diff --git a/Reconstruction/tauRec/python/TauAlgorithmsHolder.py b/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
index d36f039942a67ef0ac66ed44799a332bfeb182be..500b1bc470db0521a9e9f8d9a1f5e12c4b6e1761 100644
--- a/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
+++ b/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
@@ -254,21 +254,6 @@ def getTauCommonCalcVars():
cached_instances[_name] = TauCommonCalcVars
return TauCommonCalcVars
-
-#########################################################################
-# Tau Test
-def getTauTestDump():
- _name = sPrefix + 'TauTestDump'
-
- if _name in cached_instances:
- return cached_instances[_name]
-
- from tauRecTools.tauRecToolsConf import TauTestDump
- TauTestDump = TauTestDump(name = _name)
-
- cached_instances[_name] = TauTestDump
- return TauTestDump
-
#########################################################################
# Tau Vertex Variables
def getTauVertexVariables():
@@ -594,7 +579,7 @@ def getTauTrackFinder(removeDuplicateTracks=True):
tauParticleCache = getParticleCache(),
removeDuplicateCoreTracks = removeDuplicateTracks,
Key_trackPartInputContainer = _DefaultTrackContainer,
- Key_LargeD0TrackInputContainer = _DefaultLargeD0TrackContainer if tauFlags.useLargeD0Tracks else "",
+ Key_LargeD0TrackInputContainer = _DefaultLargeD0TrackContainer if tauFlags.associateLRT() else "",
TrackToVertexIPEstimator = getTauTrackToVertexIPEstimator(),
#maxDeltaZ0wrtLeadTrk = 2, #in mm
#removeTracksOutsideZ0wrtLeadTrk = True
@@ -614,7 +599,7 @@ def getTauClusterFinder():
from JetRec.JetRecFlags import jetFlags
doJetVertexCorrection = False
- if tauFlags.isStandalone:
+ if tauFlags.isStandalone():
doJetVertexCorrection = True
if jetFlags.useVertices() and jetFlags.useTracks():
doJetVertexCorrection = True
@@ -658,72 +643,8 @@ def getTauCombinedTES():
cached_instances[_name] = TauCombinedTES
return TauCombinedTES
-#########################################################################
-def getTauTrackClassifier():
- _name = sPrefix + 'TauTrackClassifier'
-
- if _name in cached_instances:
- return cached_instances[_name]
-
- from AthenaCommon.AppMgr import ToolSvc
- from tauRecTools.tauRecToolsConf import tauRecTools__TauTrackClassifier as TauTrackClassifier
- from tauRecTools.tauRecToolsConf import tauRecTools__TrackMVABDT as TrackMVABDT
- import PyUtils.RootUtils as ru
- ROOT = ru.import_root()
- import cppyy
- cppyy.load_library('libxAODTau_cDict.so')
-
- # =========================================================================
- _BDT_TTCT_ITFT_0 = TrackMVABDT(name = _name + "_0",
- #InputWeightsPath = "TMVAClassification_BDT.weights.root",
- #Threshold = -0.005,
- InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[0][0],
- Threshold = tauFlags.tauRecMVATrackClassificationConfig()[0][1],
- ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.unclassified,
- SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
- BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
- calibFolder = tauFlags.tauRecToolsCVMFSPath(),
- )
- ToolSvc += _BDT_TTCT_ITFT_0
- cached_instances[_BDT_TTCT_ITFT_0.name] = _BDT_TTCT_ITFT_0
-
- _BDT_TTCT_ITFT_0_0 = TrackMVABDT(name = _name + "_0_0",
- #InputWeightsPath = "TMVAClassification_BDT_0.weights.root",
- #Threshold = -0.0074,
- InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[1][0],
- Threshold = tauFlags.tauRecMVATrackClassificationConfig()[1][1],
- ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
- SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
- BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedConversion,
- calibFolder = tauFlags.tauRecToolsCVMFSPath(),
- )
- ToolSvc += _BDT_TTCT_ITFT_0_0
- cached_instances[_BDT_TTCT_ITFT_0_0.name] = _BDT_TTCT_ITFT_0_0
-
- _BDT_TTCT_ITFT_0_1 = TrackMVABDT(name = _name + "_0_1",
- #InputWeightsPath = "TMVAClassification_BDT_1.weights.root",
- #Threshold = 0.0005,
- InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[2][0],
- Threshold = tauFlags.tauRecMVATrackClassificationConfig()[2][1],
- ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
- SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
- BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedFake,
- calibFolder = tauFlags.tauRecToolsCVMFSPath(),
- )
- ToolSvc += _BDT_TTCT_ITFT_0_1
- cached_instances[_BDT_TTCT_ITFT_0_1.name] = _BDT_TTCT_ITFT_0_1
-
- # create tool alg
- myTauTrackClassifier = TauTrackClassifier( name = _name,
- Classifiers = [_BDT_TTCT_ITFT_0, _BDT_TTCT_ITFT_0_0, _BDT_TTCT_ITFT_0_1] )
- #ToolSvc += TauTrackClassifier #only add to tool service sub tools to your tool, the main tool will be added via TauRecConfigured
