def __init__(self,
globalTag,
jesUncertainties=["Total"],
jetType="AK4PFchs"):
#--------------------------------------------------------------------------------------------
# CV: globalTag and jetType not yet used, as there is no consistent set of txt files for
# JES uncertainties and JER scale factors and uncertainties yet
#--------------------------------------------------------------------------------------------
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data and simulation.
self.applyJERCorr = True
self.jerInputFileName = "Spring16_25nsV10_MC_PtResolution_AK4PFchs.txt"
self.jerUncertaintyInputFileName = "Spring16_25nsV10_MC_SF_AK4PFchs.txt"
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName,
self.jerUncertaintyInputFileName)
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.metBranchName = "MET"
self.rhoBranchName = "fixedGridRhoFastjetAll"
# read jet energy scale (JES) uncertainties
self.jesInputFilePath = os.environ[
'CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/"
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
self.jesUncertaintyInputFileName = "Summer16_23Sep2016V4_MC_Uncertainty_AK4PFchs.txt"
else:
self.jesUncertaintyInputFileName = "Summer16_23Sep2016V4_MC_UncertaintySources_AK4PFchs.txt"
# define energy threshold below which jets are considered as "unclustered energy"
# (cf. JetMETCorrections/Type1MET/python/correctionTermsPfMetType1Type2_cff.py )
self.unclEnThreshold = 15.
# load libraries for accessing JES scale factors and uncertainties from txt files
for library in [
"libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools"
]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
def __init__(
self, isMC, isSig, era, muonSelectionTag, electronSelectionTag,
CorrMET
): #, HTFilter, LTFilter):#, muonSelection, electronSelection):
self.isMC = isMC
self.isSig = isSig
self.era = era
self.muonSelectionTag = muonSelectionTag
self.electronSelectionTag = electronSelectionTag
self.CorrMET = CorrMET
#self.HTFilt = HTFilter
#self.LTFilt = LTFilter
# smear jet pT to account for measured difference in JER between data and simulation.
self.jerInputFileName = "Spring16_25nsV10_MC_PtResolution_AK4PFchs.txt"
self.jerUncertaintyInputFileName = "Spring16_25nsV10_MC_SF_AK4PFchs.txt"
###################### LepSF, JECSFs and JERSF for 2017 era ###############################################################
if self.era == "2016":
self.btag_LooseWP = 0.5426
self.btag_MediumWP = 0.8484
self.btag_TightWP = 0.9535
#https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation80XReReco
self.btag_DeepLooseWP = 0.2219
self.btag_DeepMediumWP = 0.6324
self.btag_DeepTightWP = 0.8958
if self.isMC:
if self.muonSelectionTag == "LooseWP_2016":
mu_f = ["Mu_Trg.root", "Mu_ID.root", "Mu_Iso.root"]
mu_h = [
"IsoMu24_OR_IsoTkMu24_PtEtaBins/pt_abseta_ratio",
"MC_NUM_LooseID_DEN_genTracks_PAR_pt_eta/pt_abseta_ratio",
"LooseISO_LooseID_pt_eta/pt_abseta_ratio"
]
if self.electronSelectionTag == "GPMVA90_2016":
el_f = ["EGM2D_eleGSF.root", "EGM2D_eleMVA90.root"]
el_h = ["EGamma_SF2D", "EGamma_SF2D"]
if self.muonSelectionTag == "MediumWP_2016":
