MuonAnalysisConfig.py

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# Copyright (C) 2002-2025 CERN for the benefit of the ATLAS collaboration
 
# AnaAlgorithm import(s):
from AnalysisAlgorithmsConfig.ConfigBlock import ConfigBlock
from AthenaCommon.SystemOfUnits import GeV
from AnalysisAlgorithmsConfig.ConfigAccumulator import DataType
from AthenaConfiguration.Enums import LHCPeriod
from TrigGlobalEfficiencyCorrection.TriggerLeg_DictHelpers import TriggerDict
from Campaigns.Utils import Campaign
from AthenaCommon.Logging import logging
 
 
class MuonCalibrationConfig (ConfigBlock):
    """the ConfigBlock for the muon four-momentum correction"""
 
    def __init__ (self, containerName='') :
        super (MuonCalibrationConfig, self).__init__ ()
        self.setBlockName('Muons')
        self.addOption ('containerName', containerName, type=str,
            noneAction='error',
            info="the name of the output container after calibration.")
        self.addOption ('postfix', "", type=str,
            info="a postfix to apply to decorations and algorithm names. "
            "Typically not needed here since the calibration is common to "
            "all muons.")
        self.addOption ('minPt', 3.0*GeV, type=float,
            info="pT cut to apply to calibrated muons, in MeV. "
            "The default is 3.0 GeV.")
        self.addOption ('recalibratePhyslite', True, type=bool,
            info="whether to run the CP::EgammaCalibrationAndSmearingAlg on "
            "PHYSLITE derivations. The default is True.")
        self.addOption ('maxEta', 2.7, type=float,
            info="maximum muon |eta| (float). The default is 2.7.")
        self.addOption ('excludeNSWFromPrecisionLayers', False, type=bool,
            info="only for testing purposes, turn on to ignore NSW hits and "
            "fix a crash with older derivations (p-tag <p5834)")
        self.addOption ('calibMode', 'correctData_CB', type=str, info='calibration mode of the MuonCalibTool needed to turn on the sagitta bias corrections and to select the muon track calibration type (CB or ID+MS)')
        self.addOption ('decorateTruth', False, type=bool,
            info="decorate truth particle information on the reconstructed one")
 
    def makeAlgs (self, config) :
 
        #make sure that this is sync with
        #PhysicsAnalysis/MuonID/MuonIDAnalysis/MuonMomentumCorrections/MuonMomentumCorrections/MuonCalibTool.h#L31-37
        if self.calibMode == 'correctData_CB':
            calibMode = 0
        elif self.calibMode == 'correctData_IDMS':
            calibMode = 1
        elif self.calibMode == 'notCorrectData_IDMS':
            calibMode = 2
        elif self.calibMode == 'notCorrectData_CB':
            calibMode = 3
        else :
            raise ValueError ("invalid calibMode: \"" + self.calibMode + "\". Allowed values are correctData_CB, correctData_IDMS, notCorrectData_IDMS, notCorrectData_CB")
 
        config.setSourceName (self.containerName,
                              "AnalysisMuons" if config.isPhyslite() else "Muons",
                              calibMode=calibMode)
 
        # Set up a shallow copy to decorate
        if config.wantCopy (self.containerName) :
            alg = config.createAlgorithm( 'CP::AsgShallowCopyAlg', 'MuonShallowCopyAlg' + self.postfix )
            alg.input = config.readName (self.containerName)
            alg.output = config.copyName (self.containerName)
 
        # Set up the eta-cut on all muons prior to everything else
        alg = config.createAlgorithm( 'CP::AsgSelectionAlg',
                               'MuonEtaCutAlg' + self.postfix )
        config.addPrivateTool( 'selectionTool', 'CP::AsgPtEtaSelectionTool' )
        alg.selectionTool.maxEta = self.maxEta
        alg.selectionDecoration = 'selectEta' + self.postfix + ',as_bits'
        alg.particles = config.readName (self.containerName)
        alg.preselection = config.getPreselection (self.containerName, '')
        config.addSelection (self.containerName, '', alg.selectionDecoration)
 