- cached_instances[_name] = myTauTrackClassifier
-
- return myTauTrackClassifier
-
-########################################################################
-#
+########################################################################
def getTauTrackRNNClassifier():
_name = sPrefix + 'TauTrackRNNClassifier'
@@ -737,100 +658,26 @@ def getTauTrackRNNClassifier():
import cppyy
cppyy.load_library('libxAODTau_cDict')
- _RNN= TrackRNN(name = _name + "_0",
- InputWeightsPath = tauFlags.tauRecRNNTrackClassificationConfig()[0],
- calibFolder = tauFlags.tauRecToolsCVMFSPath(),
+ _RNN = TrackRNN(name = _name + "_0",
+ InputWeightsPath = tauFlags.tauRecRNNTrackClassificationConfig()[0],
+ calibFolder = tauFlags.tauRecToolsCVMFSPath(),
)
-
ToolSvc += _RNN
cached_instances[_RNN.name] = _RNN
-
+
+ _classifyLRT = True
+ if tauFlags.associateLRT() and not tauFlags.classifyLRT():
+ _classifyLRT = False
+
# create tool alg
myTauTrackClassifier = TauTrackRNNClassifier( name = _name,
- Classifiers = [_RNN] )
- cached_instances[_name] = myTauTrackClassifier
+ Classifiers = [_RNN],
+ classifyLRT = _classifyLRT )
+ cached_instances[_name] = myTauTrackClassifier
return myTauTrackClassifier
-########################################################################
-#
-def getTauWPDecoratorJetRNN():
- import PyUtils.RootUtils as ru
- ROOT = ru.import_root()
- import cppyy
- cppyy.load_library('libxAODTau_cDict')
-
- _name = sPrefix + 'TauWPDecoratorJetRNN'
- from tauRecTools.tauRecToolsConf import TauWPDecorator
- myTauWPDecorator = TauWPDecorator( name=_name,
- flatteningFile1Prong = "rnnid_mc16d_flat_1p.root",
- flatteningFile3Prong = "rnnid_mc16d_flat_3p.root",
- CutEnumVals =
- [ ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigVeryLoose, ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigLoose,
- ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigMedium, ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigTight ],
- SigEff1P = [0.95, 0.85, 0.75, 0.60],
- SigEff3P = [0.95, 0.75, 0.60, 0.45],
- ScoreName = "RNNJetScore",
- NewScoreName = "RNNJetScoreSigTrans",
- DefineWPs = True,
- )
- cached_instances[_name] = myTauWPDecorator
- return myTauWPDecorator
-
-
-#
-def getTauWPDecoratorJetBDT():
- import PyUtils.RootUtils as ru
- ROOT = ru.import_root()
- import cppyy
- cppyy.load_library('libxAODTau_cDict')
-
- _name = sPrefix + 'TauWPDecoratorJetBDT'
- from tauRecTools.tauRecToolsConf import TauWPDecorator
- myTauWPDecorator = TauWPDecorator( name=_name,
- flatteningFile1Prong = "FlatJetBDT1Pv2.root", #update
- flatteningFile3Prong = "FlatJetBDT3Pv2.root", #update
- CutEnumVals =
- [ ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigVeryLoose, ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigLoose,
- ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigMedium, ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigTight ],
- SigEff1P = [0.95, 0.85, 0.75, 0.60],
- SigEff3P = [0.95, 0.75, 0.60, 0.45],
- ScoreName = "BDTJetScore",
- NewScoreName = "BDTJetScoreSigTrans",
- DefineWPs = True,
- )
- cached_instances[_name] = myTauWPDecorator
- return myTauWPDecorator
-
-
-#
-def getTauWPDecoratorEleBDT():
- import PyUtils.RootUtils as ru
- ROOT = ru.import_root()
- import cppyy
- cppyy.load_library('libxAODTau_cDict')
-
- _name = sPrefix + 'TauWPDecoratorEleBDT'
- from tauRecTools.tauRecToolsConf import TauWPDecorator
- TauScoreFlatteningTool = TauWPDecorator( name=_name,
- flatteningFile1Prong = "EleBDTFlat1P.root",#update
- flatteningFile3Prong = "EleBDTFlat3P.root",#update
- UseEleBDT = True ,
- ScoreName = "BDTEleScore",
- NewScoreName = "BDTEleScoreSigTrans", #dynamic
- DefineWPs = True,
- CutEnumVals =
- [ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTLoose,
- ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTMedium,
- ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTTight],
- SigEff1P = [0.95, 0.85, 0.75],
- SigEff3P = [0.95, 0.85, 0.75],
- )
- cached_instances[_name] = TauScoreFlatteningTool
- return TauScoreFlatteningTool
-
-#
def getTauJetRNNEvaluator():
_name = sPrefix + 'TauJetRNN'
from tauRecTools.tauRecToolsConf import TauJetRNNEvaluator
@@ -853,18 +700,29 @@ def getTauJetRNNEvaluator():
return myTauJetRNNEvaluator
-def getTauJetBDTEvaluator(_n, weightsFile="", minNTracks=0, maxNTracks=10000, outputVarName="BDTJetScore", minAbsTrackEta=-1, maxAbsTrackEta=-1):
- _name = sPrefix + _n
- from tauRecTools.tauRecToolsConf import TauJetBDTEvaluator
- myTauJetBDTEvaluator = TauJetBDTEvaluator(name=_name,
- weightsFile=weightsFile, #update config?