mu_f = ["Mu_Trg.root", "Mu_ID.root", "Mu_Iso.root"]
mu_h = [
"IsoMu24_OR_IsoTkMu24_PtEtaBins/pt_abseta_ratio",
"MC_NUM_MediumID_DEN_genTracks_PAR_pt_eta/pt_abseta_ratio",
"LooseISO_MediumID_pt_eta/pt_abseta_ratio"
]
if self.electronSelectionTag == "Tight_2016":
el_f = ["EGM2D_eleGSF.root", "EGM2D_eleMVA90.root"]
el_h = ["EGamma_SF2D", "EGamma_SF2D"]
#self.jerUncertaintyInputFileName = "Spring16_25nsV10_MC_SF_AK4PFchs.txt"
self.jetSmearer = jetSmearer("Summer16_23Sep2016V4_MC", "AK4PFchs",
self.jerInputFileName,
self.jerUncertaintyInputFileName)
###################### LepSF, JECSFs and JERSF for 2017 era ###############################################################
elif self.era == "2017":
self.btag_LooseWP = 0.5803
self.btag_MediumWP = 0.8838
self.btag_TightWP = 0.9693
# DeepCSV (new Deep Flavour tagger)
#https://twiki.cern.ch/twiki/bin/viewauth/CMS/BtagRecommendation94X
self.btag_DeepLooseWP = 0.1522
self.btag_DeepMediumWP = 0.4941
self.btag_DeepTightWP = 0.8001
if self.isMC:
if self.muonSelectionTag == "LooseWP_2017":
mu_f = ["Mu_Trg17.root", "Mu_ID17.root", "Mu_Iso17.root"]
mu_h = [
"IsoMu27_PtEtaBins/pt_abseta_ratio",
"NUM_LooseID_DEN_genTracks_pt_abseta",
"NUM_LooseRelIso_DEN_LooseID_pt_abseta"
]
if self.electronSelectionTag == "GPMVA90_2017":
el_f = ["EGM2D_eleGSF17.root", "EGM2D_eleMVA90_17.root"]
el_h = ["EGamma_SF2D", "EGamma_SF2D"]
if self.muonSelectionTag == "MediumWP_2017":
mu_f = ["Mu_Trg17.root", "Mu_ID17.root", "Mu_Iso17.root"]
mu_h = [
"IsoMu27_PtEtaBins/pt_abseta_ratio",
"NUM_MediumID_DEN_genTracks_pt_abseta",
"NUM_LooseRelIso_DEN_MediumID_pt_abseta"
]
if self.electronSelectionTag == "Tight_2017":
el_f = ["EGM2D_eleGSF17.root", "EGM2D_eleMVA90_17.root"]
el_h = ["EGamma_SF2D", "EGamma_SF2D"]
# Temporarly use the jetmet uncertainty for 2016
#self.jerUncertaintyInputFileName = "Spring16_25nsV10_MC_SF_AK4PFchs.txt"
#self.jetSmearer = jetSmearer("Summer16_23Sep2016V4_MC", "AK4PFchs", self.jerInputFileName, self.jerUncertaintyInputFileName)
#self.jerUncertaintyInputFileName = "Fall17_17Nov2017_V6_MC_Uncertainty_AK4PFchs.txt"
self.jetSmearer = jetSmearer("Fall17_17Nov2017_V6_MC", "AK4PFchs",
self.jerInputFileName,
self.jerUncertaintyInputFileName)
else:
raise ValueError("ERROR: Invalid era = '%s'!" % self.era)
if self.isMC:
mu_f = [
"%s/src/PhysicsTools/NanoAODTools/python/postprocessing/data/leptonSF/"
% os.environ['CMSSW_BASE'] + f for f in mu_f
]
el_f = [
"%s/src/PhysicsTools/NanoAODTools/python/postprocessing/data/leptonSF/"
% os.environ['CMSSW_BASE'] + f for f in el_f
]
self.mu_f = ROOT.std.vector(str)(len(mu_f))
self.mu_h = ROOT.std.vector(str)(len(mu_f))
for i in range(len(mu_f)):
self.mu_f[i] = mu_f[i]
self.mu_h[i] = mu_h[i]
self.el_f = ROOT.std.vector(str)(len(el_f))
self.el_h = ROOT.std.vector(str)(len(el_f))
for i in range(len(el_f)):
self.el_f[i] = el_f[i]
self.el_h[i] = el_h[i]
self.jetReCalibrator = JetReCalibrator(
"Fall17_17Nov2017_V6_MC",
"AK4PFchs",
True,
os.environ['CMSSW_BASE'] +
"/src/PhysicsTools/NanoAODTools/data/jme/",
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
self.unclEnThreshold = 15.
