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 main():
dirNormal = "../multicrab_signalAnalysisGenTauSkim_140814_211711"
dirEmb = "."
dsetsNormal = dataset.getDatasetsFromMulticrabCfg(directory=dirNormal, analysisName="signalAnalysisGenuineTau")
dsetsNormalCut = dataset.getDatasetsFromMulticrabCfg(directory=dirNormal, analysisName="signalAnalysisGenuineTauCaloMet70")
dsetsEmb = dataset.getDatasetsFromMulticrabCfg(directory=dirEmb, analysisName="signalAnalysisMIdEffTrgEffWTauMu")
dsetsEmbCut = dataset.getDatasetsFromMulticrabCfg(directory=dirEmb, analysisName="signalAnalysisMIdEffTrgEffWTauMuCaloMet70")
dsetsNormal.updateNAllEventsToPUWeighted()
dsetsNormalCut.updateNAllEventsToPUWeighted()
dsetsEmb.updateNAllEventsToPUWeighted()
dsetsEmbCut.updateNAllEventsToPUWeighted()
dsetsEmb.loadLuminosities()
dsetsEmbCut.loadLuminosities()
plots.mergeRenameReorderForDataMC(dsetsNormal)
plots.mergeRenameReorderForDataMC(dsetsNormalCut)
plots.mergeRenameReorderForDataMC(dsetsEmb)
plots.mergeRenameReorderForDataMC(dsetsEmbCut)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION_PRELIMINARY
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.82, x2=0.93)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.createLegendRatio.moveDefaults(dx=-0.05, dh=-0.1)
plots._legendLabels["BackgroundStatError"] = "Norm. stat. unc."
if not os.path.exists("calometComparison"):
os.mkdir("calometComparison")
#doPlots(dsetsNormal.getDataset("TTJets"), dsetsEmb.getDataset("TTJets"), dsetsEmb.getDataset("Data").getLuminosity())
doEffPlots(dsetsNormalCut.getDataset("TTJets"), dsetsNormal.getDataset("TTJets"), dsetsEmbCut.getDataset("TTJets"), dsetsEmb.getDataset("TTJets"), dsetsEmb.getDataset("Data").getLuminosity())
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 main():
dirAve = "."
# dirSeeds = []
# inputInfoPath = os.path.join(dirAve, "inputInfo.txt")
# f = open(inputInfoPath)
# input_re = re.compile("Embedded input directory: (?P<dir>\S+)")
# for line in f:
# m = input_re.search(line)
# if m:
# dirSeeds.append(os.path.join("..", m.group("dir")))
# f.close()
# if len(dirSeeds) == 0:
# raise Exception("Found 0 input directories from %s" % inputInfoPath)
parser = OptionParser(usage="Usage: %prog seed0 [seed1 ...]")
#parser.add_option("-s", "--seed", dest="dirSeeds", default=[], action="append"
# help="Path to pseudo-multicrab with a single seed (can be given multiple times)")
(opts, args) = parser.parse_args()
if len(args) == 0:
parser.error("No seed pseudo-multicrab directories were given")
# dirSeeds = [
## "../embedding_140509_100532",
## "../embedding_seedTest1_140508_154221",
## "../embedding_seedTest2_140508_154540",
## "../embedding_seedTest3_140508_155055",
## "../embedding_seedTest4_140508_155742"
# "../embedding_mc_tightPlus_140512_160900",
# "../embedding_mc_seedTest1_140807_084326"
# ]
dirSeeds = args
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.02)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.createLegendRatio.moveDefaults(dh=-0.1, dx=-0.53)
plots._legendLabels["BackgroundStatError"] = "Avg. stat. unc."
