def doCounters(datasetsEmb):
eventCounter = tauEmbedding.EventCounterMany(datasetsEmb, normalize=True)
#row = "btagging scale factor"
row = "deltaPhiTauMET<160"
#row = "deltaPhiTauMET<130"
table = eventCounter.getMainCounterTable()
table.keepOnlyRows([row])
result = counter.CounterTable()
def addRow(name, newktt, nsignal):
fraction = None
if nsignal != None:
fraction = nsignal.clone()
total = nsignal.clone()
total.add(newktt)
fraction.divide(total)
fraction.multiply(dataset.Count(100))
result.appendRow(counter.CounterRow(name, ["EWK+tt events", "Signal events", "Signal fraction (\%)"], [newktt, nsignal, fraction]))
addRow("No signal", table.getCount(irow=0, colName="EWKMC"), None)
ewkWithSignal = table.getCount(irow=0, colName="EWKScaled")
for mass in [80, 90, 100, 120, 140, 150, 155, 160]:
addRow("H+ M%d"%mass, ewkWithSignal, table.getCount(irow=0, colName="TTToHplus_M%d"%mass))
#cellFormat = counter.TableFormatLaTeX(counter.CellFormatTeX(valueFormat='%.3f'))
cellFormat = counter.TableFormatLaTeX(counter.CellFormatTeX(valueFormat='%.4f', withPrecision=2))
print result.format(cellFormat)
def doCounters(datasetsEmb, datasetsSig, datasetName):
lumi = datasetsEmb.getLuminosity()
# Counters
eventCounterEmb = tauEmbedding.EventCounterMany(datasetsEmb)
eventCounterSig = counter.EventCounter(datasetsSig)
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
tableEmb = eventCounterEmb.getMainCounterTable()
tableSig = eventCounterSig.getMainCounterTable()
table = counter.CounterTable()
col = tableEmb.getColumn(name=datasetName)
col.setName(datasetName+" emb")
table.appendColumn(col)
col = tableSig.getColumn(name=datasetName)
col.setName(datasetName+" norm")
table.appendColumn(col)
table.keepOnlyRows([
"njets",
"MET",
"btagging",
"btagging scale factor",
"deltaPhiTauMET<160",
"deltaPhiTauMET<130",
])
table.renameRows({"njets": "tau ID"})
return table
def doCounters(dirEmbs):
datasetsEmb = tauEmbedding.DatasetsMany(dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.setLumiFromData()
datasetsEmb.remove(filter(lambda name: "HplusTB" in name, datasetsEmb.getAllDatasetNames()))
datasetsEmb.remove(filter(lambda name: "TTToHplus" in name, datasetsEmb.getAllDatasetNames()))
eventCounter = tauEmbedding.EventCounterMany(datasetsEmb)
mainTable = eventCounter.getMainCounterTable()
ewkDatasets = ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"]
def ewkSum(table):
table.insertColumn(1, counter.sumColumn("EWKMCsum", [table.getColumn(name=name) for name in ewkDatasets]))
ewkSum(mainTable)
datasetsEmb.close()
return mainTable.getRow(name="deltaPhiTauMET<160")
def doCounters(datasetsEmb):
eventCounter = tauEmbedding.EventCounterMany(datasetsEmb,
counters=analysisEmb +
counters,
normalize=True)
mainTable = eventCounter.getMainCounterTable()
ewkDatasets = ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"]
def ewkSum(table):
table.insertColumn(
1,
counter.sumColumn(
"EWKMCsum",
[table.getColumn(name=name) for name in ewkDatasets]))
ewkSum(mainTable)
cellFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.3f'))
print mainTable.format(cellFormat)
def doCounters(datasetsEmb, datasetsSig, datasetName, normalizeEmb=True):
lumi = datasetsEmb.getLuminosity()
# Counters
eventCounterEmb = tauEmbedding.EventCounterMany(
datasetsEmb,
normalize=normalizeEmb) #, counters=analysisEmb+"/counters")
eventCounterSig = counter.EventCounter(datasetsSig)
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(
filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(
filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
tdCount = dataset.TreeDraw("dummy",
weight=tauEmbedding.signalNtuple.weightBTagging)
tdCountMET = tdCount.clone(weight=tauEmbedding.signalNtuple.weight,
selection=tauEmbedding.signalNtuple.metCut)
tdCountBTagging = tdCount.clone(
selection=And(tauEmbedding.signalNtuple.metCut,
tauEmbedding.signalNtuple.bTaggingCut))
tdCountDeltaPhi160 = tdCount.clone(selection=And(
tauEmbedding.signalNtuple.metCut, tauEmbedding.signalNtuple.
