def __init__(self, name="TrigTauRecMerged_TauCaloOnlyMVA"):
super(TrigTauRecMerged_TauCaloOnlyMVA, self).__init__(name)
import TrigTauRec.TrigTauAlgorithmsHolder as taualgs
tools = []
taualgs.setPrefix("TrigTauCaloOnlyMVA_")
# Only include tools needed for calo pre-selection
# Set seedcalo energy scale (Full RoI)
tools.append(taualgs.getJetSeedBuilder())
# Set LC energy scale (0.2 cone) and intermediate axis (corrected for vertex: useless at trigger)
tools.append(taualgs.getTauAxis())
# Calibrate to TES
tools.append(
taualgs.getEnergyCalibrationLC(correctEnergy=True,
correctAxis=False,
postfix='_onlyEnergy',
caloOnly=True))
# Calculate cell-based quantities: strip variables, EM and Had energies/radii, centFrac, isolFrac and ring energies
tools.append(taualgs.getCellVariables(cellConeSize=0.2))
# Compute MVA TES (ATR-17649), stores MVA TES as default tau pt()
tools.append(taualgs.getMvaTESVariableDecorator())
tools.append(taualgs.getMvaTESEvaluator())
for tool in tools:
tool.inTrigger = True
tool.calibFolder = 'TrigTauRec/00-11-02/'
self.Tools = tools
## add beam type flag
from AthenaCommon.BeamFlags import jobproperties
self.BeamType = jobproperties.Beam.beamType()
def __init__(self, name="TrigTauRecMerged_TauCaloOnlyMVA"):
super(TrigTauRecMerged_TauCaloOnlyMVA, self).__init__(name)
self._mytools = []
# monitoring part. To switch off do in topOption TriggerFlags.enableMonitoring = []
from TrigTauRec.TrigTauRecMonitoring import TrigTauRecValidationMonitoring, TrigTauRecOnlineMonitoring
validation = TrigTauRecValidationMonitoring()
online = TrigTauRecOnlineMonitoring()
from TrigTimeMonitor.TrigTimeHistToolConfig import TrigTimeHistToolConfig
time = TrigTimeHistToolConfig("Time")
self.AthenaMonTools = [time, validation, online]
import TrigTauRec.TrigTauAlgorithmsHolder as taualgs
tools = []
taualgs.setPrefix("TrigTauCaloOnlyMVA_")
# Collection name - not stored
self.OutputCollection = "TrigTauRecCaloOnly"
# Only include tools needed for calo pre-selection
# Set seedcalo energy scale (Full RoI)
tools.append(taualgs.getJetSeedBuilder())
# Set LC energy scale (0.2 cone) and intermediate axis (corrected for vertex: useless at trigger)
tools.append(taualgs.getTauAxis())
# Calibrate to TES
tools.append(
taualgs.getEnergyCalibrationLC(correctEnergy=True,
correctAxis=False,
postfix='_onlyEnergy',
caloOnly=True))
# Calculate cell-based quantities: strip variables, EM and Had energies/radii, centFrac, isolFrac and ring energies
tools.append(taualgs.getCellVariables(cellConeSize=0.2))
# Compute MVA TES (ATR-17649), stores MVA TES as default tau pt()
tools.append(taualgs.getMvaTESVariableDecorator())
tools.append(taualgs.getMvaTESEvaluator())
for tool in tools:
tool.inTrigger = True
tool.calibFolder = 'TrigTauRec/00-11-02/'
pass
self.Tools = tools
## add beam type flag
from AthenaCommon.BeamFlags import jobproperties
self.BeamType = jobproperties.Beam.beamType()
def __init__(self,
name="TrigTauRecMerged_TauPrecisionMVA",
doMVATES=False,
doTrackBDT=False,
doRNN=False):
super(TrigTauRecMerged_TauPrecisionMVA, self).__init__(name)
self._mytools = []
