def main():
dirEmbs = ["."] + [os.path.join("..", d) for d in result.dirEmbs[1:]]
dirSig = "../"+result.dirSig
datasetsEmb = result.DatasetsMany(dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(datasetsSig)
datasetsEmb.remove(filter(lambda name: "HplusTB" in name, datasetsEmb.getAllDatasetNames()))
def addSignal(datasetMgr):
xsect.setHplusCrossSectionsToBR(datasetMgr, br_tH=0.03, br_Htaunu=1) # agreed to use 3 % as with QCD
plots.mergeWHandHH(datasetMgr)
ttjets2 = datasetMgr.getDataset("TTJets").deepCopy()
ttjets2.setName("TTJets2")
ttjets2.setCrossSection(ttjets2.getCrossSection() - datasetMgr.getDataset("TTToHplus_M120").getCrossSection())
datasetMgr.append(ttjets2)
datasetMgr.merge("EWKnoTT", ["WJets", "DYJetsToLL", "SingleTop", "Diboson"], keepSources=True)
datasetMgr.merge("EWKScaled", ["EWKnoTT", "TTJets2"])
# for mass in [80, 100]:
for mass in [80, 90, 100, 120, 140, 150, 155, 160]:
datasetMgr.merge("EWKSignal_M%d"%mass, ["TTToHplus_M%d"%mass, "EWKScaled"], keepSources=True)
datasetsEmb.forEach(addSignal)
tauEmbedding.normalize=True
tauEmbedding.era = "Run2011A"
doCounters(datasetsEmb)
def main():
datasetsEmb = result.DatasetsMany(tauPlotMany.dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(datasetsSig)
def mergeEWK(datasets):
datasets.merge("EWKMC", ["WJets", "TTJets"], keepSources=True)
#datasets.merge("EWKMC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"], keepSources=True)
mergeEWK(datasetsSig)
datasetsEmb.forEach(mergeEWK)
plots._legendLabels["EWKMC"] = "EWK"
style = tdrstyle.TDRStyle()
histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
tauEmbedding.normalize = True
tauEmbedding.era = "Run2011A"
def dop(datasetName):
doPlots(datasetsEmb, datasetsSig, datasetName)
# doCounters(datasetsEmb, datasetsSig, datasetName)
print "%s done" % datasetName
dop("TTJets")
dop("WJets")
dop("DYJetsToLL")
dop("SingleTop")
dop("Diboson")
dop("EWKMC")
def main():
# muonDir = "../multicrab_muonDebugAnalysisAod_130503_112555"
# muonDir = "../multicrab_muonDebugAnalysisAod_pt41_130506_124929"
muonDir = "../multicrab_muonDebugAnalysisAod_pt41_muscle_pu_130506_163909"
tauDir = "."
if jetSelection:
muonDir = "../multicrab_muonAnalysis_GenMuonDebug_130506_155845"
args = {"analysisName": "debugAnalyzer", "dataEra": "Run2011A"}
muArgs = {}
muArgs.update(args)
#muArgs["analysisName"] = "debugAnalyzerMuscle"
muonDatasets = dataset.getDatasetsFromMulticrabCfg(directory=muonDir,
weightedCounters=False,
**muArgs)
tauDatasets = dataset.getDatasetsFromMulticrabCfg(directory=tauDir,
weightedCounters=False,
**args)
plots.mergeRenameReorderForDataMC(muonDatasets)
plots.mergeRenameReorderForDataMC(tauDatasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.82, x2=0.93)
doPlots(muonDatasets.getDataset("TTJets"),
tauDatasets.getDataset("TTJets"))
doCounters(muonDatasets, tauDatasets, "TTJets")
def refinedDataSets(dirs, dataEra, searchMode, analysis, optMode, removeTTJets):
datasets = dataset.getDatasetsFromMulticrabDirs(dirs,dataEra=dataEra, searchMode=searchMode, analysisName=analysis, optimizationMode=optMode)
datasets.updateNAllEventsToPUWeighted()
datasets.loadLuminosities()
datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "Hplus_taunu_t-channel" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "Hplus_taunu_tW-channel" in name, datasets.getAllDatasetNames()))
if removeTTJets:
datasets.remove(filter(lambda name: "TTJets_SemiLept" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "TTJets_FullLept" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "TTJets_Hadronic" in name, datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
datasets.merge("EWK", [
"TTJets",
"WJets",
"DYJetsToLL",
"SingleTop",
"Diboson"
])
return datasets
def main():
# muonDir = "../multicrab_muonDebugAnalysisAod_130503_112555"
# muonDir = "../multicrab_muonDebugAnalysisAod_pt41_130506_124929"
muonDir = "../multicrab_muonDebugAnalysisAod_pt41_muscle_pu_130506_163909"
tauDir = "."
if jetSelection:
muonDir = "../multicrab_muonAnalysis_GenMuonDebug_130506_155845"
args = {
"analysisName": "debugAnalyzer",
"dataEra": "Run2011A"
}
muArgs = {}
muArgs.update(args)
#muArgs["analysisName"] = "debugAnalyzerMuscle"
muonDatasets = dataset.getDatasetsFromMulticrabCfg(directory=muonDir, weightedCounters=False, **muArgs)
tauDatasets = dataset.getDatasetsFromMulticrabCfg(directory=tauDir, weightedCounters=False, **args)
plots.mergeRenameReorderForDataMC(muonDatasets)
plots.mergeRenameReorderForDataMC(tauDatasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.82, x2=0.93)
doPlots(muonDatasets.getDataset("TTJets"), tauDatasets.getDataset("TTJets"))
doCounters(muonDatasets, tauDatasets, "TTJets")
def doDataset(datasetsEmb, datasetsSig, optMode):
global ind
ind = 0
# datasetsEmb.loadLuminosities() # not needed for pseudo-multicrab
datasetsEmb.updateNAllEventsToPUWeighted()
datasetsSig.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(datasetsEmb)
plots.mergeRenameReorderForDataMC(datasetsSig)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
#histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
histograms.createLegend.moveDefaults(dx=-0.15, dh=-0.2)
#histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
#histograms.uncertaintyMode.set(histograms.uncertaintyMode.SystOnly)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatPlusSyst)
histograms.createLegendRatio.moveDefaults(dh=-0.1, dx=-0.53)
plots._legendLabels["BackgroundStatError"] = "Truth stat. unc."
plots._legendLabels["BackgroundStatSystError"] = "Truth stat. unc."
plots._plotStyles["BackgroundStatSystError"] = plots._plotStyles["BackgroundStatError"]
plotter = tauEmbedding.CommonPlotter(optMode, "mcembwtaumu", drawPlotCommon)
def dop(name, addData=False, **kwargs):
doPlots(datasetsEmb, datasetsSig, name, plotter, optMode, addData, **kwargs)
# doCounters(datasetsEmb, datasetsSig, name)
dop("TTJets")
def manageDatasets(datasets):
'''
def manageDatasets(datasets):
Handles the PU weighting, luminosity loading and signal merging of the datatasets.