- minNTracks=minNTracks,
- maxNTracks=maxNTracks,
- minAbsTrackEta=minAbsTrackEta,
- maxAbsTrackEta=maxAbsTrackEta,
- outputVarName=outputVarName)
- cached_instances[_name] = myTauJetBDTEvaluator
- return myTauJetBDTEvaluator
+def getTauWPDecoratorJetRNN():
+ import PyUtils.RootUtils as ru
+ ROOT = ru.import_root()
+ import cppyy
+ cppyy.load_library('libxAODTau_cDict')
+
+ _name = sPrefix + 'TauWPDecoratorJetRNN'
+ from tauRecTools.tauRecToolsConf import TauWPDecorator
+ myTauWPDecorator = TauWPDecorator( name=_name,
+ flatteningFile1Prong = "rnnid_mc16d_flat_1p.root",
+ flatteningFile3Prong = "rnnid_mc16d_flat_3p.root",
+ CutEnumVals =
+ [ ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigVeryLoose, ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigLoose,
+ ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigMedium, ROOT.xAOD.TauJetParameters.IsTauFlag.JetRNNSigTight ],
+ SigEff1P = [0.95, 0.85, 0.75, 0.60],
+ SigEff3P = [0.95, 0.75, 0.60, 0.45],
+ ScoreName = "RNNJetScore",
+ NewScoreName = "RNNJetScoreSigTrans",
+ DefineWPs = True,
+ )
+ cached_instances[_name] = myTauWPDecorator
+ return myTauWPDecorator
+
def getTauIDVarCalculator():
_name = sPrefix + 'TauIDVarCalculator'
@@ -979,3 +837,133 @@ def getTVATool():
cached_instances[_name] = TVATool
return TVATool
+
+
+# deprecated in R22
+
+def getTauTrackClassifier():
+ _name = sPrefix + 'TauTrackClassifier'
+
+ if _name in cached_instances:
+ return cached_instances[_name]
+
+ from AthenaCommon.AppMgr import ToolSvc
+ from tauRecTools.tauRecToolsConf import tauRecTools__TauTrackClassifier as TauTrackClassifier
+ from tauRecTools.tauRecToolsConf import tauRecTools__TrackMVABDT as TrackMVABDT
+
+ import PyUtils.RootUtils as ru
+ ROOT = ru.import_root()
+ import cppyy
+ cppyy.load_library('libxAODTau_cDict.so')
+
+ # =========================================================================
+ _BDT_TTCT_ITFT_0 = TrackMVABDT(name = _name + "_0",
+ #InputWeightsPath = "TMVAClassification_BDT.weights.root",
+ #Threshold = -0.005,
+ InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[0][0],
+ Threshold = tauFlags.tauRecMVATrackClassificationConfig()[0][1],
+ ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.unclassified,
+ SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
+ BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
+ calibFolder = tauFlags.tauRecToolsCVMFSPath(),
+ )
+ ToolSvc += _BDT_TTCT_ITFT_0
+ cached_instances[_BDT_TTCT_ITFT_0.name] = _BDT_TTCT_ITFT_0
+
+ _BDT_TTCT_ITFT_0_0 = TrackMVABDT(name = _name + "_0_0",
+ #InputWeightsPath = "TMVAClassification_BDT_0.weights.root",
+ #Threshold = -0.0074,
+ InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[1][0],
+ Threshold = tauFlags.tauRecMVATrackClassificationConfig()[1][1],
+ ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
+ SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedCharged,
+ BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedConversion,
+ calibFolder = tauFlags.tauRecToolsCVMFSPath(),
+ )
+ ToolSvc += _BDT_TTCT_ITFT_0_0
+ cached_instances[_BDT_TTCT_ITFT_0_0.name] = _BDT_TTCT_ITFT_0_0
+
+ _BDT_TTCT_ITFT_0_1 = TrackMVABDT(name = _name + "_0_1",
+ #InputWeightsPath = "TMVAClassification_BDT_1.weights.root",
+ #Threshold = 0.0005,
+ InputWeightsPath = tauFlags.tauRecMVATrackClassificationConfig()[2][0],
+ Threshold = tauFlags.tauRecMVATrackClassificationConfig()[2][1],
+ ExpectedFlag = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
+ SignalType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedIsolation,
+ BackgroundType = ROOT.xAOD.TauJetParameters.TauTrackFlag.classifiedFake,
+ calibFolder = tauFlags.tauRecToolsCVMFSPath(),
+ )
+ ToolSvc += _BDT_TTCT_ITFT_0_1
+ cached_instances[_BDT_TTCT_ITFT_0_1.name] = _BDT_TTCT_ITFT_0_1
+
+ # create tool alg
+ myTauTrackClassifier = TauTrackClassifier( name = _name,
+ Classifiers = [_BDT_TTCT_ITFT_0, _BDT_TTCT_ITFT_0_0, _BDT_TTCT_ITFT_0_1] )
+ #ToolSvc += TauTrackClassifier #only add to tool service sub tools to your tool, the main tool will be added via TauRecConfigured
+ cached_instances[_name] = myTauTrackClassifier
+
+ return myTauTrackClassifier
+
+