if "/LeptonEfficiencyCorrector_cc.so" not in ROOT.gSystem.GetLibraries(
):
print "Load C++ Worker"
ROOT.gROOT.ProcessLine(
".L %s/src/PhysicsTools/NanoAODTools/python/postprocessing/helpers/LeptonEfficiencyCorrector.cc+"
% os.environ['CMSSW_BASE'])
pass
def __init__(self,
era,
globalTag,
jesUncertainties=["Total"],
archive=None,
jetType="AK8PFPuppi",
noGroom=False,
jerTag="",
jmrVals=[],
jmsVals=[],
isData=False,
applySmearing=True,
applyHEMfix=False,
splitJER=False):
self.era = era
self.noGroom = noGroom
self.isData = isData
self.applySmearing = applySmearing if not isData else False # don't smear for data
# ---------------------------------------------------------------------
# CV: globalTag and jetType not yet used in the jet smearer, as there
# is no consistent set of txt files for JES uncertainties and JER scale
# factors and uncertainties yet
# ---------------------------------------------------------------------
self.splitJER = splitJER
if self.splitJER:
self.splitJERIDs = list(range(6))
else:
self.splitJERIDs = [""] # "empty" ID for the overall JER
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data
# and simulation.
if jerTag != "":
self.jerInputFileName = jerTag + "_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = jerTag + "_SF_" + jetType + ".txt"
else:
print("WARNING: jerTag is empty!!! This module will soon be "
"deprecated! Please use jetmetHelperRun2 in the future.")
if era == "2016":
self.jerInputFileName = ''.join(
["Summer16_25nsV1_MC_PtResolution_", jetType, ".txt"])
self.jerUncertaintyInputFileName = ''.join(
["Summer16_25nsV1_MC_SF_", jetType, ".txt"])
elif era == "2017" or era == "2018":
# use Fall17 as temporary placeholder until
# post-Moriond 2019 JERs are out
self.jerInputFileName = ''.join(
["Fall17_V3_MC_PtResolution_", jetType, ".txt"])
self.jerUncertaintyInputFileName = ''.join(
["Fall17_V3_MC_SF_", jetType, ".txt"])
# jet mass resolution: https://twiki.cern.ch/twiki/bin/view/CMS/JetWtagging
self.jmrVals = jmrVals
if not self.jmrVals:
print("WARNING: jmrVals is empty!!! Using default values. This "
"module will soon be deprecated! Please use "
"jetmetHelperRun2 in the future.")
self.jmrVals = [1.0, 1.2, 0.8] # nominal, up, down
# Use 2017 values for 2018 until 2018 are released
if self.era in ["2017", "2018"]:
self.jmrVals = [1.09, 1.14, 1.04]
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName,
self.jerUncertaintyInputFileName,
self.jmrVals)
if "AK4" in jetType:
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.genSubJetBranchName = None
self.doGroomed = False
elif "AK8" in jetType:
self.jetBranchName = "FatJet"
self.subJetBranchName = "SubJet"
self.genJetBranchName = "GenJetAK8"
self.genSubJetBranchName = "SubGenJetAK8"
if not self.noGroom:
self.doGroomed = True
self.puppiCorrFile = ROOT.TFile.Open(
os.environ['CMSSW_BASE'] +
"/src/PhysicsTools/NanoAODTools/data/jme/puppiCorr.root")
self.puppisd_corrGEN = self.puppiCorrFile.Get(
"puppiJECcorr_gen")
self.puppisd_corrRECO_cen = self.puppiCorrFile.Get(
"puppiJECcorr_reco_0eta1v3")
self.puppisd_corrRECO_for = self.puppiCorrFile.Get(
"puppiJECcorr_reco_1v3eta2v5")
else:
self.doGroomed = False
else:
raise ValueError("ERROR: Invalid jet type = '%s'!" % jetType)
self.rhoBranchName = "fixedGridRhoFastjetAll"
self.lenVar = "n" + self.jetBranchName
# jet mass scale
self.jmsVals = jmsVals
if not self.jmsVals:
print("WARNING: jmsVals is empty!!! Using default values! This " +
"module will soon be deprecated! Please use " +
"jetmetHelperRun2 in the future.")