'''
### Since (by default) we use weighted counters, and the analysis job inputs are
### normally skims (as are "v44_4" and "v53_1"), need to update events to PU weighted
print "\n*** Updating events to PU weighted:"
datasets.updateNAllEventsToPUWeighted()
if bMcOnly:
datasets.remove(datasets.getDataDatasetNames())
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
else:
datasets.loadLuminosities()
print "\n*** Default merging of dataset components:"
plots.mergeRenameReorderForDataMC(datasets)
print "\n*** Removing all signal samples, except m=%s" % (signalMass)
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M"+signalMass in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
### Setup style
styleGenerator = styles.generator(fill=False)
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.02, dy=+0.00)
print "*** Setting signal cross sections, using BR(t->bH+)=%s and BR(H+ -> tau+ nu)=%s" % (BR_tH, BR_Htaunu)
xsect.setHplusCrossSectionsToBR(datasets, BR_tH, BR_Htaunu)
print "*** Merging WH and HH signals"
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
return datasets
def main():
datasetsEmb = dataset.getDatasetsFromMulticrabCfg(
cfgfile=dirEmb + "/multicrab.cfg", counters=analysisEmb + "Counters")
datasetsSig = dataset.getDatasetsFromMulticrabCfg(
cfgfile=dirSig + "/multicrab.cfg", counters=analysisSig + "Counters")
datasetsEmb.updateNAllEventsToPUWeighted()
datasetsSig.updateNAllEventsToPUWeighted()
datasetsEmb.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasetsEmb)
plots.mergeRenameReorderForDataMC(datasetsSig)
style = tdrstyle.TDRStyle()
histograms.createLegend.setDefaults(y1=0.9, y2=0.75, x1=0.6, x2=0.95)
tauEmbedding.normalize = False
tauEmbedding.era = "Run2011A"
# doPlots(datasetsEmb, datasetsSig, "TTJets")
# doPlots(datasetsEmb, datasetsSig, "WJets")
# doCounters(datasetsEmb, datasetsSig, "TTJets")
# doCounters(datasetsEmb, datasetsSig, "WJets")
# doCounters(datasetsEmb, datasetsSig, "DYJetsToLL")
# doCounters(datasetsEmb, datasetsSig, "SingleTop")
doCounters(datasetsEmb, datasetsSig, "Diboson")
def main():
# Read the datasets
datasets = dataset.getDatasetsFromMulticrabCfg(counters=analysis+"Counters", weightedCounters=(dataEra!=""))
if dataEra != "":
datasets.updateNAllEventsToPUWeighted(era=dataEra)
datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
# Remove signal
datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames()))
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.04)
plots._legendLabels["QCD_Pt20_MuEnriched"] = "QCD"
#datasets.remove(["QCD_Pt20_MuEnriched"])
#histograms.createLegend.moveDefaults(dh=-0.05)
selectorArgs = [tauEmbedding.tauNtuple.weight[dataEra]]
ntupleCache = dataset.NtupleCache(analysis+"/tree", "TauAnalysisSelector",
selectorArgs=selectorArgs+[True],
process=False,
#maxEvents=100,
cacheFileName="histogramCacheTauEmb.root"
)
# doPlots(datasets)
doCounters(datasets, ntupleCache)
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
# datasets.loadLuminosities()
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets)
style = tdrstyle.TDRStyle()
td = dataset.TreeDraw(analysis+"/tree", weight="weightPileup*weightTrigger*weightPrescale",
selection="genMet_p4.Et() > 20"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 1"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 2"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 3"
)
kwargs = {}
kwargs["normalizeToLumi"] = 1150
dist=">>dist(25,0,5)"
for q in ["Et", "X", "Y", "Phi"]:
rawRes = plots.DataMCPlot(datasets, td.clone(varexp="met_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), **kwargs)
type1Res = plots.DataMCPlot(datasets, td.clone(varexp="metType1_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), **kwargs)
#type1Res = plots.DataMCPlot(datasets, td.clone(varexp="tcMet_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), normalizeToLumi=1150)
compare(rawRes, type1Res, q, "TTJets")
def main():
# Datasets
datasetsEmbedding = dataset.getDatasetsFromMulticrabCfg(cfgfile=embeddingDir+"/multicrab.cfg", counters=None)
datasetsTau = dataset.getDatasetsFromMulticrabCfg(cfgfile=tauDir+"/multicrab.cfg", counters=None)
datasetsEmbedding.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasetsEmbedding)
plots.mergeRenameReorderForDataMC(datasetsTau)
if embeddingData:
datasetsEmbedding.selectAndReorder(["Data"])
else:
datasetsEmbedding.selectAndReorder([mcSample])
datasetsTau.selectAndReorder([mcSample])
# Style
style = tdrstyle.TDRStyle()
def createMuonTauPlot(nameMuon, nameTau):
return MuonTauPlot(datasetsEmbedding, datasetsTau, embeddingAnalysis, tauAnalysis, nameMuon, nameTau)
def createTauPlot(nameTau):
return TauPlot(datasetsEmbedding, datasetsTau, embeddingAnalysis, tauAnalysis, nameTau)
# Plots
plotPt(createMuonTauPlot("Muon_Pt", "GenTau_Pt"), opts={"xmin":30, "ymin":5e-4})
plotPt(createTauPlot("Tau_Pt"))
plotEta(createMuonTauPlot("Muon_Eta", "GenTau_Eta"), opts={"xmin":-2.1, "xmax": 2.1})
plotEta(createTauPlot("Tau_Eta"), opts={"xmin":-2.4, "xmax":2.4})
plotPhi(createMuonTauPlot("Muon_Phi", "GenTau_Phi"))
plotPhi(createTauPlot("Tau_Phi"))
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.updateNAllEventsToPUWeighted()
datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
print "Int.Lumi",datasets.getDataset("Data").getLuminosity()
# datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
# datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
style = tdrstyle.TDRStyle()
# datasets3 = dataset.getDatasetsFromMulticrabCfg(cfgfile="/home/rkinnune/signalAnalysis/CMSSW_4_4_4/src/HiggsAnalysis/HeavyChHiggsToTauNu/test/multicrab_120607_075512/multicrab.cfg", counters=counters)
# datasets3.updateNAllEventsToPUWeighted()
# datasets3.loadLuminosities()
# plots.mergeRenameReorderForDataMC(datasets3)
# datasets2.selectAndReorder(["TTJets_TuneZ2_Fall11","TTToHplusBWB_M120_Fall11"])
# datasets2.rename("TTJets_TuneZ2_Fall11","TTJets2")
# datasets2.rename("TTToHplusBWB_M120_Fall11","TTToHplusBWB_M120_2")
# datasets.extend(datasets2)
# plot(datasets, datasets2, datasets3)
plot(datasets)
printCounters(datasets)
def main():
# Create all datasets from a multicrab task
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
# Read integrated luminosities of data datasets from lumi.json
datasets.loadLuminosities()
# Include only 120 mass bin of HW and HH datasets
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
# Default merging nad ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
# Set BR(t->H) to 0.2, keep BR(H->tau) in 1
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Merge WH and HH datasets to one (for each mass bin)
# TTToHplusBWB_MXXX and TTToHplusBHminusB_MXXX to "TTToHplus_MXXX"
plots.mergeWHandHH(datasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
dataMCExample(datasets)
distComparison(datasets)
# Script execution can be paused like this, it will continue after
# user has given some input (which must include enter)
if drawToScreen:
raw_input("Hit enter to continue")
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters,
dataEra=dataEra)
datasets.updateNAllEventsToPUWeighted()
datasets.loadLuminosities()
# datasets.getDataset("HplusTB_M180_Fall11").setCrossSection(0.363)
# datasets.getDataset("HplusTB_M190_Fall11").setCrossSection(0.2666)
datasets.getDataset("HplusTB_M200_Fall11").setCrossSection(0.1915)
# datasets.getDataset("HplusTB_M250_Fall11").setCrossSection(0.051)
# datasets.getDataset("HplusTB_M300_Fall11").setCrossSection(0.0213)
plots.mergeRenameReorderForDataMC(datasets)
print "Int.Lumi", datasets.getDataset("Data").getLuminosity()
# datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
# datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
style = tdrstyle.TDRStyle()
# datasets3 = dataset.getDatasetsFromMulticrabCfg(cfgfile="/home/rkinnune/signalAnalysis/CMSSW_4_4_4/src/HiggsAnalysis/HeavyChHiggsToTauNu/test/multicrab_120607_075512/multicrab.cfg", counters=counters)
# datasets3.updateNAllEventsToPUWeighted()
# datasets3.loadLuminosities()
# plots.mergeRenameReorderForDataMC(datasets3)
# datasets2.selectAndReorder(["TTJets_TuneZ2_Fall11","TTToHplusBWB_M120_Fall11"])
# datasets2.rename("TTJets_TuneZ2_Fall11","TTJets2")
# datasets2.rename("TTToHplusBWB_M120_Fall11","TTToHplusBWB_M120_2")
# datasets.extend(datasets2)
# plot(datasets, datasets2, datasets3)
plot(datasets)
printCounters(datasets)
def doSystematicsVariation(myMulticrabDir,era,searchMode,optimizationMode,syst,myOutputCreator,myShapeString):
myModuleInfoString = "%s_%s_%s_%s"%(era, searchMode, optimizationMode,syst)
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=myMulticrabDir)
systDsetMgr = dsetMgrCreator.createDatasetManager(dataEra=era,searchMode=searchMode,optimizationMode=optimizationMode,systematicVariation=syst)
# Do the usual normalisation
systDsetMgr.updateNAllEventsToPUWeighted()