+def getTauJetBDTEvaluator(_n, weightsFile="", minNTracks=0, maxNTracks=10000, outputVarName="BDTJetScore", minAbsTrackEta=-1, maxAbsTrackEta=-1):
+ _name = sPrefix + _n
+ from tauRecTools.tauRecToolsConf import TauJetBDTEvaluator
+ myTauJetBDTEvaluator = TauJetBDTEvaluator(name=_name,
+ weightsFile=weightsFile,
+ minNTracks=minNTracks,
+ maxNTracks=maxNTracks,
+ minAbsTrackEta=minAbsTrackEta,
+ maxAbsTrackEta=maxAbsTrackEta,
+ outputVarName=outputVarName)
+ cached_instances[_name] = myTauJetBDTEvaluator
+ return myTauJetBDTEvaluator
+
+
+def getTauWPDecoratorJetBDT():
+ import PyUtils.RootUtils as ru
+ ROOT = ru.import_root()
+ import cppyy
+ cppyy.load_library('libxAODTau_cDict')
+
+ _name = sPrefix + 'TauWPDecoratorJetBDT'
+ from tauRecTools.tauRecToolsConf import TauWPDecorator
+ myTauWPDecorator = TauWPDecorator( name=_name,
+ flatteningFile1Prong = "FlatJetBDT1Pv2.root",
+ flatteningFile3Prong = "FlatJetBDT3Pv2.root",
+ CutEnumVals =
+ [ ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigVeryLoose, ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigLoose,
+ ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigMedium, ROOT.xAOD.TauJetParameters.IsTauFlag.JetBDTSigTight ],
+ SigEff1P = [0.95, 0.85, 0.75, 0.60],
+ SigEff3P = [0.95, 0.75, 0.60, 0.45],
+ ScoreName = "BDTJetScore",
+ NewScoreName = "BDTJetScoreSigTrans",
+ DefineWPs = True,
+ )
+ cached_instances[_name] = myTauWPDecorator
+ return myTauWPDecorator
+
+
+def getTauWPDecoratorEleBDT():
+ import PyUtils.RootUtils as ru
+ ROOT = ru.import_root()
+ import cppyy
+ cppyy.load_library('libxAODTau_cDict')
+
+ _name = sPrefix + 'TauWPDecoratorEleBDT'
+ from tauRecTools.tauRecToolsConf import TauWPDecorator
+ TauScoreFlatteningTool = TauWPDecorator( name=_name,
+ flatteningFile1Prong = "EleBDTFlat1P.root",
+ flatteningFile3Prong = "EleBDTFlat3P.root",
+ UseEleBDT = True ,
+ ScoreName = "BDTEleScore",
+ NewScoreName = "BDTEleScoreSigTrans",
+ DefineWPs = True,
+ CutEnumVals =
+ [ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTLoose,
+ ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTMedium,
+ ROOT.xAOD.TauJetParameters.IsTauFlag.EleBDTTight],
+ SigEff1P = [0.95, 0.85, 0.75],
+ SigEff3P = [0.95, 0.85, 0.75],
+ )
+ cached_instances[_name] = TauScoreFlatteningTool
+ return TauScoreFlatteningTool
diff --git a/Reconstruction/tauRec/python/tauRecFlags.py b/Reconstruction/tauRec/python/tauRecFlags.py
index cf7bbe7b8d2e33526d89ac856bc7bc2e93ae3e2e..79acd8834908321826da213fe9cc3f9e2f252e38 100644
--- a/Reconstruction/tauRec/python/tauRecFlags.py
+++ b/Reconstruction/tauRec/python/tauRecFlags.py
@@ -58,9 +58,15 @@ class doTJVA(JobProperty):
allowedTypes=['bool']
StoredValue=True
-class useLargeD0Tracks(JobProperty):
- """ Use LRT tracks in tau track finding """
- statusOn=False
+class associateLRT(JobProperty):
+ """ associate Large Radius Tracks with tau in TauTrackFinder """
+ statusOn=True
+ allowedTypes=['bool']
+ StoredValue=False
+
+class classifyLRT(JobProperty):
+ """ classify Large Radius Tracks in tau track classifier """
+ statusOn=True
allowedTypes=['bool']
StoredValue=False
@@ -256,7 +262,7 @@ class tauRecFlags(JobPropertyContainer):
jobproperties.add_Container(tauRecFlags)
# I want always the following flags in the Rec container
-_list_tau=[Enabled,doTauRec,isStandalone,tauRecSeedJetCollection,tauRecToolsCVMFSPath,doTJVA,useLargeD0Tracks,removeDuplicateCoreTracks,tauRecMVATrackClassification,tauRecRNNTrackClassification,tauRecMVATrackClassificationConfig,tauRecRNNTrackClassificationConfig,tauRecDecayModeNNClassifierConfig,tauRecCalibrateLCConfig,tauRecMvaTESConfig,tauRecCombinedTESConfig,tauRecTauJetRNNConfig,tauRecTauEleRNNConfig,tauRecSeedMinPt,tauRecSeedMaxEta,tauRecMinPt,tauRecMaxNTracks,tauRecToolsDevToolList,tauRecToolsDevToolListProcessor,doRunTauDiscriminant,doPanTau,doPi0,pi0EtCuts,pi0MVACuts_1prong,pi0MVACuts_mprong,shotPtCut_1Photon,shotPtCut_2Photons,useOldVertexFitterAPI]