        # Set up the muon calibration and smearing algorithm:
        alg = config.createAlgorithm( 'CP::MuonCalibrationAndSmearingAlg',
                               'MuonCalibrationAndSmearingAlg' + self.postfix )
        config.addPrivateTool( 'calibrationAndSmearingTool',
                        'CP::MuonCalibTool' )
 
        alg.calibrationAndSmearingTool.IsRun3Geo = config.geometry() >= LHCPeriod.Run3
        alg.calibrationAndSmearingTool.calibMode = calibMode
        if config.geometry() is LHCPeriod.Run4:
            logging.warning("MuonCalibrationConfig: disabling NSW hits for Run4 geometry")
            alg.calibrationAndSmearingTool.ExcludeNSWFromPrecisionLayers = True
        else:
            alg.calibrationAndSmearingTool.ExcludeNSWFromPrecisionLayers = self.excludeNSWFromPrecisionLayers and (config.geometry() >= LHCPeriod.Run3)
        alg.muons = config.readName (self.containerName)
        alg.muonsOut = config.copyName (self.containerName)
        alg.preselection = config.getPreselection (self.containerName, '')
        if config.isPhyslite() and not self.recalibratePhyslite :
            alg.skipNominal = True
 
        # Set up the the pt selection
        if self.minPt > 0:
            alg = config.createAlgorithm( 'CP::AsgSelectionAlg', 'MuonPtCutAlg' + self.postfix )
            alg.selectionDecoration = 'selectPt' + self.postfix + ',as_bits'
            config.addPrivateTool( 'selectionTool', 'CP::AsgPtEtaSelectionTool' )
            alg.particles = config.readName (self.containerName)
            alg.selectionTool.minPt = self.minPt
            alg.preselection = config.getPreselection (self.containerName, '')
            config.addSelection (self.containerName, '', alg.selectionDecoration,
                                preselection = True)
 
        # Additional decorations
        alg = config.createAlgorithm( 'CP::AsgEnergyDecoratorAlg', 'EnergyDecorator' + self.containerName + self.postfix )
        alg.particles = config.readName (self.containerName)
 
        config.addOutputVar (self.containerName, 'pt', 'pt')
        config.addOutputVar (self.containerName, 'eta', 'eta', noSys=True)
        config.addOutputVar (self.containerName, 'phi', 'phi', noSys=True)
        config.addOutputVar (self.containerName, 'e_%SYS%', 'e')
        config.addOutputVar (self.containerName, 'charge', 'charge', noSys=True)
 
        # decorate truth information on the reconstructed object:
        if self.decorateTruth and config.dataType() is not DataType.Data:
            config.addOutputVar (self.containerName, "truthType", "truth_type", noSys=True)
            config.addOutputVar (self.containerName, "truthOrigin", "truth_origin", noSys=True)
 
class MuonWorkingPointConfig (ConfigBlock) :
    """the ConfigBlock for the muon working point
 
    This may at some point be split into multiple blocks (10 Mar 22)."""
 
    def __init__ (self, containerName='', selectionName='') :
        super (MuonWorkingPointConfig, self).__init__ ()
        self.setBlockName('MuonsWorkingPoint')
        self.addOption ('containerName', containerName, type=str,
            noneAction='error',
            info="the name of the input container.")
        self.addOption ('selectionName', selectionName, type=str,
            noneAction='error',
            info="the name of the muon selection to define (e.g. tight or loose).")
        self.addOption ('postfix', selectionName, type=str,
            info="a postfix to apply to decorations and algorithm names. "
            "Typically not needed here as selectionName is used internally.")
        self.addOption ('trackSelection', True, type=bool,
            info="whether or not to set up an instance of "
            "CP::AsgLeptonTrackSelectionAlg, with the recommended d_0 and "
            "z_0 sin(theta) cuts. The default is True.")
        self.addOption ('maxD0Significance', 3, type=float,
            info="maximum d0 significance used for the trackSelection"
            "The default is 3")
        self.addOption ('maxDeltaZ0SinTheta', 0.5, type=float,
            info="maximum Delta z0sinTheta in mm used for the trackSelection"
            "The default is 0.5 mm")
        self.addOption ('writeTrackD0Z0', False, type = bool,
            info="save the d0 significance and z0sinTheta variables so they can be written out")
        self.addOption ('quality', None, type=str,
            info="the ID WP (string) to use. Supported ID WPs: Tight, Medium, "
            "Loose, LowPt, HighPt.")
        self.addOption ('isolation', None, type=str,
            info="the isolation WP (string) to use. Supported isolation WPs: "
            "PflowLoose_VarRad, PflowTight_VarRad, Loose_VarRad, "
            "Tight_VarRad, NonIso.")
        self.addOption ('addSelectionToPreselection', True, type=bool,
            info="whether to retain only muons satisfying the working point "
            "requirements. The default is True.")
        self.addOption ('closeByCorrection', False, type=bool,
            info="whether to use close-by-corrected isolation working points.")
        self.addOption ('systematicBreakdown', False, type=bool,
            info="enables the full breakdown of efficiency SF systematics "
            "(1 NP per uncertainty source, instead of 1 NP in total). "
            "The default is False.")
        self.addOption ('onlyRecoEffSF', False, type=bool,
            info="same as noEffSF, but retains the ID scale factor. "
            "Experimental! only useful for CI tests. The default is False.")
        self.addOption ('noEffSF', False, type=bool,
            info="disables the calculation of efficiencies and scale factors. "
            "Experimental! only useful to test a new WP for which scale "
            "factors are not available. The default is False.")
        self.addOption ('excludeNSWFromPrecisionLayers', False, type=bool,
            info="only for testing purposes, turn on to ignore NSW hits and "
            "fix a crash with older derivations (p-tag <p5834)")
 