bTaggingCut, tauEmbedding.signalNtuple.deltaPhi160Cut))
tdCountDeltaPhi130 = tdCount.clone(selection=And(
tauEmbedding.signalNtuple.metCut, tauEmbedding.signalNtuple.
bTaggingCut, tauEmbedding.signalNtuple.deltaPhi130Cut))
def addRow(name, td):
tdEmb = td.clone(tree=analysisEmb + "/tree")
tdSig = td.clone(tree=analysisSig + "/tree")
eventCounterEmb.mainCounterAppendRow(name, tdEmb)
eventCounterSig.getMainCounter().appendRow(name, tdSig)
# addRow("JetsForEffs", tdCount.clone(weight=tauEmbedding.signalNtuple.weight))
# addRow("METForEffs", tdCountMET)
# addRow("BTagging (SF)", tdCountBTagging)
# addRow("DeltaPhi < 160", tdCountDeltaPhi160)
# addRow("BTagging (SF) again", tdCountBTagging)
# addRow("DeltaPhi < 130", tdCountDeltaPhi130)
table = counter.CounterTable()
col = eventCounterEmb.getMainCounterTable().getColumn(name=datasetName)
col.setName("Embedded")
table.appendColumn(col)
col = eventCounterSig.getMainCounterTable().getColumn(name=datasetName)
col.setName("Normal")
table.appendColumn(col)
tableTau = counter.CounterTable()
tmp = "TauIDPassedEvt::TauSelection_HPS"
col = eventCounterEmb.getSubCounterTable(tmp).getColumn(name=datasetName)
col.setName("Embedded")
tableTau.appendColumn(col)
col = eventCounterSig.getSubCounterTable(tmp).getColumn(name=datasetName)
col.setName("Normal")
tableTau.appendColumn(col)
postfix = ""
if not normalizeEmb:
postfix = "_notEmbNormalized"
fname = "counters_selections_%s%s.txt" % (datasetName, postfix)
f = open(fname, "w")
f.write(table.format())
f.write("\n")
f.write(tableTau.format())
f.close()
print "Printed selection counters to", fname
if not normalizeEmb:
return
# Calculate efficiencies
table.keepOnlyRows([
"njets", "MET", "btagging", "btagging scale factor",
"DeltaPhi(Tau,MET) upper limit"
])
# btag SF efficiency w.r.t. MET
row = table.getRow(name="MET")
row.setName("METForEff")
table.insertRow(3, row)
tableEff = counter.CounterTable()
tableEff.appendColumn(
counter.efficiencyColumn("Embedded eff",
table.getColumn(name="Embedded")))
tableEff.appendColumn(
counter.efficiencyColumn("Normal eff", table.getColumn(name="Normal")))
tableEff.removeRow(name="METForEff")
effFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.4f', withPrecision=2))
# print table.format(effFormat)
fname = "counters_selections_%s_eff.txt" % datasetName
f = open(fname, "w")
f.write(tableEff.format(effFormat))
f.close()
print "Printed selection efficiencies to", fname
def doTauCounters(datasetsEmb,
datasetsSig,
datasetName,
ntupleCacheEmb,
ntupleCacheSig,
normalizeEmb=True):
lumi = datasetsEmb.getLuminosity()
# Take unweighted counters for embedded, to get a handle on the muon isolation efficiency
eventCounterEmb = tauEmbedding.EventCounterMany(
datasetsEmb,
counters="/" + tauAnalysisEmb + "Counters",
normalize=normalizeEmb)
eventCounterSig = counter.EventCounter(datasetsSig,
counters="/" + tauAnalysisEmb +
"Counters")
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(
filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(
filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterEmb.mainCounterAppendRows(
ntupleCacheEmb.histogram("counters/weighted/counter"))
eventCounterSig.getMainCounter().appendRows(
ntupleCacheSig.histogram("counters/weighted/counter"))
eventCounterSig.normalizeMCToLuminosity(lumi)
table = counter.CounterTable()
col = eventCounterEmb.getMainCounterTable().getColumn(name=datasetName)
col.setName("Embedded")
table.appendColumn(col)
col = eventCounterSig.getMainCounterTable().getColumn(name=datasetName)
col.setName("Normal")
table.appendColumn(col)
lastCountEmb = table.getCount(colName="Embedded",
irow=table.getNrows() - 1)
lastCountNormal = table.getCount(colName="Normal",
irow=table.getNrows() - 1)
postfix = ""