+_list_tau=[Enabled,doTauRec,isStandalone,tauRecSeedJetCollection,tauRecToolsCVMFSPath,doTJVA,associateLRT,classifyLRT,removeDuplicateCoreTracks,tauRecMVATrackClassification,tauRecRNNTrackClassification,tauRecMVATrackClassificationConfig,tauRecRNNTrackClassificationConfig,tauRecDecayModeNNClassifierConfig,tauRecCalibrateLCConfig,tauRecMvaTESConfig,tauRecCombinedTESConfig,tauRecTauJetRNNConfig,tauRecTauEleRNNConfig,tauRecSeedMinPt,tauRecSeedMaxEta,tauRecMinPt,tauRecMaxNTracks,tauRecToolsDevToolList,tauRecToolsDevToolListProcessor,doRunTauDiscriminant,doPanTau,doPi0,pi0EtCuts,pi0MVACuts_1prong,pi0MVACuts_mprong,shotPtCut_1Photon,shotPtCut_2Photons,useOldVertexFitterAPI]
for j in _list_tau:
jobproperties.tauRecFlags.add_JobProperty(j)
del _list_tau
diff --git a/Reconstruction/tauRecTools/Root/TauJetRNNEvaluator.cxx b/Reconstruction/tauRecTools/Root/TauJetRNNEvaluator.cxx
index 097803c5ecbc2ee227ff3a6d44cf59ae47a596a7..886729e23713ebe0683e3551f80ad672a525d256 100644
--- a/Reconstruction/tauRecTools/Root/TauJetRNNEvaluator.cxx
+++ b/Reconstruction/tauRecTools/Root/TauJetRNNEvaluator.cxx
@@ -27,6 +27,7 @@ TauJetRNNEvaluator::TauJetRNNEvaluator(const std::string &name):
declareProperty("MaxClusters", m_max_clusters = 6);
declareProperty("MaxClusterDR", m_max_cluster_dr = 1.0f);
declareProperty("VertexCorrection", m_doVertexCorrection = true);
+ declareProperty("TrackClassification", m_doTrackClassification = true);
// Naming conventions for the network weight files:
declareProperty("InputLayerScalar", m_input_layer_scalar = "scalar");
@@ -182,7 +183,23 @@ const TauJetRNN* TauJetRNNEvaluator::get_rnn_3p() const {
}
StatusCode TauJetRNNEvaluator::get_tracks(const xAOD::TauJet &tau, std::vector<const xAOD::TauTrack *> &out) const {
- auto tracks = tau.allTracks();
+ std::vector<const xAOD::TauTrack*> tracks = tau.allTracks();
+
+ // Skip unclassified tracks:
+ // - the track is a LRT and classifyLRT = false
+ // - the track is not among the MaxNtracks highest-pt tracks in the track classifier
+ // - track classification is not run (trigger)
+ if(m_doTrackClassification) {
+ std::vector<const xAOD::TauTrack*>::iterator it = tracks.begin();
+ while(it != tracks.end()) {
+ if((*it)->flag(xAOD::TauJetParameters::unclassified)) {
+ it = tracks.erase(it);
+ }
+ else {
+ ++it;
+ }
+ }
+ }
// Sort by descending pt
auto cmp_pt = [](const xAOD::TauTrack *lhs, const xAOD::TauTrack *rhs) {
diff --git a/Reconstruction/tauRecTools/Root/TauTrackRNNClassifier.cxx b/Reconstruction/tauRecTools/Root/TauTrackRNNClassifier.cxx
index 9d23e5432ee40397458f3c3639b6dceae1385bde..00f2c9eb15024869be80183a2becac546985151e 100644
--- a/Reconstruction/tauRecTools/Root/TauTrackRNNClassifier.cxx
+++ b/Reconstruction/tauRecTools/Root/TauTrackRNNClassifier.cxx
@@ -23,8 +23,9 @@ using namespace tauRecTools;
//==============================================================================
//______________________________________________________________________________
-TauTrackRNNClassifier::TauTrackRNNClassifier(const std::string& sName)
- : TauRecToolBase(sName) {
+TauTrackRNNClassifier::TauTrackRNNClassifier(const std::string& name)
+ : TauRecToolBase(name) {
+ declareProperty("classifyLRT", m_classifyLRT = true);
}
//______________________________________________________________________________
@@ -35,11 +36,9 @@ TauTrackRNNClassifier::~TauTrackRNNClassifier()
//______________________________________________________________________________
StatusCode TauTrackRNNClassifier::initialize()
{
- ATH_MSG_DEBUG("intialize classifiers");
-
- for (auto cClassifier : m_vClassifier){
- ATH_MSG_INFO("TauTrackRNNClassifier tool : " << cClassifier );
- ATH_CHECK(cClassifier.retrieve());
+ for (auto classifier : m_vClassifier){
+ ATH_MSG_INFO("Intialize TauTrackRNNClassifier tool : " << classifier );
+ ATH_CHECK(classifier.retrieve());
}
return StatusCode::SUCCESS;
@@ -50,21 +49,41 @@ StatusCode TauTrackRNNClassifier::executeTrackClassifier(xAOD::TauJet& xTau, xAO
std::vector<xAOD::TauTrack*> vTracks = xAOD::TauHelpers::allTauTracksNonConst(&xTau, &tauTrackCon);
- for (xAOD::TauTrack* xTrack : vTracks)
- {
- // reset all track flags and set status to unclassified
- xTrack->setFlag(xAOD::TauJetParameters::classifiedCharged, false);
- xTrack->setFlag(xAOD::TauJetParameters::classifiedConversion, false);
- xTrack->setFlag(xAOD::TauJetParameters::classifiedIsolation, false);
- xTrack->setFlag(xAOD::TauJetParameters::classifiedFake, false);
- xTrack->setFlag(xAOD::TauJetParameters::unclassified, true);
