVector.at(sliceIndex));
             if (!features.IsFeatureVectorAvailable()) continue;
 
             LArMvaHelper::MvaFeatureVector featureVector;
             features.GetFeatureVector(featureVector);
             LArMvaHelper::ProduceTrainingExample(m_trainingOutputFile, sliceIndex == bestSliceIndex, featureVector);
         }
 
         return;
     }
 
     this->SelectPfosByProbability(pAlgorithm, nuSliceHypotheses, crSliceHypotheses, sliceFeaturesVector, selectedPfos);
 }

void lar_content::NeutrinoIdTool::SelectPfos	(	const pandora::PfoList &	pfos,
		pandora::PfoList &	selectedPfos
	)		const

private

Add the given pfos to the selected Pfo list.

Parameters

pfos	the pfos to select
selectedPfos	the list of pfos to populate

Definition at line 280 of file NeutrinoIdTool.cc.

Referenced by SelectAllPfos(), and SelectPfosByProbability().

 {
     selectedPfos.insert(selectedPfos.end(), pfos.begin(), pfos.end());
 }

void lar_content::NeutrinoIdTool::SelectPfosByProbability	(	const pandora::Algorithm *const	pAlgorithm,
		const SliceHypotheses &	nuSliceHypotheses,
		const SliceHypotheses &	crSliceHypotheses,
		const SliceFeaturesVector &	sliceFeaturesVector,
		pandora::PfoList &	selectedPfos
	)		const

private

Select pfos based on the probability that their slice contains a neutrino interaction.

Parameters

pAlgorithm	address of the master algorithm
nuSliceHypotheses	the input neutrino slice hypotheses
crSliceHypotheses	the input cosmic slice hypotheses
sliceFeaturesVector	vector holding the slice features
selectedPfos	the list of pfos to populate

Definition at line 226 of file NeutrinoIdTool.cc.

References m_maxNeutrinos, m_minProbability, m_supportVectorMachine, and SelectPfos().

Referenced by SelectOutputPfos().

 {
     // Calculate the probability of each slice that passes the minimum probability cut
     std::vector<UintFloatPair> sliceIndexProbabilityPairs;
     for (unsigned int sliceIndex = 0, nSlices = nuSliceHypotheses.size(); sliceIndex < nSlices; ++sliceIndex)
     {
         const float nuProbability(sliceFeaturesVector.at(sliceIndex).GetNeutrinoProbability(m_supportVectorMachine));
 
         for (const ParticleFlowObject *const pPfo : crSliceHypotheses.at(sliceIndex))
         {
             object_creation::ParticleFlowObject::Metadata metadata;
             metadata.m_propertiesToAdd["NuScore"] = nuProbability;
             PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::ParticleFlowObject::AlterMetadata(*pAlgorithm, pPfo, metadata));
         }
 
         for (const ParticleFlowObject *const pPfo : nuSliceHypotheses.at(sliceIndex))
         {
             object_creation::ParticleFlowObject::Metadata metadata;
             metadata.m_propertiesToAdd["NuScore"] = nuProbability;
             PANDORA_THROW_RESULT_IF(STATUS_CODE_SUCCESS, !=, PandoraContentApi::ParticleFlowObject::AlterMetadata(*pAlgorithm, pPfo, metadata));
         }
 
         if (nuProbability < m_minProbability)
         {
             this->SelectPfos(crSliceHypotheses.at(sliceIndex), selectedPfos);
             continue;
         }
 
         sliceIndexProbabilityPairs.push_back(UintFloatPair(sliceIndex, nuProbability));
     }
 
     // Sort the slices by probability
     std::sort(sliceIndexProbabilityPairs.begin(), sliceIndexProbabilityPairs.end(), [] (const UintFloatPair &a, const UintFloatPair &b)
     {
         return (a.second > b.second);
     });
 
     // Select the first m_maxNeutrinos as neutrinos, and the rest as cosmic
     unsigned int nNuSlices(0);
     for (const UintFloatPair &slice : sliceIndexProbabilityPairs)
     {
         if (nNuSlices < m_maxNeutrinos)
         {
             this->SelectPfos(nuSliceHypotheses.at(slice.first), selectedPfos);
             nNuSlices++;
             continue;
         }
 
         this->SelectPfos(crSliceHypotheses.at(slice.first), selectedPfos);
     }
 }

Member Data Documentation

std::string lar_content::NeutrinoIdTool::m_filePathEnvironmentVariable

private

The environment variable providing a list of paths to svm files.

Definition at line 254 of file NeutrinoIdTool.h.

Referenced by ReadSettings().

unsigned int lar_content::NeutrinoIdTool::m_maxNeutrinos

private

The maximum number of neutrinos to select in any one event.

Definition at line 251 of file NeutrinoIdTool.h.

Referenced by ReadSettings(), and SelectPfosByProbability().

float lar_content::NeutrinoIdTool::m_minCompleteness

private

Minimum completeness of the best slice to use event for training.

Definition at line 247 of file NeutrinoIdTool.h.

Referenced by PassesQualityCuts(), and ReadSettings().

float lar_content::NeutrinoIdTool::m_minProbability

private

Minimum probability required to classify a slice as the neutrino.

Definition at line 250 of file NeutrinoIdTool.h.

Referenced by ReadSettings(), and SelectPfosByProbability().

float lar_content::NeutrinoIdTool::m_minPurity

private

Minimum purity of the best slice to use event for training.

Definition at line 246 of file NeutrinoIdTool.h.

Referenced by PassesQualityCuts(), and ReadSettings().

int lar_content::NeutrinoIdTool::m_nuance

private

Nuance code to select for training.

Definition at line 245 of file NeutrinoIdTool.h.

Referenced by PassesQualityCuts(), and ReadSettings().

bool lar_content::NeutrinoIdTool::m_selectNuanceCode

private

Should select training events by nuance code.

Definition at line 244 of file NeutrinoIdTool.h.

Referenced by PassesQualityCuts(), and ReadSettings().

SupportVectorMachine lar_content::NeutrinoIdTool::m_supportVectorMachine

private

The support vector machine.

Definition at line 253 of file NeutrinoIdTool.h.

Referenced by ReadSettings(), and SelectPfosByProbability().

std::string lar_content::NeutrinoIdTool::m_trainingOutputFile

private

Output file name for training examples.

Definition at line 243 of file NeutrinoIdTool.h.

Referenced by ReadSettings(), and SelectOutputPfos().

bool lar_content::NeutrinoIdTool::m_useTrainingMode

private

Should use training mode. If true, training examples will be written to the output file.

Definition at line 242 of file NeutrinoIdTool.h.

Referenced by ReadSettings(), and SelectOutputPfos().

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

/cvmfs/larsoft.opensciencegrid.org/products/larpandoracontent/v03_14_03/source/larpandoracontent/LArControlFlow/NeutrinoIdTool.h
/cvmfs/larsoft.opensciencegrid.org/products/larpandoracontent/v03_14_03/source/larpandoracontent/LArControlFlow/NeutrinoIdTool.cc

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