for optMode in [
# "OptQCDTailKillerZeroPlus",
"OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
"OptQCDTailKillerTightPlus",
# "OptQCDTailKillerVeryTightPlus",
# None
]:
datasetsAve = dataset.getDatasetsFromMulticrabCfg(directory=dirAve, dataEra=dataEra, analysisName=analysisEmb, optimizationMode=optMode)
datasetsSeeds = [
dataset.getDatasetsFromMulticrabCfg(directory=d, dataEra=dataEra, analysisName=analysisEmb, optimizationMode=optMode) for d in dirSeeds
]
doDataset(datasetsAve, datasetsSeeds, optMode)
datasetsAve.close()
for d in datasetsSeeds:
d.close()
tauEmbedding.writeToFile(optMode+"_average", "input.txt", ("Average: %s\n" % os.getcwd()) + "\n".join(["Seed: "+s for s in dirSeeds]))
def main():
effDir = "../multicrab_aodAnalysis_taumet_v53_3_131015_122226_triggerTestEff"
bitDir = "."
datasets = aux.MultiObject()
datasets.add(
"eff",
dataset.getDatasetsFromMulticrabCfg(directory=effDir, dataEra=era))
datasets.add(
"bit",
dataset.getDatasetsFromMulticrabCfg(directory=bitDir, dataEra=era))
datasets.forEach(plots.mergeRenameReorderForDataMC)
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.82, x2=0.93)
histograms.createLegend.moveDefaults(dx=-0.05)
plots._plotStyles["Ratio"].extend([
styles.StyleMarker(markerColor=ROOT.kRed),
styles.StyleLine(lineColor=ROOT.kRed)
])
plots._plotStyles["RatioLine"].extend(
[styles.StyleLine(lineColor=ROOT.kBlack)])
plots.drawPlot.setDefaults(addLuminosityText=True)
doPlots(*(datasets.getDataset("TTJets")))
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():
# 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():
# 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():
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():
# 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)
datasetsEmbSig.updateNAllEventsToPUWeighted()
datasetsSig.updateNAllEventsToPUWeighted()
# 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():
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(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():
# Read the datasets
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.remove(["WJets_TuneD6T_Winter10", "TTJets_TuneD6T_Winter10",
"TTToHplusBWB_M140_Spring11","TTToHplusBWB_M80_Spring11","TTToHplusBWB_M90_Spring11",
"TTToHplusBWB_M155_Spring11","TTToHplusBWB_M150_Spring11","TTToHplusBWB_M160_Spring11","TTToHplusBWB_M100_Spring11",
"TTToHplusBHminusB_M80_Spring11","TTToHplusBHminusB_M100_Spring11","TTToHplusBHminusB_M160_Spring11",
"TTToHplusBHminusB_M150_Spring11","TTToHplusBHminusB_M140_Spring11","TTToHplusBHminusB_M155_Spring11", "TauPlusX_160431-161016_Prompt","TauPlusX_162803-162828_Prompt",
"QCD_Pt30to50_TuneZ2_Spring11","QCD_Pt50to80_TuneZ2_Spring11","QCD_Pt80to120_TuneZ2_Spring11",
"QCD_Pt120to170_TuneZ2_Spring11","QCD_Pt170to300_TuneZ2_Spring11","QCD_Pt300to470_TuneZ2_Spring11",
# "Tau_165970-166164_Prompt", "Tau_166374-167043_Prompt", "Tau_167078-167784_Prompt", "Tau_165088-165633_Prompt"
# "Tau_163270-163869_May10","Tau_161217-163261_May10", "Tau_160431-161176_May10"
])
datasets.loadLuminosities()
# Take signals from 42X
datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames()))
datasets.remove(["QCD_Pt30to50_TuneZ2_Summer11","QCD_Pt50to80_TuneZ2_Summer11","QCD_Pt80to120_TuneZ2_Summer11",
"QCD_Pt120to170_TuneZ2_Summer11","QCD_Pt170to300_TuneZ2_Summer11","QCD_Pt300to470_TuneZ2_Summer11",
"WJets_TuneZ2_Summer11", "TTJets_TuneZ2_Summer11", "DYJetsToLL_M50_TuneZ2_Summer11", "Tau_160431-161176_May10",
"Tau_161119-161119_May10_Wed", "Tau_161217-163261_May10", "Tau_163270-163869_May10",