+ for (xAOD::TauTrack* xTrack : vTracks) {
+ // reset all track flags and set status to unclassified
+ xTrack->setFlag(xAOD::TauJetParameters::classifiedCharged, false);
+ xTrack->setFlag(xAOD::TauJetParameters::classifiedConversion, false);
+ xTrack->setFlag(xAOD::TauJetParameters::classifiedIsolation, false);
+ xTrack->setFlag(xAOD::TauJetParameters::classifiedFake, false);
+ xTrack->setFlag(xAOD::TauJetParameters::unclassified, true);
+ }
+
+ // don't classify LRTs even if LRTs were associated with taus in TauTrackFinder
+ if(!m_classifyLRT) {
+ std::vector<xAOD::TauTrack*> vLRTs;
+ std::vector<xAOD::TauTrack*>::iterator it = vTracks.begin();
+ while(it != vTracks.end()) {
+ if((*it)->flag(xAOD::TauJetParameters::LargeRadiusTrack)) {
+ vLRTs.push_back(*it);
+ it = vTracks.erase(it);
+ }
+ else {
+ ++it;
+ }
}
-
- for (auto cClassifier : m_vClassifier) {
- ATH_CHECK(cClassifier->classifyTracks(vTracks, xTau));
+
+ // decorate LRTs with default RNN scores
+ for (auto classifier : m_vClassifier) {
+ ATH_CHECK(classifier->classifyTracks(vLRTs, xTau, true));
+ }
+ }
+
+ // classify tracks
+ for (auto classifier : m_vClassifier) {
+ ATH_CHECK(classifier->classifyTracks(vTracks, xTau));
}
- std::vector< ElementLink< xAOD::TauTrackContainer > > &tauTrackLinks(xTau.allTauTrackLinksNonConst());
+ std::vector< ElementLink< xAOD::TauTrackContainer > >& tauTrackLinks(xTau.allTauTrackLinksNonConst());
std::sort(tauTrackLinks.begin(), tauTrackLinks.end(), sortTracks);
float charge=0.0;
for( const xAOD::TauTrack* trk : xTau.tracks(xAOD::TauJetParameters::classifiedCharged) ){
@@ -82,13 +101,15 @@ StatusCode TauTrackRNNClassifier::executeTrackClassifier(xAOD::TauJet& xTau, xAO
//set modifiedIsolationTrack
for (xAOD::TauTrack* xTrack : vTracks) {
- if( not xTrack->flag(xAOD::TauJetParameters::classifiedCharged) and
- xTrack->flag(xAOD::TauJetParameters::passTrkSelector) ) xTrack->setFlag(xAOD::TauJetParameters::modifiedIsolationTrack, true);
- else xTrack->setFlag(xAOD::TauJetParameters::modifiedIsolationTrack, false);
+ if( not xTrack->flag(xAOD::TauJetParameters::classifiedCharged) and xTrack->flag(xAOD::TauJetParameters::passTrkSelector) ) {
+ xTrack->setFlag(xAOD::TauJetParameters::modifiedIsolationTrack, true);
+ }
+ else {
+ xTrack->setFlag(xAOD::TauJetParameters::modifiedIsolationTrack, false);
+ }
}
xTau.setDetail(xAOD::TauJetParameters::nModifiedIsolationTracks, (int) xTau.nTracks(xAOD::TauJetParameters::modifiedIsolationTrack));
-
return StatusCode::SUCCESS;
}
@@ -97,13 +118,13 @@ StatusCode TauTrackRNNClassifier::executeTrackClassifier(xAOD::TauJet& xTau, xAO
//==============================================================================
//______________________________________________________________________________
-TrackRNN::TrackRNN(const std::string& sName)
- : TauRecToolBase(sName)
- , m_sInputWeightsPath("")
+TrackRNN::TrackRNN(const std::string& name)
+ : TauRecToolBase(name)
+ , m_inputWeightsPath("")
{
// for conversion compatibility cast nTracks
int nMaxNtracks = 0;
- declareProperty( "InputWeightsPath", m_sInputWeightsPath );
+ declareProperty( "InputWeightsPath", m_inputWeightsPath );
declareProperty( "MaxNtracks", nMaxNtracks);
m_nMaxNtracks = (unsigned int)nMaxNtracks;
}
@@ -122,18 +143,30 @@ StatusCode TrackRNN::initialize()
}
//______________________________________________________________________________
-StatusCode TrackRNN::classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD::TauJet& xTau) const
+StatusCode TrackRNN::classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD::TauJet& xTau, bool skipTracks) const
{
- if(vTracks.size() == 0)
+ if(vTracks.size() == 0) {
return StatusCode::SUCCESS;
-
- std::sort(vTracks.begin(), vTracks.end(), [](const xAOD::TauTrack * a, const xAOD::TauTrack * b) {return a->pt() > b->pt();});
+ }
static const SG::AuxElement::Accessor<float> idScoreCharged("rnn_chargedScore");
static const SG::AuxElement::Accessor<float> idScoreIso("rnn_isolationScore");
static const SG::AuxElement::Accessor<float> idScoreConv("rnn_conversionScore");
static const SG::AuxElement::Accessor<float> idScoreFake("rnn_fakeScore");
+ // don't classify tracks, set default decorations