    def makeAlgs (self, config) :
        from xAODMuon.xAODMuonEnums import xAODMuonEnums
        if self.quality == 'Tight' :
            quality = xAODMuonEnums.Quality.Tight
        elif self.quality == 'Medium' :
            quality = xAODMuonEnums.Quality.Medium
        elif self.quality == 'Loose' :
            quality = xAODMuonEnums.Quality.Loose
        elif self.quality == 'VeryLoose' :
            quality = xAODMuonEnums.Quality.VeryLoose
        elif self.quality == 'HighPt' :
            quality = 4
        elif self.quality == 'LowPtEfficiency' :
            quality = 5
        else :
            raise ValueError ("invalid muon quality: \"" + self.quality +
                              "\", allowed values are Tight, Medium, Loose, " +
                              "VeryLoose, HighPt, LowPtEfficiency")
 
        # The setup below is inappropriate for Run 1
        if config.geometry() is LHCPeriod.Run1:
            raise ValueError ("Can't set up the MuonWorkingPointConfig with %s, there must be something wrong!" % config.geometry().value)
 
        postfix = self.postfix
        if postfix != '' and postfix[0] != '_' :
            postfix = '_' + postfix
 
        # Set up the track selection algorithm:
        if self.writeTrackD0Z0 or self.trackSelection:
            alg = config.createAlgorithm( 'CP::AsgLeptonTrackSelectionAlg',
                                'MuonTrackSelectionAlg' + postfix )
            alg.selectionDecoration = 'trackSelection' + postfix + ',as_bits'
            alg.decorateTTVAVars = self.writeTrackD0Z0
            alg.maxD0Significance = self.maxD0Significance
            alg.maxDeltaZ0SinTheta = self.maxDeltaZ0SinTheta
            alg.particles = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, '')
            if self.trackSelection :
                config.addSelection (self.containerName, self.selectionName, alg.selectionDecoration, preselection=self.addSelectionToPreselection)
            if self.writeTrackD0Z0 :
                alg.d0sigDecoration = 'd0sig' + postfix
                alg.z0sinthetaDecoration = 'z0sintheta' + postfix
                config.addOutputVar (self.containerName, alg.d0sigDecoration, alg.d0sigDecoration,noSys=True)
                config.addOutputVar (self.containerName, alg.z0sinthetaDecoration, alg.z0sinthetaDecoration,noSys=True)
 
        # Setup the muon quality selection
        alg = config.createAlgorithm( 'CP::MuonSelectionAlgV2',
                               'MuonSelectionAlg' + postfix )
        config.addPrivateTool( 'selectionTool', 'CP::MuonSelectionTool' )
        alg.selectionTool.MuQuality = quality
        alg.selectionTool.IsRun3Geo = config.geometry() >= LHCPeriod.Run3
        if config.geometry() is LHCPeriod.Run4:
            logging.warning("MuonCalibrationConfig: disabling NSW hits for Run4 geometry")
            alg.selectionTool.ExcludeNSWFromPrecisionLayers = True
        else:
            alg.selectionTool.ExcludeNSWFromPrecisionLayers = self.excludeNSWFromPrecisionLayers and (config.geometry() >= LHCPeriod.Run3)
        alg.selectionDecoration = 'good_muon' + postfix + ',as_char'
        alg.badMuonVetoDecoration = 'is_bad' + postfix + ',as_char'
        alg.muons = config.readName (self.containerName)
        alg.preselection = config.getPreselection (self.containerName, self.selectionName)
        config.addSelection (self.containerName, self.selectionName,
                             alg.selectionDecoration,
                             preselection=self.addSelectionToPreselection)
 