# monitoring part. To switch off do in topOption TriggerFlags.enableMonitoring = []
from TrigTauRec.TrigTauRecMonitoring import TrigTauRecValidationMonitoring, TrigTauRecOnlineMonitoring
validation = TrigTauRecValidationMonitoring()
online = TrigTauRecOnlineMonitoring()
from TrigTimeMonitor.TrigTimeHistToolConfig import TrigTimeHistToolConfig
time = TrigTimeHistToolConfig("Time")
self.AthenaMonTools = [time, validation, online]
import TrigTauRec.TrigTauAlgorithmsHolder as taualgs
tools = []
# using same prefix as in TauPrecision sequence should be safe if tools with different configurations have different names
# e.g. TauTrackFinder in 2016 using dz0=2mm instead of 1mm in 2017
taualgs.setPrefix("TrigTau_")
# Collection name
self.OutputCollection = "TrigTauRecMerged"
# Include full set of tools
# Set seedcalo energy scale (Full RoI)
tools.append(taualgs.getJetSeedBuilder())
# Associate RoI vertex or Beamspot to tau - don't use TJVA
tools.append(taualgs.getTauVertexFinder(
doUseTJVA=False)) #don't use TJVA by default
# Set LC energy scale (0.2 cone) and intermediate axis (corrected for vertex: useless at trigger)
tools.append(taualgs.getTauAxis())
# for now, use 'doMVATES=False' to detect tracktwoEF, instead of introducing new flag
if not doMVATES:
# Count tracks with deltaZ0 cut of 1mm for tracktwoEF
tools.append(
taualgs.getTauTrackFinder(applyZ0cut=True, maxDeltaZ0=1))
else:
# tightened to 0.75 mm for tracktwoMVA (until the track BDT can be used)
tools.append(
taualgs.getTauTrackFinder(applyZ0cut=True,
maxDeltaZ0=0.75,
prefix='TrigTauTightDZ_'))
if doTrackBDT:
# BDT track classification
tools.append(taualgs.getTauTrackClassifier())
# Calibrate to calo TES
tools.append(
taualgs.getEnergyCalibrationLC(correctEnergy=True,
correctAxis=False,
postfix='_onlyEnergy'))
if doMVATES:
# Compute MVA TES (ATR-17649), stores MVA TES as default tau pt()
tools.append(taualgs.getMvaTESVariableDecorator())
tools.append(taualgs.getMvaTESEvaluator())
# Calculate cell-based quantities: strip variables, EM and Had energies/radii, centFrac, isolFrac and ring energies
tools.append(taualgs.getCellVariables(cellConeSize=0.2))
# tools.append(taualgs.getElectronVetoVars())
# Lifetime variables
tools.append(taualgs.getTauVertexVariables())
# Variables combining tracking and calorimeter information
tools.append(taualgs.getTauCommonCalcVars())
# Cluster-based sub-structure, with dRMax also
tools.append(taualgs.getTauSubstructure())
# tools.append(taualgs.getEnergyCalibrationLC(correctEnergy=False, correctAxis=True, postfix='_onlyAxis'))
tools.append(taualgs.getPileUpCorrection())
if doRNN:
# RNN tau ID
tools.append(
taualgs.getTauJetRNNEvaluator(
NetworkFile0P="rnnid_config_0p_v3.json",
NetworkFile1P="rnnid_config_1p_v3.json",
NetworkFile3P="rnnid_config_mp_v3.json",
MaxTracks=10,
MaxClusters=6,
MaxClusterDR=1.0))
# flattened RNN score and WP
tools.append(taualgs.getTauWPDecoratorJetRNN())
for tool in tools:
tool.inTrigger = True
tool.calibFolder = 'TrigTauRec/00-11-02/'
pass
self.Tools = tools
## add beam type flag
from AthenaCommon.BeamFlags import jobproperties
self.BeamType = jobproperties.Beam.beamType()