systDsetMgr.loadLuminosities()
plots.mergeRenameReorderForDataMC(systDsetMgr)
systDsetMgr.merge("EWK", ["TTJets","WJets","DYJetsToLL","SingleTop","Diboson"])
myLuminosity = systDsetMgr.getDataset("Data").getLuminosity()
# Obtain results
mySystModuleResults = PseudoMultiCrabModule(systDsetMgr, era, searchMode, optimizationMode, syst)
mySystResult = None
if massType == "mt":
mySystResult = QCDFactorisedResultManager(myMtSpecs,systDsetMgr,myLuminosity,myModuleInfoString,shapeOnly=False)
elif massType == "invmass":
mySystResult = QCDFactorisedResultManager(myFullMassSpecs,systDsetMgr,myLuminosity,myModuleInfoString,shapeOnly=False)
mySystModuleResults.addShape(mySystResult.getShape(), myShapeString)
mySystModuleResults.addShape(mySystResult.getShapeMCEWK(), myShapeString+"_MCEWK")
mySystModuleResults.addShape(mySystResult.getShapePurity(), myShapeString+"_Purity")
mySystModuleResults.addDataDrivenControlPlots(mySystResult.getControlPlots(),mySystResult.getControlPlotLabels())
mySystResult.delete()
## Save module info
myOutputCreator.addModule(mySystModuleResults)
systDsetMgr.close()
dsetMgrCreator.close()
ROOT.gROOT.CloseFiles()
ROOT.gROOT.GetListOfCanvases().Delete()
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(
counters=tauAnalysisEmb + "Counters", weightedCounters=(dataEra != ""))
if dataEra != "":
datasets.updateNAllEventsToPUWeighted(era=dataEra)
plots.mergeRenameReorderForDataMC(datasets)
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
isolations = [
("Standard", "standard"),
("TauLike", "taulike"),
("ChargedHadrRel10", "chargedHadrRel10"),
("ChargedHadrRel15", "chargedHadrRel15"),
]
for name, isolation in isolations:
ntupleCache = dataset.NtupleCache(
tauAnalysisEmb + "/tree",
"EmbeddingMuonIsolationSelector",
selectorArgs=[tauEmbedding.tauNtuple.weight[dataEra], isolation],
cacheFileName="histogramCache-%s.root" % name,
#maxEvents=100,
#process=False,
)
for datasetName in ["TTJets"]:
doPlots(datasets, datasetName, name, ntupleCache)
doCounters(datasets, datasetName, name, ntupleCache)
def main():
tauDirEmbs = ["."] + [os.path.join("..", d) for d in tauEmbedding.tauDirEmbs[1:]]
tauDirSig = "../"+tauEmbedding.tauDirSig
datasetsEmb = tauEmbedding.DatasetsMany(tauDirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=tauDirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsSig.updateNAllEventsToPUWeighted()
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
#datasetsEmb.setLumiFromData()
datasetsEmb.lumi = 5049
plots.mergeRenameReorderForDataMC(datasetsSig)
def mergeEWK(datasets):
datasets.merge("EWKMC", ["WJets", "TTJets"], keepSources=True)
#datasets.merge("EWKMC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"], keepSources=True)
#mergeEWK(datasetsSig)
#datasetsEmb.forEach(mergeEWK)
#plots._legendLabels["EWKMC"] = "EWK"
style = tdrstyle.TDRStyle()
histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
tauEmbedding.normalize = True
tauEmbedding.era = "Run2011A"
def dop(datasetName):
# doPlots(datasetsEmb, datasetsSig, datasetName)
doCounters(datasetsEmb, datasetsSig, datasetName)
print "%s done" % datasetName
dop("TTJets")
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
# datasets.loadLuminosities()
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
datasets.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets)
style = tdrstyle.TDRStyle()
td = dataset.TreeDraw(analysis+"/tree", weight="weightPileup*weightTrigger*weightPrescale",
selection="genMet_p4.Et() > 20"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 1"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 2"
# selection="genMet_p4.Et() > 20 && [email protected]() >= 3"
)
kwargs = {}
kwargs["normalizeToLumi"] = 1150
dist=">>dist(25,0,5)"
for q in ["Et", "X", "Y", "Phi"]:
rawRes = plots.DataMCPlot(datasets, td.clone(varexp="met_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), **kwargs)
type1Res = plots.DataMCPlot(datasets, td.clone(varexp="metType1_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), **kwargs)
#type1Res = plots.DataMCPlot(datasets, td.clone(varexp="tcMet_p4.%s()/genMet_p4.%s() %s" % (q, q, dist)), normalizeToLumi=1150)
compare(rawRes, type1Res, q, "TTJets")
def main(opts,signalDsetCreator,era,searchMode,optimizationMode):
# Make directory for output
mySuffix = "btagEfficiency_%s_%s_%s_%s"%(opts.dset,era,searchMode,optimizationMode)
if os.path.exists(mySuffix):
shutil.rmtree(mySuffix)
os.mkdir(mySuffix)
# Create dataset manager
myDsetMgr = signalDsetCreator.createDatasetManager(dataEra=era,searchMode=searchMode,optimizationMode=optimizationMode)
# Set as luminosity 1 fb (since one looks only at MC)
myLuminosity = 1000.0
# Do merges
style = tdrstyle.TDRStyle()
myDsetMgr.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(myDsetMgr)
# Set defaults for histograms
histograms.createLegend.moveDefaults(dx=-0.05)
histograms.createSignalText.set(xmin=0.4, ymax=0.93, mass=120)
# Show info of available datasets
myDsetMgr.printDatasetTree()
# Create plots
#distributionPtEta(opts, myDsetMgr, myLuminosity, mySuffix) # FIXME: don't think this is used anymore
efficiencyplot(opts, myDsetMgr, myLuminosity, mySuffix) # Tested and works
print HighlightStyle()+"\nResults saved to directory: %s%s"%(mySuffix,NormalStyle())
def main():
dirEmbs = ["."] + [os.path.join("..", d) for d in tauEmbedding.dirEmbs[1:]]
dirSig = "../"+tauEmbedding.dirSig
datasetsEmb = tauEmbedding.DatasetsMany(dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsSig.updateNAllEventsToPUWeighted()
del plots._datasetMerge["WW"]
# del plots._datasetMerge["WZ"]
# del plots._datasetMerge["ZZ"]
datasetsEmb.forEach(lambda mgr: plots.mergeRenameReorderForDataMC(mgr, keepSourcesMC=True))
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(datasetsSig, keepSourcesMC=True)
def mergeEWK(datasets):
datasets.merge("EWKMC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson", "WW"], keepSources=True)
#datasets.merge("EWKMC", ["WJets", "TTJets"], keepSources=True)
mergeEWK(datasetsSig)
datasetsEmb.forEach(mergeEWK)
plots._legendLabels["EWKMC"] = "EWK"
datasetsEmb.remove(filter(lambda name: "TTToHplus" in name, datasetsEmb.getAllDatasetNames()))
datasetsEmb.remove(filter(lambda name: "HplusTB" in name, datasetsEmb.getAllDatasetNames()))
style = tdrstyle.TDRStyle()
ROOT.gStyle.SetEndErrorSize(5)
histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
tauEmbedding.normalize=True
tauEmbedding.era = "Run2011A"
#datasetsEmbCorrected = tauEmbedding.DatasetsDYCorrection(datasetsEmb, datasetsSig, analysisEmb, analysisSig)
datasetsEmbCorrected = tauEmbedding.DatasetsResidual(datasetsEmb, datasetsSig, analysisEmb, analysisSig, ["DYJetsToLL", "WW"], totalNames=["Data", "EWKMC"])
def dop(datasetName):
doPlots(datasetsEmb, datasetsSig, datasetName)
# doCounters(datasetsEmb, datasetsSig, datasetName)
print "%s done" % datasetName
#doPlots(datasetsEmbCorrected, datasetsSig, "EWKMC", addData=True, postfix="_residual")
doCounters(datasetsEmb, datasetsSig, "EWKMC")
return
dop("TTJets")
dop("WJets")
#dop("W3Jets")
dop("DYJetsToLL")
dop("SingleTop")
dop("Diboson")
return
dop("WW")
dop("WZ")
dop("ZZ")
#doPlots(datasetsEmb, datasetsSig, "EWKMC", doData=True, postfix="_data")
##doPlots(datasetsEmb, datasetsSig, "Data")
doPlots(datasetsEmbCorrected, datasetsSig, "EWKMC", postfix="_dycorrected")
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.loadLuminosities()
datasets.remove(
filter(lambda name: "TTToHplus" in name and not "M120" in name,
datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets)
style = tdrstyle.TDRStyle()
plot = plots.DataMCPlot(datasets, analysis + "/MET/met")
plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(10))
plot.createFrame("MET", opts={"ymin": 1e-4, "ymaxfactor": 10})
plot.getPad().SetLogy(True)
plot.setLegend(histograms.createLegend())
plot.frame.GetXaxis().SetTitle("MET (GeV)")
plot.frame.GetYaxis().SetTitle("Number of events")
plot.draw()
plot.addLuminosityText()
plot.save()
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.loadLuminosities()
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets)
style = tdrstyle.TDRStyle()
plot = plots.DataMCPlot(datasets, analysis+"/MET/met")
plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(10))
plot.createFrame("MET", opts={"ymin": 1e-4, "ymaxfactor": 10})
plot.getPad().SetLogy(True)
plot.setLegend(histograms.createLegend())
plot.frame.GetXaxis().SetTitle("MET (GeV)")
plot.frame.GetYaxis().SetTitle("Number of events")
plot.draw()
plot.addLuminosityText()
plot.save()
def doSystematicsVariation(myMulticrabDir,era,searchMode,optimizationMode,syst,myOutputCreator,myShapeString,myNormFactors):
myModuleInfoString = "%s_%s_%s_%s"%(era, searchMode, optimizationMode,syst)
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=myMulticrabDir)