if not normalizeEmb:
postfix = "_notEmbNormalized"
effFormat = counter.TableFormatLaTeX(
counter.CellFormatTeX(valueFormat="%.4f", withPrecision=2))
countFormat = counter.TableFormatText(
counter.CellFormatText(valueFormat="%.4f"),
#columnSeparator=" ;"
)
fname = "counters_tau_" + datasetName + postfix + ".txt"
f = open(fname, "w")
f.write(table.format(countFormat))
f.write("\n")
try:
ratio = lastCountNormal.clone()
ratio.divide(lastCountEmb)
f.write("Normal/embedded = %.4f +- %.4f\n\n" %
(ratio.value(), ratio.uncertainty()))
except ZeroDivisionError:
pass
f.close()
print "Printed tau counters to", fname
if not normalizeEmb:
return
tableEff = counter.CounterTable()
tableEff.appendColumn(
counter.efficiencyColumn("Embedded eff",
table.getColumn(name="Embedded")))
tableEff.appendColumn(
counter.efficiencyColumn("Normal eff", table.getColumn(name="Normal")))
embeddingMuonIsolationEff = tableEff.getCount(
rowName="tauEmbeddingMuonsCount", colName="Embedded eff")
embeddingTauIsolationEff = tableEff.getCount(rowName="Isolation",
colName="Embedded eff")
embeddingTotalIsolationEff = embeddingMuonIsolationEff.clone()
embeddingTotalIsolationEff.multiply(embeddingTauIsolationEff)
# Remove unnecessary rows
rowNames = [
# "All events",
"Decay mode finding",
"Eta cut",
"Pt cut",
"Leading track pt",
"Against electron",
"Against muon",
"Isolation",
"One prong",
"Rtau",
]
tableEff.keepOnlyRows(rowNames)
rowIndex = tableEff.getRowNames().index("Isolation")
tableEff.insertRow(
rowIndex,
counter.CounterRow("Mu isolation (emb)",
["Embedded eff", "Normal eff"],
[embeddingMuonIsolationEff, None]))
tableEff.insertRow(
rowIndex + 1,
counter.CounterRow("Tau isolation (emb)",
["Embedded eff", "Normal eff"],
[embeddingTauIsolationEff, None]))
tableEff.setCount2(embeddingTotalIsolationEff,
rowName="Isolation",
colName="Embedded eff")
#tableEff.setCount2(None, rowName="pT > 15", colName="Normal eff")
#print table.format(effFormat)
fname = "counters_tau_" + datasetName + "_eff.txt"
f = open(fname, "w")
f.write(tableEff.format(effFormat))
f.write("\n")
f.close()
print "Printed tau efficiencies to", fname
def doCounters(datasetsEmb):
# All embedded events
eventCounterAll = counter.EventCounter(
datasetsEmb.getFirstDatasetManager(),
counters=analysisEmbAll + counters)
eventCounterAll.normalizeMCByLuminosity()
tableAll = eventCounterAll.getMainCounterTable()
tableAll.keepOnlyRows([
"All events",
])
tableAll.renameRows({"All events": "All embedded events"})
# Mu eff + Wtau mu
eventCounterMuEff = counter.EventCounter(
datasetsEmb.getFirstDatasetManager(),
counters=analysisEmbNoTauEff + counters)
eventCounterMuEff.normalizeMCByLuminosity()
tauEmbedding.scaleNormalization(eventCounterMuEff)
tableMuEff = eventCounterMuEff.getMainCounterTable()
tableMuEff.keepOnlyRows(["All events"])
tableMuEff.renameRows({"All events": "mu eff + Wtaumu"})
# Event counts after embedding normalization, before tau trigger eff,
# switch to calculate uncertainties of the mean of 10 trials
eventCounterNoTauEff = tauEmbedding.EventCounterMany(
datasetsEmb, counters=analysisEmbNoTauEff + counters)
tableNoTauEff = eventCounterNoTauEff.getMainCounterTable()
tableNoTauEff.keepOnlyRows([
"Trigger and HLT_MET cut",
"njets",
])
tableNoTauEff.renameRows({
"Trigger and HLT_MET cut": "caloMET > 60",
"njets": "tau ID"
})
# Event counts after tau trigger eff
eventCounter = tauEmbedding.EventCounterMany(datasetsEmb,
counters=analysisEmb +
counters)
table = eventCounter.getMainCounterTable()
table.keepOnlyRows([
"njets", "MET", "btagging scale factor", "deltaPhiTauMET<160",
"deltaPhiTauMET<130"
])
table.renameRows({
"njets": "Tau trigger efficiency",
"btagging scale factor": "b tagging"
})
# Combine the rows to one table
result = counter.CounterTable()