        # Set up the isolation calculation algorithm:
        if self.isolation != 'NonIso' :
            alg = config.createAlgorithm( 'CP::MuonIsolationAlg',
                                   'MuonIsolationAlg' + postfix )
            config.addPrivateTool( 'isolationTool', 'CP::IsolationSelectionTool' )
            alg.isolationTool.MuonWP = self.isolation
            if self.closeByCorrection:
              alg.isolationTool.IsoDecSuffix = "CloseByCorr"
            alg.isolationDecoration = 'isolated_muon' + postfix + ',as_char'
            alg.muons = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, self.selectionName)
            config.addSelection (self.containerName, self.selectionName,
                                 alg.isolationDecoration,
                                 preselection=self.addSelectionToPreselection)
 
        # Set up the reco/ID efficiency scale factor calculation algorithm:
        if config.dataType() is not DataType.Data and (not self.noEffSF or self.onlyRecoEffSF):
            alg = config.createAlgorithm( 'CP::MuonEfficiencyScaleFactorAlg',
                                   'MuonEfficiencyScaleFactorAlgReco' + postfix )
            config.addPrivateTool( 'efficiencyScaleFactorTool',
                            'CP::MuonEfficiencyScaleFactors' )
            alg.scaleFactorDecoration = 'muon_reco_effSF' + postfix + "_%SYS%"
            alg.outOfValidity = 2 #silent
            alg.outOfValidityDeco = 'muon_reco_bad_eff' + postfix
            alg.efficiencyScaleFactorTool.WorkingPoint = self.quality
            if config.geometry() >= LHCPeriod.Run3:
                alg.efficiencyScaleFactorTool.CalibrationRelease = '240711_Preliminary_r24run3'
            alg.efficiencyScaleFactorTool.BreakDownSystematics = self.systematicBreakdown
            alg.muons = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, self.selectionName)
            config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'reco_effSF' + postfix)
 
        # Set up the HighPt-specific BadMuonVeto efficiency scale factor calculation algorithm:
        if config.dataType() is not DataType.Data and self.quality == 'HighPt' and not self.onlyRecoEffSF and not self.noEffSF:
            alg = config.createAlgorithm( 'CP::MuonEfficiencyScaleFactorAlg',
                                   'MuonEfficiencyScaleFactorAlgBMVHighPt' + postfix )
            config.addPrivateTool( 'efficiencyScaleFactorTool',
                            'CP::MuonEfficiencyScaleFactors' )
            alg.scaleFactorDecoration = 'muon_BadMuonVeto_effSF' + postfix + "_%SYS%"
            alg.outOfValidity = 2 #silent
            alg.outOfValidityDeco = 'muon_BadMuonVeto_bad_eff' + postfix
            alg.efficiencyScaleFactorTool.WorkingPoint = 'BadMuonVeto_HighPt'
            if config.geometry() >= LHCPeriod.Run3:
                alg.efficiencyScaleFactorTool.CalibrationRelease = '220817_Preliminary_r22run3' # not available as part of '230123_Preliminary_r22run3'!
            alg.efficiencyScaleFactorTool.BreakDownSystematics = self.systematicBreakdown
            alg.muons = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, self.selectionName)
            config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'BadMuonVeto_effSF' + postfix)
 