# 2016 values
self.jmsVals = [1.00, 0.9906, 1.0094] # nominal, down, up
# Use 2017 values for 2018 until 2018 are released
if self.era in ["2017", "2018"]:
self.jmsVals = [0.982, 0.978, 0.986]
# read jet energy scale (JES) uncertainties
# (downloaded from https://twiki.cern.ch/twiki/bin/view/CMS/JECDataMC )
self.jesInputArchivePath = os.environ['CMSSW_BASE'] + \
"/src/PhysicsTools/NanoAODTools/data/jme/"
# Text files are now tarred so must extract first into temporary
# directory (gets deleted during python memory management at script exit)
self.jesArchive = tarfile.open(
self.jesInputArchivePath + globalTag +
".tgz", "r:gz") if not archive else tarfile.open(
self.jesInputArchivePath + archive + ".tgz", "r:gz")
self.jesInputFilePath = tempfile.mkdtemp()
self.jesArchive.extractall(self.jesInputFilePath)
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
self.jesUncertaintyInputFileName = globalTag + "_Uncertainty_" + jetType + ".txt"
elif jesUncertainties[0] == "Merged" and not self.isData:
self.jesUncertaintyInputFileName = "Regrouped_" + \
globalTag + "_UncertaintySources_" + jetType + ".txt"
else:
self.jesGroupedFilePath = os.environ[
'CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/regrouped/"
self.jesGroupedUncertaintyFileName = "RegroupedV2_" + globalTag + "_UncertaintySources_" + jetType + ".txt"
self.jesGroupedUncertaintyFilePath = pjoin(
self.jesGroupedFilePath, self.jesGroupedUncertaintyFileName)
# Copy the uncertainty source file to the tmp directory
shutil.copy(
self.jesGroupedUncertaintyFilePath,
pjoin(self.jesInputFilePath,
self.jesGroupedUncertaintyFileName))
self.jesUncertaintyInputFileName = self.jesGroupedUncertaintyFileName
#self.jesUncertaintyInputFileName = "RegroupedV2_" + globalTag + "_UncertaintySources_" + jetType + ".txt"
# read all uncertainty source names from the loaded file
if jesUncertainties[0] in ["All", "Merged"]:
with open(self.jesInputFilePath + '/' +
self.jesUncertaintyInputFileName) as f:
lines = f.read().split("\n")
sources = [
x for x in lines if x.startswith("[") and x.endswith("]")
]
sources = [x[1:-1] for x in sources]
self.jesUncertainties = sources
if applyHEMfix:
self.jesUncertainties.append("HEMIssue")
self.jetReCalibrator = JetReCalibrator(
globalTag,
jetType,
True,
self.jesInputFilePath,
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
# load libraries for accessing JES scale factors and uncertainties
# from txt files
for library in [
"libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools"
]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
def __init__(self,
era,
globalTag,
jesUncertainties=["Total"],
jetType="AK4PFchs",
redoJEC=False,
noGroom=False):
self.era = era
self.redoJEC = redoJEC
self.noGroom = noGroom
#--------------------------------------------------------------------------------------------
# CV: globalTag and jetType not yet used, as there is no consistent set of txt files for
# JES uncertainties and JER scale factors and uncertainties yet
#--------------------------------------------------------------------------------------------
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data and simulation.
self.jerInputFileName = "Spring16_25nsV10_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Spring16_25nsV10_MC_SF_" + jetType + ".txt"
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName,
self.jerUncertaintyInputFileName)
if "AK4" in jetType:
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.genSubJetBranchName = None
self.doGroomed = False
self.corrMET = True
elif "AK8" in jetType:
self.jetBranchName = "FatJet"
self.subJetBranchName = "SubJet"
self.genJetBranchName = "GenJetAK8"
self.genSubJetBranchName = "SubGenJetAK8"
if not self.noGroom:
self.doGroomed = True
else:
self.doGroomed = False
self.corrMET = False
else:
raise ValueError("ERROR: Invalid jet type = '%s'!" % jetType)
self.metBranchName = "MET"
self.rhoBranchName = "fixedGridRhoFastjetAll"
self.lenVar = "n" + self.jetBranchName
# To do : change to real values
self.jmsVals = [1.00, 0.99, 1.01]
# read jet energy scale (JES) uncertainties
# (downloaded from https://twiki.cern.ch/twiki/bin/view/CMS/JECDataMC )
self.jesInputFilePath = os.environ[
'CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/"
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
if self.era == "2016":
self.jesUncertaintyInputFileName = "Summer16_23Sep2016V4_MC_Uncertainty_" + jetType + ".txt"
elif self.era == "2017":
self.jesUncertaintyInputFileName = "Fall17_17Nov2017_V6_MC_Uncertainty_" + jetType + ".txt"
else:
raise ValueError("ERROR: Invalid era = '%s'!" % self.era)
else:
if self.era == "2016":
self.jesUncertaintyInputFileName = "Summer16_23Sep2016V4_MC_UncertaintySources_" + jetType + ".txt"
elif self.era == "2017":
self.jesUncertaintyInputFileName = "Fall17_17Nov2017_V6_MC_UncertaintySources_" + jetType + ".txt"
else:
raise ValueError("ERROR: Invalid era = '%s'!" % self.era)
# read all uncertainty source names from the loaded file
if jesUncertainties[0] == "All":
with open(self.jesInputFilePath +
self.jesUncertaintyInputFileName) as f:
lines = f.read().split("\n")
sources = filter(
lambda x: x.startswith("[") and x.endswith("]"), lines)
sources = map(lambda x: x[1:-1], sources)
self.jesUncertainties = sources
if self.redoJEC:
self.jetReCalibrator = JetReCalibrator(
globalTag,
jetType,
True,
self.jesInputFilePath,
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
# define energy threshold below which jets are considered as "unclustered energy"
# (cf. JetMETCorrections/Type1MET/python/correctionTermsPfMetType1Type2_cff.py )
self.unclEnThreshold = 15.