for tbl in [tableAll, tableMuEff, tableNoTauEff, table]:
for iRow in xrange(tbl.getNrows()):
result.appendRow(tbl.getRow(index=iRow))
addMcSum(result)
cellFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.4f', withPrecision=2))
print result.format(cellFormat)
def doCounters(datasetsEmb, datasetsSig, datasetName):
lumi = datasetsEmb.getLuminosity()
treeDraw = dataset.TreeDraw("dummy", weight=weight)
# Counters
eventCounterEmb = tauEmbedding.EventCounterMany(datasetsEmb, counters=analysisEmb+"Counters")
eventCounterSig = counter.EventCounter(datasetsSig, counters=analysisSig+"Counters")
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
#effFormat = counter.TableFormatText(counter.CellFormatText(valueFormat='%.4f'))
#effFormat = counter.TableFormatConTeXtTABLE(counter.CellFormatTeX(valueFormat='%.4f'))
effFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.4f'))
tdEmb = treeDraw.clone(tree=analysisEmb+"/tree")
tdSig = treeDraw.clone(tree=analysisSig+"/tree")
selectionsCumulative = []
tauSelectionsCumulative = []
def sel(name, selection):
selectionsCumulative.append(selection)
sel = selectionsCumulative[:]
if len(tauSelectionsCumulative) > 0:
sel += ["Sum$(%s) >= 1" % "&&".join(tauSelectionsCumulative)]
sel = "&&".join(sel)
eventCounterEmb.mainCounterAppendRow(name, tdEmb.clone(selection=sel))
eventCounterSig.getMainCounter().appendRow(name, tdSig.clone(selection=sel))
def tauSel(name, selection):
tauSelectionsCumulative.append(selection)
sel = selectionsCumulative[:]
if len(tauSelectionsCumulative) > 0:
sel += ["Sum$(%s) >= 1" % "&&".join(tauSelectionsCumulative)]
sel = "&&".join(sel)
eventCounterEmb.mainCounterAppendRow(name, tdEmb.clone(selection=sel))
eventCounterSig.getMainCounter().appendRow(name, tdSig.clone(selection=sel))
# sel("Primary vertex", tauEmbedding.tauNtuple.pvSelection)
sel(">= 1 tau candidate", "Length$(taus_p4) >= 1")
tauSel("Decay mode finding", tauEmbedding.tauNtuple.decayModeFinding)
tauSel("pT > 15", tauEmbedding.tauNtuple.tauPtPreCut)
tauSel("pT > 40", tauEmbedding.tauNtuple.tauPtCut)
tauSel("eta < 2.1", tauEmbedding.tauNtuple.tauEtaCut)
tauSel("leading track pT > 20", tauEmbedding.tauNtuple.tauLeadPt)
tauSel("ECAL fiducial", tauEmbedding.tauNtuple.ecalFiducial)
tauSel("againstElectron", tauEmbedding.tauNtuple.electronRejection)
tauSel("againstMuon", tauEmbedding.tauNtuple.muonRejection)
tauSel("isolation", tauEmbedding.tauNtuple.tightIsolation)
tauSel("oneProng", tauEmbedding.tauNtuple.oneProng)
tauSel("Rtau", tauEmbedding.tauNtuple.rtau)
sel("3 jets", tauEmbedding.tauNtuple.jetEventSelection)
sel("MET", tauEmbedding.tauNtuple.metSelection)
sel("btag", tauEmbedding.tauNtuple.btagEventSelection)
table = counter.CounterTable()
col = eventCounterEmb.getMainCounterTable().getColumn(name=datasetName)
col.setName("Embedded")
table.appendColumn(col)
col = eventCounterSig.getMainCounterTable().getColumn(name=datasetName)
col.setName("Normal")
table.appendColumn(col)
col = table.getColumn(name="Embedded")
table.insertColumn(1, counter.efficiencyColumn(col.getName()+" eff", col))
col = table.getColumn(name="Normal")
table.appendColumn(counter.efficiencyColumn(col.getName()+" eff", col))
print "%s counters" % datasetName
print table.format(effFormat)
f = open("counters_"+datasetName+".txt", "w")
f.write(table.format(effFormat))
f.write("\n")
f.close()
def doCounters(datasetsEmb, datasetsSig, datasetName):
lumi = datasetsEmb.getLuminosity()
# Counters
eventCounterEmb = tauEmbedding.EventCounterMany(datasetsEmb,
counters=analysisEmb +
"Counters/weighted")
eventCounterSig = counter.EventCounter(datasetsSig,
counters=analysisSig +
"Counters/weighted")
def isNotThis(name):
return name != datasetName
