diff --git a/Reconstruction/tauRec/python/TauAlgorithmsHolder.py b/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
index 53b70a48cd3aac514f9c0281630a6344ce4f7c14..e6b2aa6ff55693f4ad54138ae6a7cb47a22e47b5 100644
--- a/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
+++ b/Reconstruction/tauRec/python/TauAlgorithmsHolder.py
@@ -93,10 +93,9 @@ def getEnergyCalibrationLC(correctEnergy=True, correctAxis=False, postfix=''):
from tauRecTools.tauRecToolsConf import TauCalibrateLC
TauCalibrateLC = TauCalibrateLC(name = _name,
- calibrationFile = "TES_MC16a_prelim.root",
+ calibrationFile = tauFlags.tauRecCalibrateLCConfig(),
doPtResponse = True,
- Key_vertexInputContainer = _DefaultVertexContainer
- )
+ Key_vertexInputContainer = _DefaultVertexContainer)
cached_instances[_name] = TauCalibrateLC
return TauCalibrateLC
@@ -697,7 +696,7 @@ def getMvaTESEvaluator():
_name = sPrefix + 'MvaTESEvaluator'
from tauRecTools.tauRecToolsConf import MvaTESEvaluator
MvaTESEvaluator = MvaTESEvaluator(name = _name,
- WeightFileName = 'MvaTES_20170207_v2_BDTG.weights.root') #update config?
+ WeightFileName = tauFlags.tauRecMvaTESConfig())
cached_instances[_name] = MvaTESEvaluator
return MvaTESEvaluator
@@ -707,7 +706,7 @@ def getCombinedP4FromRecoTaus():
_name = sPrefix + 'CombinedP4FromRecoTaus'
from tauRecTools.tauRecToolsConf import CombinedP4FromRecoTaus
CombinedP4FromRecoTaus = CombinedP4FromRecoTaus(name = _name,
- WeightFileName = 'CalibLoopResult_v04-04.root') #update config?
+ WeightFileName = tauFlags.tauRecCombinedP4Config())
cached_instances[_name] = CombinedP4FromRecoTaus
return CombinedP4FromRecoTaus
@@ -884,23 +883,23 @@ def getTauWPDecoratorEleBDT():
#
-def getTauJetRNNEvaluator(_n, NetworkFile0P="", NetworkFile1P="", NetworkFile3P="", OutputVarname="RNNJetScore", MaxTracks=10, MaxClusters=6, MaxClusterDR=1.0, InputLayerScalar="scalar", InputLayerTracks="tracks", InputLayerClusters="clusters", OutputLayer="rnnid_output", OutputNode="sig_prob"):
- _name = sPrefix + _n
+def getTauJetRNNEvaluator():
+ _name = sPrefix + 'TauJetRNN'
from tauRecTools.tauRecToolsConf import TauJetRNNEvaluator
- myTauJetRNNEvaluator = TauJetRNNEvaluator(name=_name,
- NetworkFile0P=NetworkFile0P,
- NetworkFile1P=NetworkFile1P,
- NetworkFile3P=NetworkFile3P,
- OutputVarname=OutputVarname,
- MaxTracks=MaxTracks,
- MaxClusters=MaxClusters,
- MaxClusterDR=MaxClusterDR,
- VertexCorrection=True,
- InputLayerScalar=InputLayerScalar,
- InputLayerTracks=InputLayerTracks,
- InputLayerClusters=InputLayerClusters,
- OutputLayer=OutputLayer,
- OutputNode=OutputNode)
+ myTauJetRNNEvaluator = TauJetRNNEvaluator(name = _name,
+ NetworkFile0P = "",
+ NetworkFile1P = tauFlags.tauRecTauJetRNNConfig()[0],
+ NetworkFile3P = tauFlags.tauRecTauJetRNNConfig()[1],
+ OutputVarname = "RNNJetScore",
+ MaxTracks = 10,
+ MaxClusters = 6,
+ MaxClusterDR = 1.0,