        # Set up the isolation efficiency scale factor calculation algorithm:
        if config.dataType() is not DataType.Data and self.isolation != 'NonIso' and not self.onlyRecoEffSF and not self.noEffSF:
            alg = config.createAlgorithm( 'CP::MuonEfficiencyScaleFactorAlg',
                                   'MuonEfficiencyScaleFactorAlgIsol' + postfix )
            config.addPrivateTool( 'efficiencyScaleFactorTool',
                            'CP::MuonEfficiencyScaleFactors' )
            alg.scaleFactorDecoration = 'muon_isol_effSF' + postfix + "_%SYS%"
            alg.outOfValidity = 2 #silent
            alg.outOfValidityDeco = 'muon_isol_bad_eff' + postfix
            alg.efficiencyScaleFactorTool.WorkingPoint = self.isolation + 'Iso'
            if config.geometry() >= LHCPeriod.Run3:
                alg.efficiencyScaleFactorTool.CalibrationRelease = '240711_Preliminary_r24run3'
            alg.efficiencyScaleFactorTool.BreakDownSystematics = self.systematicBreakdown
            alg.muons = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, self.selectionName)
            config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'isol_effSF' + postfix)
 
        # Set up the TTVA scale factor calculation algorithm:
        if config.dataType() is not DataType.Data and not self.onlyRecoEffSF and not self.noEffSF:
            alg = config.createAlgorithm( 'CP::MuonEfficiencyScaleFactorAlg',
                                   'MuonEfficiencyScaleFactorAlgTTVA' + postfix )
            config.addPrivateTool( 'efficiencyScaleFactorTool',
                            'CP::MuonEfficiencyScaleFactors' )
            alg.scaleFactorDecoration = 'muon_TTVA_effSF' + postfix + "_%SYS%"
            alg.outOfValidity = 2 #silent
            alg.outOfValidityDeco = 'muon_TTVA_bad_eff' + postfix
            alg.efficiencyScaleFactorTool.WorkingPoint = 'TTVA'
            if config.geometry() >= LHCPeriod.Run3:
                alg.efficiencyScaleFactorTool.CalibrationRelease = '240711_Preliminary_r24run3'
            alg.efficiencyScaleFactorTool.BreakDownSystematics = self.systematicBreakdown
            alg.muons = config.readName (self.containerName)
            alg.preselection = config.getPreselection (self.containerName, self.selectionName)
            config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'TTVA_effSF' + postfix)
 
 
def makeMuonCalibrationConfig( seq, containerName,
                               postfix = None):
    """Create muon calibration analysis algorithms
 
    This makes all the algorithms that need to be run first befor
    all working point specific algorithms and that can be shared
    between the working points.
 
    Keyword arguments:
      containerName -- name of the output container
      postfix -- a postfix to apply to decorations and algorithm
                 names.  this is mostly used/needed when using this
                 sequence with multiple working points to ensure all
                 names are unique.
    """
 
    config = MuonCalibrationConfig (containerName)
    config.setOptionValue ('postfix', postfix)
    seq.append (config)
 
 
 
 
 
def makeMuonWorkingPointConfig( seq, containerName, workingPoint, selectionName,
                                addSelectionToPreselection = None,
                                systematicBreakdown = None,
                                noEffSF = None,
                                onlyRecoEffSF = None ):
    """Create muon analysis algorithms for a single working point
 
    Keyword arguments:
      workingPoint -- The working point to use
      selectionName -- a postfix to apply to decorations and algorithm
                 names.  this is mostly used/needed when using this
                 sequence with multiple working points to ensure all
                 names are unique.
      addSelectionToPreselection -- Whether or not to apply muon quality selection
                                when creating output containers.
      systematicBreakdown -- enables the full breakdown of eff SF systematics
      noEffSF -- Disables the calculation of efficiencies and scale factors
      onlyRecoEffSF -- Only enables the reconstruction scale factor
    """
 
 
    config = MuonWorkingPointConfig (containerName, selectionName)
    if workingPoint is not None :
        splitWP = workingPoint.split ('.')
        if len (splitWP) != 2 :
            raise ValueError ('working point should be of format "quality.isolation", not ' + workingPoint)
        config.setOptionValue ('quality', splitWP[0])
        config.setOptionValue ('isolation', splitWP[1])
    config.setOptionValue ('addSelectionToPreselection', addSelectionToPreselection)
    config.setOptionValue ('systematicBreakdown', systematicBreakdown)
    config.setOptionValue ('noEffSF', noEffSF)
    config.setOptionValue ('onlyRecoEffSF', onlyRecoEffSF)
    seq.append (config)
 
 
class MuonTriggerAnalysisSFBlock (ConfigBlock):
 