#eventCounterSig.normalizeMCToLuminosity(lumi)
#print eventCounterSig.getMainCounterTable().format()
#return
eventCounterEmb.removeColumns(
filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(
filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
tdCount = dataset.TreeDraw("dummy", weight=weightBTagging)
tdCountMET = tdCount.clone(weight=weight, selection=metCut)
tdCountBTagging = tdCount.clone(selection=And(metCut, bTaggingCut))
tdCountDeltaPhi160 = tdCount.clone(
selection=And(metCut, bTaggingCut, deltaPhi160Cut))
tdCountDeltaPhi130 = tdCount.clone(
selection=And(metCut, bTaggingCut, deltaPhi130Cut))
def addRow(name, td):
tdEmb = td.clone(tree=analysisEmb + "/tree")
tdSig = td.clone(tree=analysisSig + "/tree")
eventCounterEmb.mainCounterAppendRow(name, tdEmb)
eventCounterSig.getMainCounter().appendRow(name, tdSig)
addRow("JetsForEffs", tdCount.clone(weight=weight))
addRow("METForEffs", tdCountMET)
addRow("BTagging (SF)", tdCountBTagging)
addRow("DeltaPhi < 160", tdCountDeltaPhi160)
addRow("BTagging (SF) again", tdCountBTagging)
addRow("DeltaPhi < 130", tdCountDeltaPhi130)
#effFormat = counter.TableFormatText(counter.CellFormatText(valueFormat='%.4f'))
#effFormat = counter.TableFormatConTeXtTABLE(counter.CellFormatTeX(valueFormat='%.4f'))
effFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.4f'))
f = open("counters_%s.txt" % datasetName, "w")
for function, cname in [
(lambda c: c.getMainCounterTable(), "Main"),
(lambda c: c.getSubCounterTable("TauIDPassedEvt::tauID_HPSTight"),
"Tau")
]:
tableEmb = function(eventCounterEmb)
tableSig = function(eventCounterSig)
table = counter.CounterTable()
col = tableEmb.getColumn(name=datasetName)
col.setName("Embedded")
table.appendColumn(col)
col = tableSig.getColumn(name=datasetName)
col.setName("Normal")
table.appendColumn(col)
f.write("%s counters\n" % cname)
f.write(table.format())
f.write("\n")
if cname == "Main":
#map(lambda t: t.keepOnlyRows([
table.keepOnlyRows([
"All events",
"Trigger and HLT_MET cut",
"taus == 1",
#"trigger scale factor",
"electron veto",
"muon veto",
"MET",
"njets",
"btagging",
"btagging scale factor",
"JetsForEffs",
"METForEffs",
"BTagging (SF)",
"DeltaPhi < 160",
"BTagging (SF) again",
"DeltaPhi < 130"
]) #, [tableEmb, tableSig])
else:
#map(lambda t: t.keepOnlyRows([
table.keepOnlyRows([
"AllTauCandidates",
"DecayModeFinding",
"TauJetPt",
"TauJetEta",
#"TauLdgTrackExists",
"TauLdgTrackPtCut",
"TauECALFiducialCutsCracksAndGap",
"TauAgainstElectronCut",
"TauAgainstMuonCut",
#"EMFractionCut",
"HPS",
"TauOneProngCut",
"TauRtauCut",
]) #, [tableEmb, tableSig])
col = table.getColumn(name="Embedded")
table.insertColumn(
1, counter.efficiencyColumn(col.getName() + " eff", col))
col = table.getColumn(name="Normal")
table.appendColumn(
counter.efficiencyColumn(col.getName() + " eff", col))
f.write("%s counters\n" % cname)
f.write(table.format(effFormat))
f.write("\n\n")
f.close()
def doCounters(datasetsEmb):
isCorrected = isinstance(datasetsEmb, result.DatasetsDYCorrection)
if isCorrected:
eventCounter = result.EventCounterDYCorrection(datasetsEmb,
counters=analysisEmb +
counters)
else:
scaleNormalization = analysisEmb != "signalAnalysis"
eventCounter = tauEmbedding.EventCounterMany(
datasetsEmb,
counters=analysisEmb + counters,
normalize=scaleNormalization)
# Add counts
sels = []
tdCount = treeDraw.clone(weight=weightBTagging)
tdCountMET = tdCount.clone(weight=weight,
selection="&&".join(sels + [metCut]))
tdCountBTagging = tdCount.clone(selection="&&".join(sels +
[metCut, bTaggingCut]))
tdCountDeltaPhi160 = tdCount.clone(
selection="&&".join(sels + [metCut, bTaggingCut, deltaPhi160Cut]))
tdCountDeltaPhi130 = tdCount.clone(
selection="&&".join(sels + [metCut, bTaggingCut, deltaPhi130Cut]))