# load libraries for accessing JES scale factors and uncertainties from txt files
for library in [
"libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools"
]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
def __init__(self, era, globalTag, jesUncertainties = [ "Total" ], jetType = "AK4PFchs", redoJEC=False, noGroom=False, jerTag="", jmrVals = [], jmsVals = []):
self.era = era
self.redoJEC = redoJEC
self.noGroom = noGroom
#--------------------------------------------------------------------------------------------
# CV: globalTag and jetType not yet used in the jet smearer, as there is no consistent set of
# txt files for JES uncertainties and JER scale factors and uncertainties yet
#--------------------------------------------------------------------------------------------
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data and simulation.
if jerTag != "":
self.jerInputFileName = jerTag + "_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = jerTag + "_SF_" + jetType + ".txt"
else:
print "WARNING: jerTag is empty!!! This module will soon be deprecated! Please use jetmetHelperRun2 in the future."
if era == "2016":
self.jerInputFileName = "Summer16_25nsV1_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Summer16_25nsV1_MC_SF_" + jetType + ".txt"
elif era == "2017" or era == "2018": # use Fall17 as temporary placeholder until post-Moriond 2019 JERs are out
self.jerInputFileName = "Fall17_V3_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Fall17_V3_MC_SF_" + jetType + ".txt"
#jet mass resolution: https://twiki.cern.ch/twiki/bin/view/CMS/JetWtagging
self.jmrVals = jmrVals
if not self.jmrVals:
print "WARNING: jmrVals is empty!!! Using default values. This module will soon be deprecated! Please use jetmetHelperRun2 in the future."
self.jmrVals = [1.0, 1.2, 0.8] #nominal, up, down
# Use 2017 values for 2018 until 2018 are released
if self.era in ["2017","2018"]:
self.jmrVals = [1.09, 1.14, 1.04]
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName, self.jerUncertaintyInputFileName, self.jmrVals)
if "AK4" in jetType :
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.genSubJetBranchName = None
self.doGroomed = False
self.corrMET = True
elif "AK8" in jetType :
self.jetBranchName = "FatJet"
self.subJetBranchName = "SubJet"
self.genJetBranchName = "GenJetAK8"
self.genSubJetBranchName = "SubGenJetAK8"
if not self.noGroom:
self.doGroomed = True
self.puppiCorrFile = ROOT.TFile.Open(os.environ['CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/puppiCorr.root")
self.puppisd_corrGEN = self.puppiCorrFile.Get("puppiJECcorr_gen")
self.puppisd_corrRECO_cen = self.puppiCorrFile.Get("puppiJECcorr_reco_0eta1v3")
self.puppisd_corrRECO_for = self.puppiCorrFile.Get("puppiJECcorr_reco_1v3eta2v5")
else:
self.doGroomed = False
self.corrMET = False
else:
raise ValueError("ERROR: Invalid jet type = '%s'!" % jetType)
self.metBranchName = "MET"
self.rhoBranchName = "fixedGridRhoFastjetAll"
self.lenVar = "n" + self.jetBranchName
#jet mass scale
self.jmsVals = jmsVals
if not self.jmsVals:
print "WARNING: jmsVals is empty!!! Using default values! This module will soon be deprecated! Please use jetmetHelperRun2 in the future."