    def __init__ (self, configName='') :
        super (MuonTriggerAnalysisSFBlock, self).__init__ ()
 
        self.addOption ('triggerChainsPerYear', {}, type=None,
                        info="a dictionary with key (string) the year and value (list of "
                        "strings) the trigger chains. The default is {} (empty dictionary).")
        self.addOption ('muonID', '', type=str,
                        info="the muon quality WP (string) to use.")
        self.addOption ('saveEff', False, type=bool,
                        info="define whether we decorate also the trigger scale efficiency "
                        "The default is false.")
        self.addOption ('containerName', '', type=str,
                        info="the input muon container, with a possible selection, in "
                        "the format container or container.selection.")
 
    def makeAlgs (self, config) :
 
        if config.dataType() is not DataType.Data:
 
            # Dictionary from TrigGlobalEfficiencyCorrection/Triggers.cfg
            # Key is trigger chain (w/o HLT prefix)
            # Value is empty for single leg trigger or list of legs
            triggerDict = TriggerDict()
 
            if config.campaign() is Campaign.MC20a:
                years = [2015, 2016]
            elif config.campaign() is Campaign.MC20d:
                years = [2017]
            elif config.campaign() is Campaign.MC20e:
                years = [2018]
            elif config.campaign() in [Campaign.MC21a, Campaign.MC23a]:
                years = [2022]
            elif config.campaign() in [Campaign.MC23c, Campaign.MC23d]:
                years = [2023]
 
            triggerConfigs = {}
            triggerConfigYears = {}
            for year in years:
                triggerChains = self.triggerChainsPerYear.get(int(year), self.triggerChainsPerYear.get(str(year), []))
                for chain in triggerChains:
                    chain = chain.replace(" || ", "_OR_")
                    chain_noHLT = chain.replace("HLT_","")
                    legs = triggerDict[chain_noHLT]
                    if len(legs)==0:
                        if chain_noHLT.startswith('mu') and chain_noHLT[2].isdigit:
                            # Need to support HLT_mu26_ivarmedium_OR_HLT_mu50
                            triggerConfigs[chain_noHLT] = chain
                            if chain_noHLT in triggerConfigYears.keys():
                                triggerConfigYears[chain_noHLT].append(year)
                            else:
                                triggerConfigYears[chain_noHLT] = [year]
                    else:
                        for leg in legs:
                            if leg.startswith('mu') and leg[2].isdigit:
                                # Need to support HLT_mu14_ivarloose
                                triggerConfigs[leg] = 'HLT_' + leg
                                if chain_noHLT in triggerConfigYears.keys():
                                    triggerConfigYears[leg].append(year)
                                else:
                                    triggerConfigYears[leg] = [year]
 
            for trig_short, trig in triggerConfigs.items():
                alg = config.createAlgorithm('CP::MuonTriggerEfficiencyScaleFactorAlg',
                                             'MuonTrigEfficiencyCorrectionsAlg_' + trig_short)
                config.addPrivateTool( 'efficiencyScaleFactorTool',
                                       'CP::MuonTriggerScaleFactors' )
 
                # Reproduce config from TrigGlobalEfficiencyAlg
                alg.efficiencyScaleFactorTool.MuonQuality = self.muonID
                alg.efficiencyScaleFactorTool.AllowZeroSF = True
 
                # Avoid warnings for MC20a 2015-2016 triggers covering a single year
                if config.campaign() is Campaign.MC20a:
                    if triggerConfigYears[trig_short] == [2015]:
                        alg.maxRunNumber = 290000
                    elif triggerConfigYears[trig_short] == [2016]:
                        alg.minRunNumber = 290000
 
                alg.trigger = trig
                alg.scaleFactorDecoration = 'muon_trigEffSF_' + trig_short + '_%SYS%'
                if(self.saveEff):
                    alg.mcEfficiencyDecoration = 'muon_trigEff_' + trig_short + '_%SYS%'
                alg.outOfValidity = 2 #silent
                alg.outOfValidityDeco = 'bad_eff_muontrig_' + trig_short
                alg.muons = config.readName (self.containerName)
                alg.preselection = config.getPreselection (self.containerName, '')
                config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'trigEffSF_' + trig_short)
                if(self.saveEff):
                    config.addOutputVar (self.containerName, alg.scaleFactorDecoration, 'trigEff_' + trig_short)