tdCountDeltaPhi90 = tdCount.clone(
selection="&&".join(sels + [metCut, bTaggingCut, deltaPhi90Cut]))
eventCounter.mainCounterAppendRow(
"JetsForEffs", tdCount.clone(weight=weight, selection="&&".join(sels)))
eventCounter.mainCounterAppendRow("METForEffs", tdCountMET)
eventCounter.mainCounterAppendRow("BTagging", tdCountBTagging)
eventCounter.mainCounterAppendRow("DeltaPhi < 160", tdCountDeltaPhi160)
eventCounter.mainCounterAppendRow("DeltaPhi < 130", tdCountDeltaPhi130)
eventCounter.mainCounterAppendRow("DeltaPhi < 90", tdCountDeltaPhi90)
if not isCorrected:
td1 = tdCount.clone(selection=metCut + "&&" + bTaggingCut +
"&& (tecalometNoHF_p4.Pt() > 60)")
td2 = tdCount.clone(selection=metCut + "&&" + bTaggingCut +
"&& (tecalomet_p4.Pt() > 60)")
td3 = dataset.TreeDrawCompound(
td1, {
"SingleMu_Mu_170722-172619_Aug05": td2,
"SingleMu_Mu_172620-173198_Prompt": td2,
"SingleMu_Mu_173236-173692_Prompt": td2,
})
eventCounter.mainCounterAppendRow("BTagging+CaloMetNoHF", td1)
eventCounter.mainCounterAppendRow("BTagging+CaloMet", td2)
eventCounter.mainCounterAppendRow("BTagging+CaloMet(NoHF)", td3)
#(mainTable, mainTableChi2) = eventCounter.getMainCounterTableFit()
mainTable = eventCounter.getMainCounterTable()
ewkDatasets = ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"]
allDatasets = None
if "QCD_Pt20_MuEnriched" in datasetsEmb.getAllDatasetNames():
allDatasets = ["QCD_Pt20_MuEnriched"] + ewkDatasets
def ewkSum(table):
table.insertColumn(
1,
counter.sumColumn(
"EWKMCsum",
[table.getColumn(name=name) for name in ewkDatasets]))
if allDatasets != None:
table.insertColumn(
2,
counter.sumColumn(
"MCSum",
[table.getColumn(name=name) for name in allDatasets]))
ewkSum(mainTable)
cellFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.3f'))
#print mainTableChi2.format(cellFormat)
print mainTable.format(cellFormat)
tauTable = eventCounter.getSubCounterTable(
"TauIDPassedEvt::tauID_HPSTight")
ewkSum(tauTable)
print tauTable.format(cellFormat)
# Efficiencies
mainTable.keepOnlyRows([
"All events",
"Trigger and HLT_MET cut",
"taus == 1",
# "trigger scale factor",
"electron veto",
"muon veto",
"MET",
"njets",
"btagging",
"btagging scale factor",
"JetsForEffs",
"METForEffs",
"BTagging",
"DeltaPhi < 160",
"DeltaPhi < 130"
])
tauTable.keepOnlyRows([
"AllTauCandidates",
"DecayModeFinding",
"TauJetPt",
"TauJetEta",
"TauLdgTrackExists",
"TauLdgTrackPtCut",
"TauECALFiducialCutsCracksAndGap",
"TauAgainstElectronCut",
"TauAgainstMuonCut",
#"EMFractionCut",
"HPS",
"TauOneProngCut",
"TauRtauCut",
])
effFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.4f'))
#effFormat = counter.TableFormatConTeXtTABLE(counter.CellFormatTeX(valueFormat='%.4f'))
for name, table in [("Main", mainTable), ("Tau ID", tauTable)]:
effTable = counter.CounterTable()
col = table.getColumn(name="Data")
effTable.appendColumn(col)
effTable.appendColumn(
counter.efficiencyColumn(col.getName() + " eff", col))
col = table.getColumn(name="EWKMCsum")
effTable.appendColumn(col)
effTable.appendColumn(
counter.efficiencyColumn(col.getName() + " eff", col))
print "%s counter efficiencies" % name
print effTable.format(effFormat)
if isCorrected:
return
print "Trigger uncertainties"
bins = [40, 50, 60, 80]
tauPtPrototype = ROOT.TH1F("tauPtTrigger", "Tau pt",
len(bins) - 1, array.array("d", bins))
runs = [
"(160431 <= run && run <= 167913)",
"(170722 <= run && run <= 173198)",
"(173236 <= run && run <= 173692)",
#"(160431 <= run && run <= 173692)",
]
for name, td in [("BTagging", tdCountBTagging),
("DeltaPhi160", tdCountDeltaPhi160),
("DeltaPhi130", tdCountDeltaPhi130),
("DeltaPhi90", tdCountDeltaPhi90)]:
t = td.clone(varexp="tau_p4.Pt() >>tauPtTrigger")
NallSum = 0
NSum = 0
absUncSquareSum = 0
for runRegion in runs:
#neventsPlot = createPlot(dataset.treeDrawToNumEntries(t.clone(weight="weightTrigger")))
#uncertaintyPlot = createPlot(dataset.treeDrawToNumEntries(t.clone(weight="weightTriggerAbsUnc*weightTriggerAbsUnc/(weightTrigger*weightTrigger)")))
tmp = t.clone(selection=t.selection + "&&" + runRegion)
(th1all,
gr) = datasetsEmb.getHistogram("Data",
tmp.clone(weight="")) # Nall
(th1, gr) = datasetsEmb.getHistogram(
"Data", tmp.clone(weight="weightTrigger")) # Nevents
(th12, gr) = datasetsEmb.getHistogram(
"Data", tmp.clone(weight="weightTriggerAbsUnc")) # uncertainty
Nall = th1all.Integral(0, th1all.GetNbinsX() + 1)
N = th1.Integral(0, th1.GetNbinsX() + 1)
#absSum2 = th12.Integral(0, th12.GetNbinsX()+1)
#absUnc = math.sqrt(absSum2)
#absUnc = th12.Integral(0, 2)
NallSum += Nall
NSum += N
absUnc = tauEmbedding.squareSum(th12)
absUncSquareSum += absUnc
absUnc = math.sqrt(absUnc)
relUnc = 0
if N > 0:
relUnc = absUnc / N
print "%-15s for runs %s Nall = %.2f, N = %.2f, absolute uncertainty %.2f, relative uncertainty %.4f" % (
name, runRegion, Nall, N, absUnc, relUnc)
absUnc = math.sqrt(absUncSquareSum)
relUnc = absUnc / NSum
print "%-15s Nall = %.2f, N = %.2f, absolute uncertainty %.2f, relative uncertainty %.4f" % (
name, NallSum, NSum, absUnc, relUnc)
print
def doCounters(datasetsEmb, datasetsSig, datasetName):
lumi = datasetsEmb.getLuminosity()
# Counters
eventCounterEmb = tauEmbedding.EventCounterMany(datasetsEmb)
eventCounterSig = counter.EventCounter(datasetsSig)
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(
filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(
filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
tdCount = dataset.TreeDraw("dummy",
weight=tauEmbedding.signalNtuple.weightBTagging)
tdCountMET = tdCount.clone(weight=tauEmbedding.signalNtuple.weight,
selection=tauEmbedding.signalNtuple.metCut)
tdCountBTagging = tdCount.clone(
selection=And(tauEmbedding.signalNtuple.metCut,
tauEmbedding.signalNtuple.bTaggingCut))
tdCountDeltaPhi160 = tdCount.clone(selection=And(
tauEmbedding.signalNtuple.metCut, tauEmbedding.signalNtuple.
bTaggingCut, tauEmbedding.signalNtuple.deltaPhi160Cut))
tdCountDeltaPhi130 = tdCount.clone(selection=And(
tauEmbedding.signalNtuple.metCut, tauEmbedding.signalNtuple.
bTaggingCut, tauEmbedding.signalNtuple.deltaPhi130Cut))
def addRow(name, td):
tdEmb = td.clone(tree=analysisEmb + "/tree")
tdSig = td.clone(tree=analysisSig + "/tree")
eventCounterEmb.mainCounterAppendRow(name, tdEmb)
eventCounterSig.getMainCounter().appendRow(name, tdSig)
addRow("JetsForEffs",
tdCount.clone(weight=tauEmbedding.signalNtuple.weight))
addRow("METForEffs", tdCountMET)
addRow("BTagging (SF)", tdCountBTagging)
addRow("DeltaPhi < 160", tdCountDeltaPhi160)
addRow("BTagging (SF) again", tdCountBTagging)
addRow("DeltaPhi < 130", tdCountDeltaPhi130)
table = counter.CounterTable()
col = eventCounterEmb.getMainCounterTable().getColumn(name=datasetName)
table.appendColumn(counter.efficiencyColumn("Embedded eff", col))
col = eventCounterSig.getMainCounterTable().getColumn(name=datasetName)
table.appendColumn(counter.efficiencyColumn("Normal eff", col))
table.keepOnlyRows([
"btagging", "METForEffs", "BTagging (SF)", "DeltaPhi < 160",
"DeltaPhi < 130"
])
row = table.getRow(name="btagging")
table.removeRow(name="btagging")
table.insertRow(1, row)
table.renameRows({
"METForEffs": "MET > 50",
"btagging": "b tagging",
"BTagging (SF)": "b tagging with SF (w.r.t MET)",
"DeltaPhi < 130": "DeltaPhi < 130 (w.r.t. btagSF)"
})
effFormat = counter.TableFormatText(
counter.CellFormatTeX(valueFormat='%.4f', withPrecision=2))
# print table.format(effFormat)
fname = "counters_selections_%s.txt" % datasetName
f = open(fname, "w")
f.write(table.format(effFormat))
f.close()