systDsetMgr = dsetMgrCreator.createDatasetManager(dataEra=era,searchMode=searchMode,optimizationMode=optimizationMode,systematicVariation=syst)
# Do the usual normalisation
systDsetMgr.updateNAllEventsToPUWeighted()
systDsetMgr.loadLuminosities()
plots.mergeRenameReorderForDataMC(systDsetMgr)
systDsetMgr.merge("EWK", ["TTJets","WJets","DYJetsToLL","SingleTop","Diboson"])
myLuminosity = systDsetMgr.getDataset("Data").getLuminosity()
# Obtain results
mySystModuleResults = pseudoMultiCrabCreator.PseudoMultiCrabModule(systDsetMgr, era, searchMode, optimizationMode, syst)
mySystResult = qcdInvertedResult.QCDInvertedResultManager(myShapeString, "AfterCollinearCuts", systDsetMgr, myLuminosity, myModuleInfoString, myNormFactors, shapeOnly=False, displayPurityBreakdown=False, noRebin=True)
mySystModuleResults.addShape(mySystResult.getShape(), myShapeString)
mySystModuleResults.addShape(mySystResult.getShapeMCEWK(), myShapeString+"_MCEWK")
mySystModuleResults.addShape(mySystResult.getShapePurity(), myShapeString+"_Purity")
mySystModuleResults.addDataDrivenControlPlots(mySystResult.getControlPlots(),mySystResult.getControlPlotLabels())
mySystResult.delete()
## Save module info
myOutputCreator.addModule(mySystModuleResults)
systDsetMgr.close()
dsetMgrCreator.close()
ROOT.gROOT.CloseFiles()
ROOT.gROOT.GetListOfCanvases().Delete()
ROOT.gDirectory.GetList().Delete()
def main():
# Read the datasets
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.updateNAllEventsToPUWeighted()
#datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
# Set the signal cross sections to a given BR(t->H), BR(h->taunu)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Set the signal cross sections to a value from MSSM
# xsect.setHplusCrossSectionsToMSSM(datasets, tanbeta=20, mu=200)
plots.mergeWHandHH(
datasets
) # merging of WH and HH signals must be done after setting the cross section
# Create counter
eventCounter = counter.EventCounter(datasets)
#eventCounter.normalizeMCByLuminosity()
eventCounter.normalizeMCToLuminosity(1000) # in pb^-1
print "============================================================"
print "Main counter (MC normalized by collision data luminosity)"
print eventCounter.getMainCounterTable().format()
triggerCounter = eventCounter.getSubCounter("Trigger")
triggerCounter.forEachDataset(printTriggerEfficiency)
def main():
# Read the datasets
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
#datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
# Set the signal cross sections to a given BR(t->H), BR(h->taunu)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Set the signal cross sections to a value from MSSM
# xsect.setHplusCrossSectionsToMSSM(datasets, tanbeta=20, mu=200)
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
# Create counter
eventCounter = counter.EventCounter(datasets)
#eventCounter.normalizeMCByLuminosity()
eventCounter.normalizeMCToLuminosity(1000) # in pb^-1
print "============================================================"
print "Main counter (MC normalized by collision data luminosity)"
print eventCounter.getMainCounterTable().format()
triggerCounter = eventCounter.getSubCounter("Trigger")
triggerCounter.forEachDataset(printTriggerEfficiency)
def main():
# Create all datasets from a multicrab task
datasets = dataset.getDatasetsFromMulticrabCfg(analysisName=analysis)
# As we use weighted counters for MC normalisation, we have to
# update the all event count to a separately defined value because
# the analysis job uses skimmed pattuple as an input
datasets.updateNAllEventsToPUWeighted()
# Read integrated luminosities of data datasets from lumi.json
datasets.loadLuminosities()
# Include only 120 mass bin of HW and HH datasets
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
# Default merging nad ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
# Set BR(t->H) to 0.2, keep BR(H->tau) in 1
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Merge WH and HH datasets to one (for each mass bin)
# TTToHplusBWB_MXXX and TTToHplusBHminusB_MXXX to "TTToHplus_MXXX"
plots.mergeWHandHH(datasets)
# Merge EWK datasets
datasets.merge("EWK", [
"WJets",
"TTJets",
"DYJetsToLL",
"SingleTop",
"Diboson"
])
# Apply TDR style
style = tdrstyle.TDRStyle()
# Create the normalized plot of transverse mass
# Read the histogram from the file
#mT = plots.DataMCPlot(datasets, "transverseMass")
# Create the histogram from the tree (and see the selections explicitly)
td = dataset.TreeDraw("tree", weight="weightPileup*weightTrigger*weightPrescale",
selection="met_p4.Et() > 70 && Max$(jets_btag) > 1.7")
mT = plots.DataMCPlot(datasets, td.clone(varexp="sqrt(2 * tau_p4.Pt() * met_p4.Et() * (1-cos(tau_p4.Phi()-met_p4.Phi())))>>dist(400, 0, 400)"))
# Rebin before subtracting
mT.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
# Create the data-EWK histogram and draw it
dataEwkDiff(mT)
# Draw the mT distribution
transverseMass(mT)
def main():
# Read the datasets
# Take only TT+W from signal analysis, and data from embedding+signal analysis
datasetsEmbSig = dataset.getDatasetsFromMulticrabCfg(
cfgfile=embeddingSignalAnalysis + "/multicrab.cfg", counters=counters)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=signalAnalysis +
"/multicrab.cfg",
counters=counters)
# Select only data from embedded
datasetsEmbSig.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasetsEmbSig)
if useData:
datasetsEmbSig.selectAndReorder(datasetsEmbSig.getDataDatasetNames())
else:
mcNames = filter(lambda name: "TTToHplus" not in name,
datasetsEmbSig.getMCDatasetNames())
print "Merging MC"
print " " + "\n ".join(mcNames)
datasetsEmbSig.merge("MC", mcNames)
datasetsEmbSig.selectAndReorder(["Data", "MC"])
# Select only data from original
datasetsSig.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasetsSig)
sigLumi = datasetsSig.getDataset("Data").getLuminosity()
if useData:
datasetsSig.selectAndReorder(datasetsSig.getDataDatasetNames())
else:
datasetsSig.remove(["WW_TuneZ2", "WZ_TuneZ2", "ZZ_TuneZ2"])
mcNames = filter(lambda name: "TTToHplus" not in name,
datasetsSig.getMCDatasetNames())
print "Merging MC"
print " " + "\n ".join(mcNames)
datasetsSig.merge("MC", mcNames)
datasetsSig.selectAndReorder(["Data", "MC"])
print "Embedding luminosity %f" % datasetsEmbSig.getDataset(
"Data").getLuminosity()
print "Normal luminosity %f" % datasetsSig.getDataset(
"Data").getLuminosity()
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.setDefaults(y1=0.7)
# Wrapper to decrease typing and have the common options
def createPlot(plot, *args):
kwargs = {}
kwargs["saveFormats"] = [".png"]
return Plot(datasetsEmbSig, datasetsSig, analysis + "/" + plot, *args,
**kwargs)
transverseMass(createPlot("transverseMass"), rebin=20)
print "============================================================"
print "Main counter"
print getMainCounterTable(datasetsEmbSig, datasetsSig).format()
def main(argv):
interactive = True
interactive = False
# HISTONAME = "TauIdJets"
# HISTONAME = "TauIdBtag"
HISTONAME = "TauIdBveto"
dirs = []
if len(sys.argv) < 2:
usage()
dirs.append(sys.argv[1])
# Disable batch mode here to have the interactivity (see also the line with 'raw_input') below
if interactive:
ROOT.gROOT.SetBatch(False)
# Create all datasets from a multicrab task
# datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
# datasets = dataset.getDatasetsFromMulticrabDirs(dirs,counters=counters, dataEra=dataEra)
datasets = dataset.getDatasetsFromMulticrabDirs(dirs,counters=counters, dataEra=dataEra, analysisbaseName = "signalAnalysisInvertedTau")
# As we use weighted counters for MC normalisation, we have to
# update the all event count to a separately defined value because
# the analysis job uses skimmed pattuple as an input
datasets.updateNAllEventsToPUWeighted()
# Read integrated luminosities of data datasets from lumi.json
datasets.loadLuminosities()
# Include only 120 mass bin of HW and HH datasets
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
# Default merging nad ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
# Set BR(t->H) to 0.2, keep BR(H->tau) in 1
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Merge WH and HH datasets to one (for each mass bin)
# TTToHplusBWB_MXXX and TTToHplusBHminusB_MXXX to "TTToHplus_MXXX"
plots.mergeWHandHH(datasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
#dataMCExample(datasets)
distComparison(datasets)
# Script execution can be paused like this, it will continue after
# user has given some input (which must include enter)
if interactive:
raw_input("Hit enter to continue")
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.updateNAllEventsToPUWeighted()
# remove data datasets
datasets.remove(filter(lambda name: "Tau_" in name, datasets.getAllDatasetNames()))
# remove heavy H+ datasets
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
# Apply TDR style
style = tdrstyle.TDRStyle()