+ if(skipTracks) {
+ for(xAOD::TauTrack* track : vTracks) {
+ idScoreCharged(*track) = 0.;
+ idScoreConv(*track) = 0.;
+ idScoreIso(*track) = 0.;
+ idScoreFake(*track) = 0.;
+ }
+ return StatusCode::SUCCESS;
+ }
+
+ std::sort(vTracks.begin(), vTracks.end(), [](const xAOD::TauTrack * a, const xAOD::TauTrack * b) {return a->pt() > b->pt();});
+
VectorMap valueMap;
ATH_CHECK(calulateVars(vTracks, xTau, valueMap));
@@ -167,11 +200,15 @@ StatusCode TrackRNN::classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD:
idScoreIso(*vTracks[i]) = vClassProb[2];
idScoreFake(*vTracks[i]) = vClassProb[3];
- int iMaxIndex = 3; // for safty reasons set this to FT to circumvent bias
+ int iMaxIndex = 3; // for safety reasons set this to FT to circumvent bias
for (unsigned int j = 0; j < vClassProb.size(); ++j){
if(vClassProb[j] > vClassProb[iMaxIndex]) iMaxIndex = j;
}
+ if(iMaxIndex < 4) {
+ vTracks[i]->setFlag(xAOD::TauJetParameters::unclassified, false);
+ }
+
if(iMaxIndex == 3){
vTracks[i]->setFlag(xAOD::TauJetParameters::classifiedFake, true);
}else if(iMaxIndex == 0){
@@ -180,8 +217,6 @@ StatusCode TrackRNN::classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD:
vTracks[i]->setFlag(xAOD::TauJetParameters::classifiedConversion, true);
}else if(iMaxIndex == 2){
vTracks[i]->setFlag(xAOD::TauJetParameters::classifiedIsolation, true);
- }else if(iMaxIndex == 4){
- vTracks[i]->setFlag(xAOD::TauJetParameters::unclassified, true);
}
}
@@ -198,10 +233,10 @@ StatusCode TrackRNN::classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD:
//______________________________________________________________________________
StatusCode TrackRNN::addWeightsFile()
{
- std::string sInputWeightsPath = find_file(m_sInputWeightsPath);
- ATH_MSG_DEBUG("InputWeightsPath: " << sInputWeightsPath);
+ std::string inputWeightsPath = find_file(m_inputWeightsPath);
+ ATH_MSG_DEBUG("InputWeightsPath: " << inputWeightsPath);
- std::ifstream nn_config_istream(sInputWeightsPath);
+ std::ifstream nn_config_istream(inputWeightsPath);
lwtDev::GraphConfig NNconfig = lwtDev::parse_json_graph(nn_config_istream);
@@ -221,8 +256,9 @@ StatusCode TrackRNN::calulateVars(const std::vector<xAOD::TauTrack*>& vTracks, c
// initialize map with values
valueMap.clear();
unsigned int n_timeSteps = vTracks.size();
- if(m_nMaxNtracks > 0 && n_timeSteps>m_nMaxNtracks)
+ if(m_nMaxNtracks > 0 && n_timeSteps > m_nMaxNtracks) {
n_timeSteps = m_nMaxNtracks;
+ }
valueMap["log(trackPt)"] = std::vector<double>(n_timeSteps);
valueMap["log(jetSeedPt)"] = std::vector<double>(n_timeSteps);
@@ -270,9 +306,6 @@ StatusCode TrackRNN::calulateVars(const std::vector<xAOD::TauTrack*>& vTracks, c
uint8_t iTracksNSCTDeadSensors = 0; ATH_CHECK( xTrackParticle->summaryValue(iTracksNSCTDeadSensors, xAOD::numberOfSCTDeadSensors) );
uint8_t iTracksNTRTHighThresholdHits = 0; ATH_CHECK( xTrackParticle->summaryValue( iTracksNTRTHighThresholdHits, xAOD::numberOfTRTHighThresholdHits) );
uint8_t iTracksNTRTHits = 0; ATH_CHECK( xTrackParticle->summaryValue( iTracksNTRTHits, xAOD::numberOfTRTHits) );
- //uint8_t iNumberOfContribPixelLayers = 0; ATH_CHECK( xTrackParticle->summaryValue(iNumberOfContribPixelLayers, xAOD::numberOfContribPixelLayers) );
- //uint8_t iNumberOfPixelHoles = 0; ATH_CHECK( xTrackParticle->summaryValue(iNumberOfPixelHoles, xAOD::numberOfPixelHoles) );
- //uint8_t iNumberOfSCTHoles = 0; ATH_CHECK( xTrackParticle->summaryValue(iNumberOfSCTHoles, xAOD::numberOfSCTHoles) );
float fTracksEProbabilityHT; ATH_CHECK( xTrackParticle->summaryValue( fTracksEProbabilityHT, xAOD::eProbabilityHT) );
@@ -296,8 +329,9 @@ StatusCode TrackRNN::calulateVars(const std::vector<xAOD::TauTrack*>& vTracks, c
valueMap["charge"][i] = fTrackCharge;
++i;
- if(m_nMaxNtracks > 0 && i >= m_nMaxNtracks)
+ if(m_nMaxNtracks > 0 && i >= m_nMaxNtracks) {
break;
+ }
}
return StatusCode::SUCCESS;
diff --git a/Reconstruction/tauRecTools/tauRecTools/TauJetRNNEvaluator.h b/Reconstruction/tauRecTools/tauRecTools/TauJetRNNEvaluator.h
index 3275d6aa099923b718a2eb703ed8ec469327724f..a4e13523e0f65c651e9fe23d56ba566048a8f08c 100644
--- a/Reconstruction/tauRecTools/tauRecTools/TauJetRNNEvaluator.h