#2016 values
self.jmsVals = [1.00, 0.9906, 1.0094] #nominal, down, up
# Use 2017 values for 2018 until 2018 are released
if self.era in ["2017","2018"]:
self.jmsVals = [0.982, 0.978, 0.986]
# read jet energy scale (JES) uncertainties
# (downloaded from https://twiki.cern.ch/twiki/bin/view/CMS/JECDataMC )
self.jesInputArchivePath = os.environ['CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/"
# Text files are now tarred so must extract first into temporary directory (gets deleted during python memory management at script exit)
self.jesArchive = tarfile.open(self.jesInputArchivePath+globalTag+".tgz", "r:gz")
self.jesInputFilePath = tempfile.mkdtemp()
self.jesArchive.extractall(self.jesInputFilePath)
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
self.jesUncertaintyInputFileName = globalTag + "_Uncertainty_" + jetType + ".txt"
else:
self.jesUncertaintyInputFileName = globalTag + "_UncertaintySources_" + jetType + ".txt"
# read all uncertainty source names from the loaded file
if jesUncertainties[0] == "All":
with open(self.jesInputFilePath+'/'+self.jesUncertaintyInputFileName) as f:
lines = f.read().split("\n")
sources = filter(lambda x: x.startswith("[") and x.endswith("]"), lines)
sources = map(lambda x: x[1:-1], sources)
self.jesUncertainties = sources
if self.redoJEC :
self.jetReCalibrator = JetReCalibrator(globalTag, jetType , True, self.jesInputFilePath, calculateSeparateCorrections = False, calculateType1METCorrection = False)
# define energy threshold below which jets are considered as "unclustered energy"
# (cf. JetMETCorrections/Type1MET/python/correctionTermsPfMetType1Type2_cff.py )
self.unclEnThreshold = 15.
# load libraries for accessing JES scale factors and uncertainties from txt files
for library in [ "libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools" ]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
def __init__(self,
era,
globalTag,
jesUncertainties=["Total"],
archive=None,
globalTagProd=None,
jetType="AK4PFchs",
metBranchName="MET",
jerTag="",
isData=False,
applySmearing=True):
# globalTagProd only needs to be defined if METFixEE2017 is to be recorrected, and should be the GT that was used for the production of the nanoAOD files
self.era = era
self.isData = isData
self.applySmearing = applySmearing if not isData else False # if set to true, Jet_pt_nom will have JER applied. not to be switched on for data.
self.metBranchName = metBranchName
self.rhoBranchName = "fixedGridRhoFastjetAll"
#--------------------------------------------------------------------------------------------
# CV: globalTag and jetType not yet used in the jet smearer, as there is no consistent set of
# txt files for JES uncertainties and JER scale factors and uncertainties yet
#--------------------------------------------------------------------------------------------
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data and simulation.
if jerTag != "":
self.jerInputFileName = jerTag + "_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = jerTag + "_SF_" + jetType + ".txt"
else:
print "WARNING: jerTag is empty!!! This module will soon be deprecated! Please use jetmetHelperRun2 in the future."
if era == "2016":
self.jerInputFileName = "Summer16_25nsV1_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Summer16_25nsV1_MC_SF_" + jetType + ".txt"
elif era == "2017" or era == "2018": ## use 2017 JER for 2018 for the time being
self.jerInputFileName = "Fall17_V3_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Fall17_V3_MC_SF_" + jetType + ".txt"
elif era == "2018" and False: ## jetSmearer not working with 2018 JERs yet
self.jerInputFileName = "Autumn18_V7_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Autumn18_V7_MC_SF_" + jetType + ".txt"
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName,
self.jerUncertaintyInputFileName)
if "AK4" in jetType:
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.genSubJetBranchName = None
else:
raise ValueError("ERROR: Invalid jet type = '%s'!" % jetType)
self.lenVar = "n" + self.jetBranchName
# read jet energy scale (JES) uncertainties
# (downloaded from https://twiki.cern.ch/twiki/bin/view/CMS/JECDataMC )
self.jesInputArchivePath = os.environ[
'CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/"
# Text files are now tarred so must extract first into temporary directory (gets deleted during python memory management at script exit)
self.jesArchive = tarfile.open(
self.jesInputArchivePath + globalTag +
".tgz", "r:gz") if not archive else tarfile.open(
self.jesInputArchivePath + archive + ".tgz", "r:gz")
self.jesInputFilePath = tempfile.mkdtemp()
self.jesArchive.extractall(self.jesInputFilePath)