# Define variables and cuts
tauPt = "tau_p4.Pt()"; tauPtCut = tauPt+" > 40"
tauLeadingCandPt = "tau_leadPFChargedHadrCand_p4.Pt()"; tauLeadingCandPtCut = tauLeadingCandPt+" > 20"
met = "met_p4.Et()"; metCut = met+" > 70"
btagMax = "Max$(jets_btag)"; btagCut = btagMax+" > 1.7"
btagJetNum17 = "Sum$(jets_btag > 1.7"
btag2ndMax = "MaxIf(kets_btag, jets_btag < Max$(jets_btag))"
rtau = "tau_leadPFChargedHadrCand_p4.P()/tau_p4.P()"; rtauCut = rtau+" > 0.65"
mt = "sqrt(2 * tau_p4.Pt() * met_p4.Et() * (1-cos(tau_p4.Phi()-met_p4.Phi())))"; mtCut = mt+" > 80"
deltaPhi = "acos((tau_p4.Px()*met_p4.Px()+tau_p4.Py()*met_p4.Py())/tau_p4.Pt()/met_p4.Et())*57.2958"; deltaPhiCut = deltaPhi+" < 160"
npv = "goodPrimaryVertices_n";
td = dataset.TreeDraw(analysis+"/tree", weight="weightPileup*weightTrigger*weightPrescale")
lumi = 1145
def createResult(varexp, selection, weight=None, **kwargs):
args = {"varexp": varexp, "selection": selection}
if weight != None:
args["weight"] = weight
return Result(datasets, td.clone(**args), normalizeToLumi=lumi, **kwargs)
# metRes = createResult(met+">>dist(100,0,200)", btagCut, greaterThan=True)
# metRes.save("met", "MET (GeV)", rebin=10, logy=True, opts={"ymin": 0.01, "ymaxfactor": 10})
# btagRes = createResult(btagMax+">>dist(80, 0, 8)", metCut, greaterThan=True)
# btagRes.save("btag", "TCHE", rebin=5, logy=True, opts={"ymin": 0.01, "ymaxfactor": 10})
# rtauRes = createResult(rtau+">>dist(110,0,1.1)", metCut+"&&"+btagCut, greaterThan=True)
# rtauRes.save("rtau", "R_{#tau}", rebin=10, logy=True, opts={"ymin": 0.01, "ymaxfactor": 10})
# mtRes = createResult(mt+">>dist(50,0,200)", metCut+"&&"+btagCut, greaterThan=True)
# mtRes.save("mt", "M_{T}(#tau, MET) (GeV)", rebin=2, logy=True, opts={"ymin": 0.01, "ymaxfactor": 10})
# deltaPhiRes = createResult(deltaPhi+">>dist(90,0,180)", metCut+"&&"+btagCut, lessThan=True)
# deltaPhiRes.save("deltaPhi", "#Delta#Phi(#tau, MET) (#circ)", rebin=5, logy=True, opts={"ymin": 0.01, "ymaxfactor": 10})
pileupRes = createResult(npv+">>dist(4,1,17)", metCut+"&&"+btagCut, weight="", doPassed=False, lessThan=True)
pileupRes.save("goodPV", "N(good primary vertices)")
def main():
### Get the ROOT files for all datasets, merge datasets and reorder them
print "*** Obtaining ROOT files from:\n %s" % (multicrabPath)
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabPath, dataEra="Run2011A")
printPSet(bPrintPSet, folderName="signalAnalysisRun2011A")
print "*** Calling datasets.updateNAllEventsToPUWeighted():"
datasets.updateNAllEventsToPUWeighted()
print "*** Loading luminosities"
datasets.loadLuminosities()
print "*** Calling plots.mergeRenameReorderForDataMC(datasets):"
plots.mergeRenameReorderForDataMC(datasets)
if mcOnly:
datasets.remove(datasets.getDataDatasetNames())
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
### Merge desirable datasets
if bMergeEwk:
print "*** Merging EWK MC"
datasets.merge("EWK MC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"])
plots._plotStyles["EWK MC"] = styles.ttStyle #plots._plotStyles["EWK"] = styles.getEWKStyle()
### Remove signals other than M120
print "*** Removing all signal except M120"
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
### Setup style
print "*** Setting up style"
styleGenerator = styles.generator(fill=True)
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.0, dy=+0.0)
### Merge signals into one histo
print "*** Merging WH and HH signals into one histogram"
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
### Print desirable information here
print "*** Available datasets:\n %s" % (datasets.getAllDatasetNames())
if mcOnly:
print "*** Integrated Luminosity:\n %s (pb)" % (mcOnlyLumi)
else:
print "*** Integrated Luminosity:\n %s (pb)" % (datasets.getDataset("Data").getLuminosity())
### Do all plots defined in histoDict function
doPlots(datasets, histoDict, JetSelectionCuts, SaveExtension = "JetSelection")
doPlots(datasets, histoDict, MtCut, SaveExtension = "Mt")
doPlots(datasets, histoDict, MetBtagDeltaPhiCuts, SaveExtension = "MetBtagDeltaPhi")
doPlots(datasets, histoDict, MetBtagDeltaPhiMtCuts, SaveExtension = "MetBtagDeltaPhiMt")
### Keep session alive (otherwise canvases close automatically)
if bBatchMode == False:
raw_input("*** Press \"any\" key to exit pyROOT: ")
def main():
# Apply TDR style
style = tdrstyle.TDRStyle()
# histograms.cmsTextMode = histograms.CMSMode.NONE
#histograms.uncertaintyMode.set(histograms.Uncertainty.StatOnly)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatAndSyst)
#histograms.createLegend.moveDefaults(dx=-0.15, dh=0.05)#, dh=-0.05) # QCD removed
histograms.createLegend.setDefaults(textSize=0.04)
histograms.createLegend.moveDefaults(dx=-0.25, dh=0.1)#, dh=-0.05) # QCD removed
histograms.createLegendRatio.setDefaults(ncolumns=2, textSize=0.08, columnSeparation=0.3)
histograms.createLegendRatio.moveDefaults(dx=-0.35, dh=-0.1, dw=0.25)
plots._legendLabels["BackgroundStatError"] = "Sim. stat. unc."
plots._legendLabels["BackgroundStatSystError"] = "Sim. stat.#oplussyst. unc."
legendLabelsSet = False
for optMode in [
# "OptQCDTailKillerNoCuts",
"OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
# "OptQCDTailKillerTightPlus",
# None
]:
# Create the dataset objects
datasetsEmb = dataset.getDatasetsFromMulticrabCfg(dataEra=dataEra, optimizationMode=optMode)
# Remove signal and W+3jets datasets
datasetsEmb.remove(filter(lambda name: "HplusTB" in name, datasetsEmb.getAllDatasetNames()))
datasetsEmb.remove(filter(lambda name: "TTToHplus" in name, datasetsEmb.getAllDatasetNames()))
datasetsEmb.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(datasetsEmb)
doCounters(datasetsEmb, optMode)
if not legendLabelsSet:
def trans(n):
if n[0:2] in ["W+", "Z/"]:
return n
else:
return n[0].lower()+n[1:]
for d in datasetsEmb.getAllDatasetNames():
oldName = plots._legendLabels.get(d, d)
plots._legendLabels[d] = "Embedded "+trans(oldName)
legendLabelsSet = True
# Remove QCD for plots
datasetsEmb.remove(["QCD_Pt20_MuEnriched"])
outputDir = optMode
if outputDir is not None:
outputDir += "_embdatamc"
doPlots(datasetsEmb, outputDir)
tauEmbedding.writeToFile(outputDir, "input.txt", "Embedded: %s\n" % os.getcwd())
def doDataset(datasetsSeeds, optMode, labels):
for d in datasetsSeeds:
d.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(d)
plotter = tauEmbedding.CommonPlotter(optMode, "average", drawPlotCommon)
doPlots(datasetsSeeds, labels, "Data", plotter)
doPlots(datasetsSeeds, labels, "TTJets", plotter)
def main():
# Read the datasets
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
# Remove signals other than M120
### datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
### datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
# Set the signal cross sections to a given BR(t->H), BR(h->taunu)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Set the signal cross sections to a value from MSSM
# xsect.setHplusCrossSectionsToMSSM(datasets, tanbeta=20, mu=200)
### plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
eventCounter = counter.EventCounter(datasets, counters=counters)
eventCounter.normalizeMCByCrossSection()
mainTable = eventCounter.getMainCounterTable()
wh = [
"TTToHplusBWB_M80",
# "TTToHplusBWB_M90",
"TTToHplusBWB_M100",
"TTToHplusBWB_M120",
"TTToHplusBWB_M140",
"TTToHplusBWB_M150",
# "TTToHplusBWB_M155",
"TTToHplusBWB_M160",
]
hh = [
"TTToHplusBHminusB_M80",
# "TTToHplusBHminusB_M90",
"TTToHplusBHminusB_M100",
"TTToHplusBHminusB_M120",
"TTToHplusBHminusB_M140",
"TTToHplusBHminusB_M150",
# "TTToHplusBHminusB_M155",
"TTToHplusBHminusB_M160",
]
xvalues = [80,
# 90,
100, 120, 140, 150,
# 155,
160]
doPlots(mainTable, xvalues, wh, "HW", True)
doPlots(mainTable, xvalues, wh, "HW", False)
doPlots(mainTable, xvalues, hh, "HH", True)
doPlots(mainTable, xvalues, hh, "HH", False)
def main():
# Get the ROOT files for all datasets, merge datasets and reorder them
datasets = dataset.getDatasetsFromMulticrabCfg(directory="/Volumes/disk/attikis/HIG-12-037/TreeAnalysis_v44_4_130113_105229/", dataEra="Run2011A")
datasets.updateNAllEventsToPUWeighted()
datasets.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasets)
# Merge desirable datasets
datasets.merge("EWK MC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"])
plots._plotStyles["EWK MC"] = styles.ttStyle #plots._plotStyles["EWK"] = styles.getEWKStyle()
# Remove signals other than M120
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
# Setup style
styleGenerator = styles.generator(fill=True)
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.0, dy=+0.0)
# Merge signals into one histo
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
# Print desirable information here
print "*** Event weight applied: %s" % (EvtWeight)
print "*** Available datasets: %s" % (datasets.getAllDatasetNames())
print "*** WARNING! What about btag scale factor?"