+++ b/Reconstruction/tauRecTools/tauRecTools/TauJetRNNEvaluator.h
@@ -57,6 +57,7 @@ private:
std::size_t m_max_clusters;
float m_max_cluster_dr;
bool m_doVertexCorrection;
+ bool m_doTrackClassification;
// Configuration of the weight file
std::string m_input_layer_scalar;
diff --git a/Reconstruction/tauRecTools/tauRecTools/TauTrackRNNClassifier.h b/Reconstruction/tauRecTools/tauRecTools/TauTrackRNNClassifier.h
index 82c8d0c7f7bf7566c0b409353ca409c32bb322a6..ea2152c22c54cd7b359bbab1a84681c5b3e8889b 100644
--- a/Reconstruction/tauRecTools/tauRecTools/TauTrackRNNClassifier.h
+++ b/Reconstruction/tauRecTools/tauRecTools/TauTrackRNNClassifier.h
@@ -49,7 +49,7 @@ public:
ASG_TOOL_CLASS2( TauTrackRNNClassifier, TauRecToolBase, ITauToolBase )
- TauTrackRNNClassifier(const std::string& sName="TauTrackRNNClassifier");
+ TauTrackRNNClassifier(const std::string& name="TauTrackRNNClassifier");
~TauTrackRNNClassifier();
// retrieve all track classifier sub tools
@@ -59,6 +59,8 @@ public:
private:
ToolHandleArray<TrackRNN> m_vClassifier {this, "Classifiers", {}};
+ bool m_classifyLRT;
+
}; // class TauTrackRNNClassifier
//______________________________________________________________________________
@@ -72,7 +74,7 @@ class TrackRNN
public:
- TrackRNN(const std::string& sName);
+ TrackRNN(const std::string& name);
~TrackRNN();
// configure the MVA object and build a general map to store variables
@@ -82,7 +84,7 @@ class TrackRNN
// executes MVA object to get the BDT score, makes the decision and resets
// classification flags
- StatusCode classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD::TauJet& xTau) const;
+ StatusCode classifyTracks(std::vector<xAOD::TauTrack*>& vTracks, xAOD::TauJet& xTau, bool skipTracks=false) const;
private:
// set BDT input variables in the corresponding map entries
@@ -99,7 +101,7 @@ private:
private:
// configurable variables
- std::string m_sInputWeightsPath;
+ std::string m_inputWeightsPath;
unsigned int m_nMaxNtracks;
private:
diff --git a/Trigger/TrigAlgorithms/TrigTauRec/python/TrigTauAlgorithmsHolder.py b/Trigger/TrigAlgorithms/TrigTauRec/python/TrigTauAlgorithmsHolder.py
index 33662b5b7ee624c81622429983d1df3285378d5b..e68a07385825bbddbbda494d2cfef5af11464051 100644
--- a/Trigger/TrigAlgorithms/TrigTauRec/python/TrigTauAlgorithmsHolder.py
+++ b/Trigger/TrigAlgorithms/TrigTauRec/python/TrigTauAlgorithmsHolder.py
@@ -720,7 +720,7 @@ def getTauJetBDTEvaluator(suffix="TauJetBDT", weightsFile="", calibFolder="", mi
########################################################################
# TauJetRNNEvaluator
def getTauJetRNNEvaluator(NetworkFile0P="", NetworkFile1P="", NetworkFile3P="", OutputVarname="RNNJetScore",
- MaxTracks=10, MaxClusters=6, MaxClusterDR=1.0,
+ MaxTracks=10, MaxClusters=6, MaxClusterDR=1.0, TrackClassification=False,
InputLayerScalar="scalar", InputLayerTracks="tracks", InputLayerClusters="clusters",
OutputLayer="rnnid_output", OutputNode="sig_prob"):
@@ -731,20 +731,21 @@ def getTauJetRNNEvaluator(NetworkFile0P="", NetworkFile1P="", NetworkFile3P="",
from AthenaCommon.AppMgr import ToolSvc
from tauRecTools.tauRecToolsConf import TauJetRNNEvaluator
- TauJetRNNEvaluator = TauJetRNNEvaluator(name=_name,
- NetworkFile0P=NetworkFile0P,
- NetworkFile1P=NetworkFile1P,
- NetworkFile3P=NetworkFile3P,
- OutputVarname=OutputVarname,
- MaxTracks=MaxTracks,
- MaxClusters=MaxClusters,
- MaxClusterDR=MaxClusterDR,
- VertexCorrection=doVertexCorrection,
- InputLayerScalar=InputLayerScalar,
- InputLayerTracks=InputLayerTracks,
- InputLayerClusters=InputLayerClusters,
- OutputLayer=OutputLayer,
- OutputNode=OutputNode)
+ TauJetRNNEvaluator = TauJetRNNEvaluator(name = _name,
+ NetworkFile0P = NetworkFile0P,
+ NetworkFile1P = NetworkFile1P,
+ NetworkFile3P = NetworkFile3P,
+ OutputVarname = OutputVarname,
+ MaxTracks = MaxTracks,
+ MaxClusters = MaxClusters,
+ MaxClusterDR = MaxClusterDR,
+ VertexCorrection = doVertexCorrection,
+ TrackClassification = TrackClassification,
+ InputLayerScalar = InputLayerScalar,
+ InputLayerTracks = InputLayerTracks,
+ InputLayerClusters = InputLayerClusters,
+ OutputLayer = OutputLayer,
+ OutputNode = OutputNode)
ToolSvc += TauJetRNNEvaluator
cached_instances[_name] = TauJetRNNEvaluator