8 #ifndef LAR_MVA_PFO_CHARACTERISATION_ALGORITHM_H 9 #define LAR_MVA_PFO_CHARACTERISATION_ALGORITHM_H 1 19 #include "Pandora/PandoraInternal.h" 37 virtual bool IsClearTrack(
const pandora::ParticleFlowObject *
const pPfo)
const;
38 virtual bool IsClearTrack(
const pandora::Cluster *
const pCluster)
const;
39 pandora::StatusCode
ReadSettings(
const pandora::TiXmlHandle xmlHandle);
94 #endif // #ifndef LAR_MVA_PFO_CHARACTERISATION_ALGORITHM_H bool m_enableProbability
Whether to use probabilities instead of binary classification.
MvaPfoCharacterisationAlgorithm()
Default constructor.
std::string m_trainingOutputFile
The training output file.
pandora::StringVector m_algorithmToolNamesNoChargeInfo
Vector of strings saving feature tool order for use in feature calculation (missing W view) ...
float m_fiducialMinZ
Fiducial volume minimum z.
std::string m_caloHitListName
Name of input calo hit list.
float m_fiducialMaxX
Fiducial volume maximum x.
LArMCParticleHelper::PrimaryParameters m_primaryParameters
The mc particle primary selection parameters.
MvaPfoCharacterisationAlgorithm class.
std::string m_mcParticleListName
Name of input MC particle list.
unsigned int m_minCaloHitsCut
The minimum number of calo hits to qualify as a track.
bool m_testBeamMode
Whether the training set is from a test beam experiment.
T m_mvaNoChargeInfo
The mva for missing W view.
ClusterCharacterisationFeatureTool::FeatureToolMap m_featureToolMap
The feature tool map.
PfoCharacterisationFeatureTool::FeatureToolMap m_featureToolMapNoChargeInfo
FeatureToolMap as a map for missing W view.
bool m_applyReconstructabilityChecks
Whether to apply reconstructability checks during training.
bool m_applyFiducialCut
Whether to apply a fiducial volume cut during training.
std::map< std::string, MvaFeatureTool< Ts... > * > FeatureToolMap
Header file for the lar adaptive boosted decision tree class.
float m_fiducialMinY
Fiducial volume minimum y.
pandora::StatusCode ReadSettings(const pandora::TiXmlHandle xmlHandle)
Header file for the lar monte carlo particle helper helper class.
Header file for the lar support vector machine class.
std::string m_mvaNameNoChargeInfo
The name of the mva to find for PFOs missing the W view, and thus charge info.
bool PassesFiducialCut(const pandora::CartesianVector &vertex) const
Checks if the interaction vertex is within the fiducial volume.
float m_fiducialMaxY
Fiducial volume maximum y.
std::string m_mvaName
The name of the mva to find.
bool m_trainingSetMode
Whether to train.
Header file for the pfo characterisation base algorithm class.
float m_minProbabilityCut
The minimum probability to label a cluster as track-like.
std::string m_mvaFileName
The mva input file.
PfoCharacterisationBaseAlgorithm class.
MvaPfoCharacterisationAlgorithm< AdaBoostDecisionTree > BdtPfoCharacterisationAlgorithm
std::string m_mvaFileNameNoChargeInfo
The mva input file for PFOs missing the W view, and thus charge info.
virtual bool IsClearTrack(const pandora::ParticleFlowObject *const pPfo) const
Whether pfo is identified as a clear track.
PfoCharacterisationFeatureTool::FeatureToolMap m_featureToolMapThreeD
FeatureToolMap as a map for 3D info.
float m_fiducialMinX
Fiducial volume minimum x.
std::string m_filePathEnvironmentVariable
The environment variable providing a list of paths to mva files.
MvaPfoCharacterisationAlgorithm< SupportVectorMachine > SvmPfoCharacterisationAlgorithm
pandora::StringVector m_algorithmToolNames
Vector of strings saving feature tool order for use in feature calculation.
float m_fiducialMaxZ
Fiducial volume maximum z.
bool m_persistFeatures
Whether to write the features to the properties map.
bool m_useThreeDInformation
Whether to use 3D information.