print "*** Integrated Luminosity: %s (pb)" % (datasets.getDataset("Data").getLuminosity())
# Define histogram name, expression, and binning here:
# { hName": "expression >> hNameTmp(nBins, xMin, xMax) }
histoDict1 = {
"sphericity": "sphericity >> sphericity(20, 0.0, 1.0)",
"aplanarity": "aplanarity >> aplanarity(20, 0.0, 0.5)",
"planarity": "planarity >> planarity(20, 0.0, 0.5)",
"circularity": "circularity >> circularity(20, 0.0, 1.0)",
"alphaT": "alphaT >> alphaT(20, 0.0, 1.0)",
"mT": "%s >> mT(30, 0.0, 600.0)" % (Mt)
}
# Do all plots defined in doPlots(datasets) function
# doPlots(datasets, histoDict1, "", SaveExtension = "JetSelection")
# doPlots(datasets, histoDict1, MetBtagDeltaPhiCuts, SaveExtension = "Met_Btag_DeltaPhi")
# doPlots(datasets, histoDict1, MetBtagDeltaPhiCircularityCuts, SaveExtension = "Met_Btag_DeltaPhi_Circularity")
# doPlots(datasets, histoDict1, TestCuts, SaveExtension = "Test")
# Do just mT plots
histoDict2 = {
"mT": "%s >> mT(30, 0.0, 600.0)" % (Mt)
}
for i in range(1, 8):
cutValue = (i+0.0)/(10.0)
doPlots(datasets, histoDict2, "circularity <= %f" % (cutValue), SaveExtension = "Circularity%s" % (i))
def doDataset(datasetsSeeds, optMode, labels):
for d in datasetsSeeds:
d.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(d)
plotter = tauEmbedding.CommonPlotter(optMode, "average", drawPlotCommon)
doPlots(datasetsSeeds, labels, "Data", plotter)
doPlots(datasetsSeeds, labels, "TTJets", plotter)
def main():
# Create all datasets from a multicrab task
datasets = dataset.getDatasetsFromMulticrabCfg(analysisName="test")
# We don't have yet the lumi information handled in NtupleAnalysis, so remove data for now
datasets.remove(datasets.getDataDatasetNames())
datasets.getDataset("TBHp_HToTauNu_M_200_13TeV_pythia6").setCrossSection(0.336902*2*0.955592) # pb
datasets.getDataset("TTbar_HBWB_HToTauNu_M_160_13TeV_pythia6").setCrossSection(0.336902*2*0.955592) # pb
datasets.getDataset("TTJets_MSDecaysCKM_central_Tune4C_13TeV_madgraph_tauola").setCrossSection(245.8) # pb
datasets.getDataset("QCD_Pt_50to80_Tune4C_13TeV_pythia8").setCrossSection(8148778.0) # pb
# For this we don't have cross section
datasets.remove(["DYJetsToLL_M10to50_TuneZ2star_Summer12"])
### datasets.remove(["TBHp_HToTauNu_M_200_13TeV_pythia6"])
datasets.remove(["QCD_Pt_50to80_TuneZ2star_13TeV_pythia6"])
datasets.remove(["DYToTauTau_M_20_CT10_TuneZ2star_v2_powheg_tauola_Summer12"])
# These have 0 events after skim in multicrab_TEST5, and the code crashes because of that
datasets.remove([
"QCD_Pt30to50_TuneZ2star_Summer12",
"QCD_Pt50to80_TuneZ2star_Summer12",
"QCD_Pt80to120_TuneZ2star_Summer12",
"QCD_Pt120to170_TuneZ2star_Summer12"
])
# As we use weighted counters for MC normalisation, we have to
# update the all event count to a separately defined value because
# the analysis job uses skimmed pattuple as an input
datasets.updateNAllEventsToPUWeighted(era="Run2012ABCD")
# At the moment the collision energy must be set by hand
for dset in datasets.getMCDatasets():
dset.setEnergy("8")
# At the moment the cross sections must be set by hand
xsect.setBackgroundCrossSections(datasets)
# Default merging and ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
datasets.rename("TTJets_MSDecaysCKM_central_Tune4C_13TeV_madgraph_tauola", "TTJets")
datasets.rename("QCD_Pt_50to80_Tune4C_13TeV_pythia8", "QCD")
# Apply TDR style
style = tdrstyle.TDRStyle()
dataMCExample(datasets)
MetComparison(datasets)
# Script execution can be paused like this, it will continue after
# user has given some input (which must include enter)
if drawToScreen:
raw_input("Hit enter to continue")
def printMuonOrigin(datasetsMC, selection):
datasets = datasetsMC.deepCopy()
plots.mergeRenameReorderForDataMC(datasets)
printMuonOriginHelper(datasets, selection)
datasets.merge("Ws", ["TTJets", "WJets", "SingleTop"])
datasets.selectAndReorder(["Ws"])
printMuonOriginHelper(datasets, selection)
def doDataset(datasetsEmb, datasetsSig, optMode):
datasetsSig.updateNAllEventsToPUWeighted()
datasetsEmb.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(datasetsEmb)
plots.mergeRenameReorderForDataMC(datasetsSig)
plotter = tauEmbedding.CommonPlotter(optMode+"_embdatasigmc", "embdatasigmc", drawPlotCommon)
doPlots(datasetsEmb, datasetsSig, plotter, optMode)
def main():
tauDirEmbs = [os.path.join("..", d) for d in tauEmbedding.tauDirEmbs]
tauDirSig = "../"+tauEmbedding.tauDirSig
dirEmbs = ["."] + [os.path.join("..", d) for d in tauEmbedding.dirEmbs[1:]]
dirSig = "../"+tauEmbedding.dirSig
# tauDirEmbs = tauDirEmbs[:2]
# dirEmbs = dirEmbs[:2]
tauDatasetsEmb = tauEmbedding.DatasetsMany(tauDirEmbs, tauAnalysisEmb+"Counters", normalizeMCByLuminosity=True)
tauDatasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=tauDirSig+"/multicrab.cfg", counters=tauAnalysisSig+"Counters")
datasetsEmb = tauEmbedding.DatasetsMany(dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
tauDatasetsSig.updateNAllEventsToPUWeighted()
datasetsSig.updateNAllEventsToPUWeighted()
tauDatasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
tauDatasetsEmb.setLumiFromData()
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(tauDatasetsSig)
plots.mergeRenameReorderForDataMC(datasetsSig)
def mergeEWK(datasets):
datasets.merge("EWKMC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"], keepSources=True)
mergeEWK(tauDatasetsSig)
mergeEWK(datasetsSig)
tauDatasetsEmb.forEach(mergeEWK)
datasetsEmb.forEach(mergeEWK)
plots._legendLabels["EWKMC"] = "EWK"
# Apply TDR style
style = tdrstyle.TDRStyle()
ROOT.gStyle.SetHatchesLineWidth(2)
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
#histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
histograms.createLegend.setDefaults(y1=0.93, y2=0.77, x1=0.45, x2=0.7, textSize=0.04)
#histograms.createLegend.setDefaults(y1=0.93, y2=0.7, x1=0.45, x2=0.93)
tauEmbedding.normalize = True
tauEmbedding.era = "Run2011A"
def dop(name):
doTauPlots(tauDatasetsEmb, tauDatasetsSig, name)
doTauCounters(tauDatasetsEmb, tauDatasetsSig, name)
doPlots(datasetsEmb, datasetsSig, name)
doCounters(datasetsEmb, datasetsSig, name)
dop("TTJets")
dop("WJets")
dop("DYJetsToLL")
dop("SingleTop")
dop("Diboson")
def main(opts):
datasets = dataset.getDatasetsFromMulticrabCfg(directory=opts.mdir, dataEra=dataEra, weightedCounters=False)
# datasets = dataset.getDatasetsFromRootFiles([("TTJets_TuneZ2_Summer11", "histograms.root")], counters=counters, dataEra=dataEra, analysisBaseName=analysis, weightedCounters=False)
plots.mergeRenameReorderForDataMC(datasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
process(datasets, "TTJets", "Before", ">= 1 genuine tau in acceptance")
def main():
dirEmbs = ["."] + [os.path.join("..", d) for d in result.dirEmbs[1:]]
dirSig = "../" + result.dirSig
datasetsEmb = result.DatasetsMany(dirEmbs,
analysisEmb + "Counters",
normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(
cfgfile=dirSig + "/multicrab.cfg", counters=analysisSig + "Counters")
datasetsEmb.remove(
filter(lambda name: "HplusTB" in name,
datasetsEmb.getAllDatasetNames()))
datasetsEmb.remove(