# to fully re-calculate type-1 MET the JEC that are currently applied are also needed. IS THAT EVEN CORRECT?
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
self.jesUncertaintyInputFileName = globalTag + "_Uncertainty_" + jetType + ".txt"
else:
self.jesUncertaintyInputFileName = globalTag + "_UncertaintySources_" + jetType + ".txt"
# read all uncertainty source names from the loaded file
if jesUncertainties[0] == "All":
with open(self.jesInputFilePath + '/' +
self.jesUncertaintyInputFileName) as f:
lines = f.read().split("\n")
sources = filter(
lambda x: x.startswith("[") and x.endswith("]"), lines)
sources = map(lambda x: x[1:-1], sources)
self.jesUncertainties = sources
# Define the jet recalibrator
self.jetReCalibrator = JetReCalibrator(
globalTag,
jetType,
True,
self.jesInputFilePath,
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
# Define the recalibrator for level 1 corrections only
self.jetReCalibratorL1 = JetReCalibrator(
globalTag,
jetType,
False,
self.jesInputFilePath,
calculateSeparateCorrections=True,
calculateType1METCorrection=False,
upToLevel=1)
# Define the recalibrators for GT used in nanoAOD production (only needed to reproduce 2017 v2 MET)
if globalTagProd:
self.jetReCalibratorProd = JetReCalibrator(
globalTagProd,
jetType,
True,
self.jesInputFilePath,
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
self.jetReCalibratorProdL1 = JetReCalibrator(
globalTagProd,
jetType,
False,
self.jesInputFilePath,
calculateSeparateCorrections=True,
calculateType1METCorrection=False,
upToLevel=1)
else:
self.jetReCalibratorProd = False
self.jetReCalibratorProdL1 = False
# define energy threshold below which jets are considered as "unclustered energy"
# (cf. JetMETCorrections/Type1MET/python/correctionTermsPfMetType1Type2_cff.py )
self.unclEnThreshold = 15.
# load libraries for accessing JES scale factors and uncertainties from txt files
for library in [
"libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools"
]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
def __init__(self,
era,
globalTag,
jesUncertainties=["Total"],
jetType="AK4PFchs",
redoJEC=False,
noGroom=False,
reducedJECsystematics=False):
self.era = era
self.redoJEC = redoJEC
self.noGroom = noGroom
#--------------------------------------------------------------------------------------------
# CV: globalTag and jetType not yet used in the jet smearer, as there is no consistent set of
# txt files for JES uncertainties and JER scale factors and uncertainties yet
#--------------------------------------------------------------------------------------------
self.jesUncertainties = jesUncertainties
# smear jet pT to account for measured difference in JER between data and simulation.
if era == "2016":
self.jerInputFileName = "Summer16_25nsV1b_MC/Summer16_25nsV1b_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Summer16_25nsV1b_MC/Summer16_25nsV1b_MC_SF_" + jetType + ".txt"
elif era == "2017": # use Fall17 as temporary placeholder until post-Moriond 2019 JERs are out
self.jerInputFileName = "Fall17_V3b_MC/Fall17_V3b_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Fall17_V3b_MC/Fall17_V3b_MC_SF_" + jetType + ".txt"
elif era == "2018": ## (see https://hypernews.cern.ch/HyperNews/CMS/get/JetMET/1994.html)
self.jerInputFileName = "Autumn18_V7b_MC/Autumn18_V7b_MC_PtResolution_" + jetType + ".txt"
self.jerUncertaintyInputFileName = "Autumn18_V7b_MC/Autumn18_V7b_MC_SF_" + jetType + ".txt"
#jet mass resolution: https://twiki.cern.ch/twiki/bin/view/CMS/JetWtagging
if self.era == "2016" or self.era == "2018": #update when 2018 values available
self.jmrVals = [1.0, 1.2, 0.8] #nominal, up, down
else:
self.jmrVals = [1.09, 1.14, 1.04]