+ VertexCorrection = True,
+ InputLayerScalar = "scalar",
+ InputLayerTracks = "tracks",
+ InputLayerClusters = "clusters",
+ OutputLayer = "rnnid_output",
+ OutputNode = "sig_prob")
cached_instances[_name] = myTauJetRNNEvaluator
return myTauJetRNNEvaluator
@@ -928,28 +927,22 @@ def getTauIDVarCalculator():
cached_instances[_name] = myTauIDVarCalculator
return myTauIDVarCalculator
-def getTauEleRNNEvaluator(_n,
- NetworkFile1P="", NetworkFile3P="",
- OutputVarname="RNNEleScore", MaxTracks=10,
- MaxClusters=6, MaxClusterDR=1.0, InputLayerScalar="scalar",
- InputLayerTracks="tracks", InputLayerClusters="clusters",
- OutputLayer="rnneveto_output", OutputNode="sig_prob"):
-
- _name = sPrefix + _n
+def getTauEleRNNEvaluator():
+ _name = sPrefix + 'TauEleRNN'
from tauRecTools.tauRecToolsConf import TauJetRNNEvaluator
- tool = TauJetRNNEvaluator(name=_name,
- NetworkFile1P=NetworkFile1P,
- NetworkFile3P=NetworkFile3P,
- OutputVarname=OutputVarname,
- MaxTracks=MaxTracks,
- MaxClusters=MaxClusters,
- MaxClusterDR=MaxClusterDR,
- VertexCorrection=True,
- InputLayerScalar=InputLayerScalar,
- InputLayerTracks=InputLayerTracks,
- InputLayerClusters=InputLayerClusters,
- OutputLayer=OutputLayer,
- OutputNode=OutputNode)
+ tool = TauJetRNNEvaluator(name = _name,
+ NetworkFile1P = tauFlags.tauRecTauEleRNNConfig()[0],
+ NetworkFile3P = tauFlags.tauRecTauEleRNNConfig()[1],
+ OutputVarname = "RNNEleScore",
+ MaxTracks = 10,
+ MaxClusters = 6,
+ MaxClusterDR = 1.0,
+ VertexCorrection = True,
+ InputLayerScalar = "scalar",
+ InputLayerTracks = "tracks",
+ InputLayerClusters = "clusters",
+ OutputLayer = "rnneveto_output",
+ OutputNode = "sig_prob")
cached_instances[_name] = tool
return tool
diff --git a/Reconstruction/tauRec/python/TauRecRunner.py b/Reconstruction/tauRec/python/TauRecRunner.py
index 8af178600538c49e3c8a40051f30ced3bbdc64be..3bdf712bfb02afd2e0ed6acd4036930a6b74493c 100644
--- a/Reconstruction/tauRec/python/TauRecRunner.py
+++ b/Reconstruction/tauRec/python/TauRecRunner.py
@@ -63,15 +63,9 @@ class TauRecRunner ( TauRecRunConfigured ) :
if tauFlags.doRunTauDiscriminant():
tools.append(taualgs.getTauIDVarCalculator())
- tools.append(taualgs.getTauJetRNNEvaluator("TauJetRNN",
- NetworkFile1P="rnnid_mc16d_config_1p.json",
- NetworkFile3P="rnnid_mc16d_config_3p.json",
- OutputVarname="RNNJetScore", MaxTracks=10, MaxClusters=6))
+ tools.append(taualgs.getTauJetRNNEvaluator())
tools.append(taualgs.getTauWPDecoratorJetRNN())
- tools.append(taualgs.getTauEleRNNEvaluator("TauEleRNN",
- NetworkFile1P="rnneveto_mc16d_config_1p.json",
- NetworkFile3P="rnneveto_mc16d_config_3p.json",
- OutputVarname="RNNEleScore", MaxTracks=10, MaxClusters=6))
+ tools.append(taualgs.getTauEleRNNEvaluator())
tools.append(taualgs.getTauWPDecoratorEleRNN())
tools.append(taualgs.getTauDecayModeNNClassifier())