filter(lambda name: "TTToHplus" in name,
datasetsEmb.getAllDatasetNames()))
# del plots._datasetMerge["WW"]
# del plots._datasetMerge["WZ"]
# del plots._datasetMerge["ZZ"]
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(datasetsSig)
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.04)
datasetsEmb.remove(["W3Jets"])
datasetsEmb.remove(["QCD_Pt20_MuEnriched"])
#plots._legendLabels["QCD_Pt20_MuEnriched"] = "QCD"
histograms.createLegend.moveDefaults(dh=-0.05)
#histograms.createLegend.moveDefaults(dx=-0.18, dy=0.05, dh=-0.05)
tauEmbedding.normalize = True
#tauEmbedding.normalize=False
tauEmbedding.era = "Run2011A"
def mergeEWK(datasets):
datasets.merge(
"EWKMC",
["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson", "WW"],
keepSources=True)
#datasets.merge("EWKMC", ["WJets", "TTJets"], keepSources=True)
# mergeEWK(datasetsSig)
# datasetsEmb.forEach(mergeEWK)
datasetsEmbCorrected = result.DatasetsDYCorrection(datasetsEmb,
datasetsSig,
analysisEmb,
analysisSig)
datasetsResidual = result.DatasetsResidual(datasetsEmb, datasetsSig,
analysisEmb, analysisSig,
["DYJetsToLL", "WW"])
doPlots(datasetsEmb)
def doSystematicsVariation(myMulticrabDir, era, searchMode, optimizationMode,
syst, myOutputCreator, myShapeString, myNormFactors,
dataDrivenFakeTaus):
myModuleInfoString = "%s_%s_%s_%s" % (era, searchMode, optimizationMode,
syst)
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=myMulticrabDir)
systDsetMgr = dsetMgrCreator.createDatasetManager(
dataEra=era,
searchMode=searchMode,
optimizationMode=optimizationMode,
systematicVariation=syst)
# Do the usual normalisation
systDsetMgr.updateNAllEventsToPUWeighted()
systDsetMgr.loadLuminosities()
plots.mergeRenameReorderForDataMC(systDsetMgr)
systDsetMgr.merge(
"EWK", ["TTJets", "WJets", "DYJetsToLL", "SingleTop", "Diboson"])
myLuminosity = systDsetMgr.getDataset("Data").getLuminosity()
myFakeRateCalculator = fakeRate.FakeRateCalculator(
systDsetMgr,
myShapeString,
myNormFactors,
myLuminosity,
dataDrivenFakeTaus=dataDrivenFakeTaus)
# Obtain results
mySystModuleResults = pseudoMultiCrabCreator.PseudoMultiCrabModule(
systDsetMgr, era, searchMode, optimizationMode, syst)
mySystResult = qcdInvertedResult.QCDInvertedResultManager(
myShapeString,
"AfterCollinearCuts",
systDsetMgr,
myLuminosity,
myModuleInfoString,
myFakeRateCalculator.getTotalFakeRateProbabilities(),
dataDrivenFakeTaus=dataDrivenFakeTaus,
shapeOnly=False,
displayPurityBreakdown=False,
noRebin=True)
mySystModuleResults.addShape(mySystResult.getShape(), myShapeString)
mySystModuleResults.addShape(mySystResult.getShapeMCEWK(),
myShapeString + "_MCEWK")
mySystModuleResults.addShape(mySystResult.getShapePurity(),
myShapeString + "_Purity")
mySystModuleResults.addDataDrivenControlPlots(
mySystResult.getControlPlots(), mySystResult.getControlPlotLabels())
mySystResult.delete()
## Save module info
myOutputCreator.addModule(mySystModuleResults)
systDsetMgr.close()
dsetMgrCreator.close()
ROOT.gROOT.CloseFiles()
ROOT.gROOT.GetListOfCanvases().Delete()
ROOT.gDirectory.GetList().Delete()
def doDataset(datasetsAve, datasetsSeeds, optMode):
ds = [datasetsAve] + datasetsSeeds
for d in ds:
d.updateNAllEventsToPUWeighted()
plots.mergeRenameReorderForDataMC(d)
plotter = tauEmbedding.CommonPlotter(optMode + "_average", "average",
drawPlotCommon)
doPlots(datasetsAve, datasetsSeeds, "Data", plotter)
def __init__(self, analyses, mergeAllMC=False):
self.analyses = analyses
self.datasetManagers = []
for an in analyses:
dm = dataset.getDatasetsFromMulticrabCfg(counters=an +
"Counters/weighted")
dm.loadLuminosities()
plots.mergeRenameReorderForDataMC(dm)
if mergeAllMC:
dm.mergeMC()
self.datasetManagers.append(dm)
def main():
# Create all datasets from a multicrab task
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
# Read integrated luminosities of data datasets from lumi.json
datasets.loadLuminosities()
# Include only 120 mass bin of HW and HH datasets
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M120" in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
# Default merging nad ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
# Set BR(t->H) to 0.2, keep BR(H->tau) in 1
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Merge WH and HH datasets to one (for each mass bin)
# TTToHplusBWB_MXXX and TTToHplusBHminusB_MXXX to "TTToHplus_MXXX"
plots.mergeWHandHH(datasets)
# Merge EWK datasets
datasets.merge("EWK", [
"WJets",
"TTJets",
"DYJetsToLL",
"SingleTop",
"Diboson"
])
# Apply TDR style
style = tdrstyle.TDRStyle()
# Create the normalized plot of transverse mass
# Read the histogram from the file
#mT = plots.DataMCPlot(datasets, analysis+"/transverseMass")
# Create the histogram from the tree (and see the selections explicitly)
td = dataset.TreeDraw(analysis+"/tree", weight="weightPileup*weightTrigger*weightPrescale",
selection="met_p4.Et() > 70 && Max$(jets_btag) > 1.7")
mT = plots.DataMCPlot(datasets, td.clone(varexp="sqrt(2 * tau_p4.Pt() * met_p4.Et() * (1-cos(tau_p4.Phi()-met_p4.Phi())))>>dist(400, 0, 400)"))
# Rebin before subtracting
mT.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
# Create the data-EWK histogram and draw it
dataEwkDiff(mT)
# Draw the mT distribution
transverseMass(mT)
def main():
# Create all datasets from a multicrab task
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.updateNAllEventsToPUWeighted()
# Read integrated luminosities of data datasets from lumi.json
datasets.loadLuminosities()
# Default merging nad ordering of data and MC datasets
# All data datasets to "Data"
# All QCD datasets to "QCD"
# All single top datasets to "SingleTop"
# WW, WZ, ZZ to "Diboson"
plots.mergeRenameReorderForDataMC(datasets)
# Set the signal cross sections to a given BR(t->H), BR(h->taunu)
#xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.2, br_Htaunu=1)
# LandS assumes ttbar cross section for both HW and HH
#xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# LandS expects that HW and HH are normalized to top cross section
xsect.setHplusCrossSectionsToTop(datasets)
# Create data-MC comparison plot to get the proper normalization
# easily
mt = plots.DataMCPlot(datasets, analysis + "/transverseMassBeforeFakeMet")
# Rebin to have the agreed 10 GeV binning
mt.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(10))
# Create the output ROOT file
f = ROOT.TFile.Open(outputFile, "RECREATE")
# Add the histograms of the wanted datasets to the tree
for datasetName, outputName in [("Data", "data"),
("TTToHplusBWB_M100", "hw_100"),
("TTToHplusBHminusB_M100", "hh_100"),
("TTToHplusBWB_M120", "hw_120"),
("TTToHplusBHminusB_M120", "hh_120"),
("TTToHplusBWB_M160", "hw_160"),
("TTToHplusBHminusB_M160", "hh_160")]:
th1 = mt.histoMgr.getHisto(datasetName).getRootHisto().Clone(
"mt_" + outputName)
th1.SetDirectory(f)
th1.Write()
# Write and close the file
f.Close()
print
print "Wrote transverse mass histograms to %s for LandS" % outputFile
def manageDatasets(datasets):
'''
def manageDatasets(datasets):
Handles the PU weighting, luminosity loading and signal merging of the datatasets.