print "Printed selection counters to", fname
def doTauCounters(datasetsEmb, datasetsSig, datasetName):
lumi = datasetsEmb.getLuminosity()
treeDraw = dataset.TreeDraw(
"dummy", weight=tauEmbedding.tauNtuple.weight[tauEmbedding.era])
eventCounterEmb = tauEmbedding.EventCounterMany(datasetsEmb)
eventCounterSig = counter.EventCounter(datasetsSig)
def isNotThis(name):
return name != datasetName
eventCounterEmb.removeColumns(
filter(isNotThis, datasetsEmb.getAllDatasetNames()))
eventCounterSig.removeColumns(
filter(isNotThis, datasetsSig.getAllDatasetNames()))
eventCounterSig.normalizeMCToLuminosity(lumi)
effFormat = counter.TableFormatLaTeX(
counter.CellFormatTeX(valueFormat="%.4f", withPrecision=2))
tdEmb = treeDraw.clone(tree=tauAnalysisEmb + "/tree")
tdSig = treeDraw.clone(tree=tauAnalysisSig + "/tree")
selectionsCumulative = []
tauSelectionsCumulative = []
rowNames = []
def sel(name, selection):
selectionsCumulative.append(selection)
sel = selectionsCumulative[:]
if len(tauSelectionsCumulative) > 0:
sel += ["Sum$(%s) >= 1" % "&&".join(tauSelectionsCumulative)]
sel = "&&".join(sel)
eventCounterEmb.mainCounterAppendRow(name, tdEmb.clone(selection=sel))
eventCounterSig.getMainCounter().appendRow(name,
tdSig.clone(selection=sel))
rowNames.append(name)
def tauSel(name, selection):
tauSelectionsCumulative.append(selection)
sel = selectionsCumulative[:]
if len(tauSelectionsCumulative) > 0:
sel += ["Sum$(%s) >= 1" % "&&".join(tauSelectionsCumulative)]
sel = "&&".join(sel)
eventCounterEmb.mainCounterAppendRow(name, tdEmb.clone(selection=sel))
eventCounterSig.getMainCounter().appendRow(name,
tdSig.clone(selection=sel))
rowNames.append(name)
sel(">= 1 tau candidate", "Length$(taus_p4) >= 1")
tauSel("Decay mode finding", tauEmbedding.tauNtuple.decayModeFinding)
tauSel("pT > 15", "taus_p4.Pt() > 15")
tauSel("pT > 40", tauEmbedding.tauNtuple.tauPtCut)
tauSel("eta < 2.1", tauEmbedding.tauNtuple.tauEtaCut)
tauSel("leading track pT > 20", tauEmbedding.tauNtuple.tauLeadPt)
tauSel("ECAL fiducial", tauEmbedding.tauNtuple.ecalFiducial)
tauSel("againstElectron", tauEmbedding.tauNtuple.electronRejection)
tauSel("againstMuon", tauEmbedding.tauNtuple.muonRejection)
tauSel("isolation", tauEmbedding.tauNtuple.tightIsolation)
tauSel("oneProng", tauEmbedding.tauNtuple.oneProng)
tauSel("Rtau", tauEmbedding.tauNtuple.rtau)
sel("MET", tauEmbedding.tauNtuple.metSelection)
table = counter.CounterTable()
col = eventCounterEmb.getMainCounterTable().getColumn(name=datasetName)
table.appendColumn(counter.efficiencyColumn("Embedded eff", col))
col = eventCounterSig.getMainCounterTable().getColumn(name=datasetName)
table.appendColumn(counter.efficiencyColumn("Normal eff", col))
embeddingMuonIsolationEff = table.getCount(
rowName="tauEmbeddingMuonsCount", colName="Embedded eff")
embeddingTauIsolationEff = table.getCount(rowName="isolation",
colName="Embedded eff")
embeddingTotalIsolationEff = embeddingMuonIsolationEff.clone()
embeddingTotalIsolationEff.multiply(embeddingTauIsolationEff)
# Remove unnecessary rows
del rowNames[0]
table.keepOnlyRows(rowNames)
rowIndex = table.getRowNames().index("isolation")
table.insertRow(
rowIndex,
counter.CounterRow("Mu isolation (emb)",
["Embedded eff", "Normal eff"],
[embeddingMuonIsolationEff, None]))
table.insertRow(
rowIndex + 1,
counter.CounterRow("Tau isolation (emb)",
["Embedded eff", "Normal eff"],
[embeddingTauIsolationEff, None]))
table.setCount2(embeddingTotalIsolationEff,
rowName="isolation",
colName="Embedded eff")
table.setCount2(None, rowName="pT > 15", colName="Normal eff")
#print table.format(effFormat)
fname = "counters_tau_" + datasetName + ".txt"
f = open(fname, "w")
f.write(table.format(effFormat))
f.write("\n")
f.close()
print "Printed tau counters to", fname