self.jetSmearer = jetSmearer(globalTag, jetType, self.jerInputFileName,
self.jerUncertaintyInputFileName,
self.jmrVals)
if "AK4" in jetType:
self.jetBranchName = "Jet"
self.genJetBranchName = "GenJet"
self.genSubJetBranchName = None
self.doGroomed = False
self.corrMET = True
elif "AK8" in jetType:
self.jetBranchName = "FatJet"
self.subJetBranchName = "SubJet"
self.genJetBranchName = "GenJetAK8"
self.genSubJetBranchName = "SubGenJetAK8"
if not self.noGroom:
self.doGroomed = True
else:
self.doGroomed = False
self.corrMET = False
else:
raise ValueError("ERROR: Invalid jet type = '%s'!" % jetType)
self.metBranchName = "MET"
self.rhoBranchName = "fixedGridRhoFastjetAll"
self.lenVar = "n" + self.jetBranchName
#jet mass scale
#W-tagging PUPPI softdrop JMS values: https://twiki.cern.ch/twiki/bin/view/CMS/JetWtagging
#2016 values - use for 2018 until new values available
self.jmsVals = [1.00, 0.9906, 1.0094] #nominal, down, up
if self.era == "2017":
self.jmsVals = [0.982, 0.978, 0.986]
# read jet energy scale (JES) uncertainties
# (downloaded from https://twiki.cern.ch/twiki/bin/view/CMS/JECDataMC )
self.jesInputArchivePath = os.environ[
'CMSSW_BASE'] + "/src/PhysicsTools/NanoAODTools/data/jme/"
# Text files are now tarred so must extract first into temporary directory (gets deleted during python memory management at script exit)
self.jesArchive = tarfile.open(
self.jesInputArchivePath + globalTag + ".tgz", "r:gz")
self.jesInputFilePath = tempfile.mkdtemp()
self.jesArchive.extractall(self.jesInputFilePath)
if len(jesUncertainties) == 1 and jesUncertainties[0] == "Total":
if self.era == "2016":
self.jesUncertaintyInputFileName = "Summer16_07Aug2017_V11_MC_Uncertainty_" + jetType + ".txt"
elif self.era == "2017":
self.jesUncertaintyInputFileName = "Fall17_17Nov2017_V32_MC_Uncertainty_" + jetType + ".txt"
elif self.era == "2018":
self.jesUncertaintyInputFileName = "Autumn18_V19_MC_Uncertainty_" + jetType + ".txt"
else:
raise ValueError("ERROR: Invalid era = '%s'!" % self.era)
else:
if self.era == "2016":
self.jesUncertaintyInputFileName = "Summer16_07Aug2017_V11_MC_UncertaintySources_" + jetType + ".txt"
elif self.era == "2017":
self.jesUncertaintyInputFileName = "Fall17_17Nov2017_V32_MC_UncertaintySources_" + jetType + ".txt"
elif self.era == "2018":
self.jesUncertaintyInputFileName = "Autumn18_V19_MC_UncertaintySources_" + jetType + ".txt"
else:
raise ValueError("ERROR: Invalid era = '%s'!" % self.era)
if reducedJECsystematics:
## Use https://twiki.cern.ch/twiki/bin/viewauth/CMS/JECUncertaintySources#Run_2_reduced_set_of_uncertainty ##
self.jesUncertaintyInputFileName = "Regrouped_" + self.jesUncertaintyInputFileName
# read all uncertainty source names from the loaded file
if jesUncertainties[0] == "All":
with open(self.jesInputFilePath + '/' +
self.jesUncertaintyInputFileName) as f:
lines = f.read().split("\n")
sources = filter(
lambda x: x.startswith("[") and x.endswith("]"), lines)
sources = map(lambda x: x[1:-1], sources)
self.jesUncertainties = sources
if self.redoJEC:
self.jetReCalibrator = JetReCalibrator(
globalTag,
jetType,
True,
self.jesInputFilePath,
calculateSeparateCorrections=False,
calculateType1METCorrection=False)
# define energy threshold below which jets are considered as "unclustered energy"
# (cf. JetMETCorrections/Type1MET/python/correctionTermsPfMetType1Type2_cff.py )
self.unclEnThreshold = 15.
# load libraries for accessing JES scale factors and uncertainties from txt files
for library in [
"libCondFormatsJetMETObjects", "libPhysicsToolsNanoAODTools"
]:
if library not in ROOT.gSystem.GetLibraries():
print("Load Library '%s'" % library.replace("lib", ""))
ROOT.gSystem.Load(library)