'''
### Since (by default) we use weighted counters, and the analysis job inputs are
### normally skims (as are "v44_4" and "v53_1"), need to update events to PU weighted
print "\n*** Updating events to PU weighted:"
datasets.updateNAllEventsToPUWeighted()
if bMcOnly==True:
datasets.remove(datasets.getDataDatasetNames())
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
else:
datasets.loadLuminosities()
print "\n*** Default merging of dataset components:"
plots.mergeRenameReorderForDataMC(datasets)
print "\n*** Removing all signal samples, except m=%s GeV/cc" % (signalMass)
datasets.remove(filter(lambda name: "TTToHplus" in name and not "M"+signalMass in name, datasets.getAllDatasetNames()))
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
### Setup style
styleGenerator = styles.generator(fill=False)
plots._legendLabels["TTToHplus_M"+signalMass] = "m_{H^{+}} = " + signalMass + " GeV/c^{2}"
style = tdrstyle.TDRStyle()
print "*** Setting signal cross sections, using BR(t->bH+)=%s and BR(H+ -> tau+ nu)=%s" % (BR_tH, BR_Htaunu)
xsect.setHplusCrossSectionsToBR(datasets, BR_tH, BR_Htaunu)
print "*** Merging WH and HH signals"
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
### Now optionally remove datasets
if bRemoveEwk:
mergeEwkMc(datasets)
datasets.remove(filter(lambda name: "EWK MC" in name, datasets.getAllDatasetNames()))
else:
if bMergeEwk==True:
mergeEwkMc(datasets)
if bRemoveQcd:
datasets.remove(filter(lambda name: "QCD" in name, datasets.getAllDatasetNames()))
#if bRemoveSignal: FIXME
# datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames()))
# datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
print "*** Available datasets: %s" % (datasets.getAllDatasetNames())
return datasets
def main():
datasetsEmb = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirEmb+"/multicrab.cfg", counters=analysisEmb+"Counters")
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsEmb.loadLuminosities()
plots.mergeRenameReorderForDataMC(datasetsEmb)
plots.mergeRenameReorderForDataMC(datasetsSig)
style = tdrstyle.TDRStyle()
histograms.createLegend.setDefaults(y1=0.93, y2=0.78, x1=0.6, x2=0.95)
doPlots(datasetsEmb, datasetsSig, "TTJets")
doPlots(datasetsEmb, datasetsSig, "WJets")
def main():
dirEmbs = ["."] + [os.path.join("..", d) for d in tauEmbedding.dirEmbs[1:]]
dirSig = "../" + tauEmbedding.dirSig
# dirEmbs = dirEmbs[:2]
datasetsEmb = tauEmbedding.DatasetsMany(dirEmbs,
analysisEmb + "/counters",
normalizeMCByLuminosity=True)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(
cfgfile=dirSig + "/multicrab.cfg", counters=analysisSig + "/counters")
datasetsSig.updateNAllEventsToPUWeighted()
datasetsEmb.forEach(plots.mergeRenameReorderForDataMC)
datasetsEmb.setLumiFromData()
plots.mergeRenameReorderForDataMC(datasetsSig)
def mergeEWK(datasets):
datasets.merge(
"EWKMC", ["WJets", "TTJets", "DYJetsToLL", "SingleTop", "Diboson"],
keepSources=True)
mergeEWK(datasetsSig)
datasetsEmb.forEach(mergeEWK)
plots._legendLabels["EWKMC"] = "EWK"
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
tauEmbedding.normalize = True
tauEmbedding.era = "Run2011AB"
table = counter.CounterTable()
def dop(name):
doPlots(datasetsEmb, datasetsSig, name)
tbl = doCounters(datasetsEmb, datasetsSig, name)
for icol in xrange(tbl.getNcolumns()):
table.appendColumn(tbl.getColumn(icol))
dop("TTJets")
dop("WJets")
dop("DYJetsToLL")
dop("SingleTop")
dop("Diboson")
cellFormat = counter.TableFormatLaTeX(
counter.CellFormatTeX(valueFormat='%.4f', withPrecision=2))
print table.format(cellFormat)
def main(opts):
# muonDir = "/opt/data/matti/embedding/v44_5/multicrab_muonDebugAnalysisNtupleAod_130507_141258"
muonDir = "/opt/data/matti/embedding/v44_5/multicrab_muonDebugAnalysisNtupleAod_130515_104754"
tauDir = "/opt/data/matti/embedding/v44_5/multicrab_analysisTau_v44_5_GenTauDebug_130508_123329"
muonDatasets = dataset.getDatasetsFromMulticrabCfg(directory=muonDir,
weightedCounters=False)
tauDatasets = dataset.getDatasetsFromMulticrabCfg(directory=tauDir,
weightedCounters=False)
plots.mergeRenameReorderForDataMC(muonDatasets)
plots.mergeRenameReorderForDataMC(tauDatasets)
# Apply TDR style
style = tdrstyle.TDRStyle()
tdrstyle.setDarkBodyRadiatorPalette()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.cmsText[histograms.CMSMode.SIMULATION] = "Simulation"
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.7, x2=0.93)
selectorArgsMuon = MuonSelectorArgs()
selectorArgsTau = TauSelectorArgs()
selectorArgsMuon.set(puWeight="Run2011A")
selectorArgsTau.set(puWeight="Run2011A")
args = {
"process": opts.process,
#"maxEvents": 100,
#"printStatus": False
}
ntupleCacheMuon = dataset.NtupleCache(
"tree",
"EmbeddingDebugMuonAnalysisSelector",
selectorArgs=selectorArgsMuon,
cacheFileName="histogramCacheMuon.root",
macros=["rochcor_wasym_v4.C"],
**args)
ntupleCacheTau = dataset.NtupleCache(
"tree",
"EmbeddingDebugTauAnalysisSelector",
selectorArgs=selectorArgsTau,
cacheFileName="histogramCacheTau.root",
**args)
doPlots(muonDatasets.getDataset("TTJets"),
tauDatasets.getDataset("TTJets"), ntupleCacheMuon, ntupleCacheTau)
doCounters(muonDatasets, tauDatasets, "TTJets", ntupleCacheMuon,
ntupleCacheTau)
def main(opts,signalDsetCreator,era,searchMode,optimizationMode):
# Make directory for output
mySuffix = "phiOscillation_%s_%s_%s"%(era,searchMode,optimizationMode)
if os.path.exists(mySuffix):
if os.path.exists("%s_old"%mySuffix):
shutil.rmtree("%s_old"%mySuffix)
os.rename(mySuffix, "%s_old"%mySuffix)
os.mkdir(mySuffix)
# Create dataset manager
myDsetMgr = signalDsetCreator.createDatasetManager(dataEra=era,searchMode=searchMode,optimizationMode=optimizationMode)
myDsetMgr.updateNAllEventsToPUWeighted()
myDsetMgr.loadLuminosities()
style = tdrstyle.TDRStyle()
# Get luminosity
myLuminosity = 0.0
myDataDatasets = myDsetMgr.getDataDatasets()
for d in myDataDatasets:
myLuminosity += d.getLuminosity()
# Merge datasets
plots.mergeRenameReorderForDataMC(myDsetMgr)
mergeEWK = not True
myAvailableDatasetNames = ["Data", "TTToHplusBWB_M120"]
if mergeEWK:
myDsetMgr.merge("EWK", [
"TTJets",
"WJets",
"DYJetsToLL",
"SingleTop",
"Diboson"
])
myAvailableDatasetNames.extend(["EWK"])
else:
myAvailableDatasetNames.extend(["TTJets", "WJets"])
# loop over datasets
myList = []
if opts.dirs == None:
myList.extend(myAvailableDatasetNames)
else:
if len(opts.dirs) > 0:
myList.extend(opts.dirs)
else:
myList.extend(myAvailableDatasetNames)
for d in myList:
print HighlightStyle()+d+NormalStyle()
doPlots(d, myDsetMgr.getDataset(d), opts, mySuffix, myLuminosity)