diff --git a/Reconstruction/tauRec/python/tauRecFlags.py b/Reconstruction/tauRec/python/tauRecFlags.py
index 72490b28b994d73115b487d48c9a180be97c6d08..877dcbbd8857619e13057a9b60bd25209b522006 100644
--- a/Reconstruction/tauRec/python/tauRecFlags.py
+++ b/Reconstruction/tauRec/python/tauRecFlags.py
@@ -108,6 +108,41 @@ class tauRecDecayModeNNClassifierConfig(JobProperty):
allowedTypes=['string']
StoredValue='NNDecayModeWeights-20200625.json'
+class tauRecCalibrateLCConfig(JobProperty):
+ """Config file for TauCalibrateLC
+ """
+ statusOn=True
+ allowedTypes=['string']
+ StoredValue='TES_MC16a_prelim.root'
+
+class tauRecMvaTESConfig(JobProperty):
+ """Config file for MvaTESEvaluator
+ """
+ statusOn=True
+ allowedTypes=['string']
+ StoredValue='MvaTES_20170207_v2_BDTG.weights.root'
+
+class tauRecCombinedP4Config(JobProperty):
+ """Config file for CombinedP4FromRecoTaus
+ """
+ statusOn=True
+ allowedTypes=['string']
+ StoredValue='CalibLoopResult_v04-04.root'
+
+class tauRecTauJetRNNConfig(JobProperty):
+ """Config files for TauJetRNNEvaluator jet ID
+ """
+ statusOn=True
+ allowedTypes=[['string']]
+ StoredValue=[ 'rnnid_mc16d_config_1p.json', 'rnnid_mc16d_config_3p.json' ]
+
+class tauRecTauEleRNNConfig(JobProperty):
+ """Config files for TauJetRNNEvaluator eVeto
+ """
+ statusOn=True
+ allowedTypes=[['string']]
+ StoredValue=[ 'rnneveto_mc16d_config_1p.json', 'rnneveto_mc16d_config_3p.json' ]
+
class tauRecSeedMinPt(JobProperty):
""" minimum jet seed pt
"""
@@ -150,21 +185,6 @@ class doRunTauDiscriminant(JobProperty):
allowedTypes=['bool']
StoredValue=True
-
-class useVertexBasedConvFinder(JobProperty):
- """ switch for PhotonConversionVertex.cxx/h conversion veto
- """
- statusOn=True
- allowedTypes=['bool']
- StoredValue=False
-
-class useNewPIDBasedConvFinder(JobProperty):
- """ switch for TauConversionTagger.cxx/h conversion veto
- """
- statusOn=True
- allowedTypes=['bool']
- StoredValue=True
-
class doPanTau(JobProperty):
""" if pantau should run after tauRec
"""
@@ -229,7 +249,7 @@ 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,tauRecSeedMinPt,tauRecSeedMaxEta,tauRecMaxNTracks,tauRecToolsDevToolList,tauRecToolsDevToolListProcessor,doRunTauDiscriminant,useVertexBasedConvFinder,useNewPIDBasedConvFinder,doPanTau,doPi0,pi0EtCuts,pi0MVACuts_1prong,pi0MVACuts_mprong,shotPtCut_1Photon,shotPtCut_2Photons,useOldVertexFitterAPI]
+_list_tau=[Enabled,doTauRec,isStandalone,tauRecSeedJetCollection,tauRecToolsCVMFSPath,doTJVA,useLargeD0Tracks,removeDuplicateCoreTracks,tauRecMVATrackClassification,tauRecRNNTrackClassification,tauRecMVATrackClassificationConfig,tauRecRNNTrackClassificationConfig,tauRecDecayModeNNClassifierConfig,tauRecCalibrateLCConfig,tauRecMvaTESConfig,tauRecCombinedP4Config,tauRecTauJetRNNConfig,tauRecTauEleRNNConfig,tauRecSeedMinPt,tauRecSeedMaxEta,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