"Tau_165088-165633_Prompt", "Tau_165103-165103_Prompt_Wed", "Tau_165970-166164_Prompt",
"Tau_166346-166346_Prompt", "Tau_166374-167043_Prompt", "Tau_167078-167784_Prompt",
"Tau_167786-167913_Prompt_Wed"
])
datasetsSignal = dataset.getDatasetsFromMulticrabCfg(cfgfile="multicrab.cfg", counters=counters)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
# Apply TDR style
style = tdrstyle.TDRStyle()
datasets_tm = datasets.deepCopy()
genTopPt(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genTopPt", normalizeByCrossSection=True), "genTopPt")
genTopPt(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genTopPt_wrongB", normalizeByCrossSection=True), "genTopPt_wrongB")
genBquark_Eta(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_FromTop_Eta", normalizeByCrossSection=True), "genBquark_FromTop_Eta")
genBquark_Eta(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_NotFromTop_Eta", normalizeByCrossSection=True), "genBquark_NotFromTop_Eta")
genBquark_Pt(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_FromTop_Pt", normalizeByCrossSection=True), "genBquark_FromTop_Pt")
genBquark_Pt(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_NotFromTop_Pt", normalizeByCrossSection=True), "genBquark_NotFromTop_Pt")
genBquark_DeltaRTau(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_FromTop_DeltaRTau", normalizeByCrossSection=True), "genBquark_FromTop_DeltaRTau")
genBquark_DeltaRTau(plots.MCPlot(datasets, analysis+"/GenParticleAnalysis/genBquark_NotFromTop_DeltaRTau", normalizeByCrossSection=True), "genBquark_NotFromTop_DeltaRTau")
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():
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()))
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 getDatasets(multicrabPath, myDataEra):
# Get the ROOT files for all datasets, merge datasets and reorder them
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabPath,
dataEra=myDataEra)
#print "%sAvailable datasets:\n %s" % (" "*0, datasets.getAllDatasetNames())
# Print PSets used in ROOT-file generation
if bPrintPSet:
#print "*** Printing PSets for dataset \"%s\"" % ("TTToHplusBHminusB_M120_Fall11")
#print datasets.getDataset("TTToHplusBHminusB_M120_Fall11").getParameterSet()
psets = datasets.getSelections()
f = open("PSets.txt", "w")
f.write(psets)
f.close()
# Take care of PU weighting, luminosity, signal merging etc... of the datatasets
print "\n*** Datasets:"
manageDatasets(datasets)
# Print the dataset information for sanity checks
print "=" * 70
datasets.printInfo()
print "=" * 70
# Do sanity checks before returning the datasets object
nDatasets = len(datasets.getAllDatasetNames())
nDataDatasets = len(datasets.getDataDatasets())
nMCDatasets = len(datasets.getMCDatasets())
if nDatasets > 0:
return datasets
else:
print "%sERROR! There are zero (0) datasets. Check your settings. " % (
" " * 0)
sys.exit()
def main():
datasetsEmb = DatasetsMany(dirEmbs, analysisEmb+"Counters", normalizeMCByLuminosity=False)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirSig+"/multicrab.cfg", counters=analysisSig+"Counters")
datasetsEmb.forEach(lambda d: d.mergeData())
datasetsEmb.setLumiFromData()
# nonDyMc = ["QCD_Pt20_MuEnriched", "WJets", "TTJets", "SingleTop", "Diboson"]
# datasetsEmb.remove(nonDyMc)
# datasetsSig.remove(nonDyMc)
tauEmbedding.normalize=True
tauEmbedding.era = "Run2011A"
taskDir = multicrab.createTaskDir("embedded")
f = open(os.path.join(taskDir, "codeVersion.txt"), "w")
f.write(git.getCommitId()+"\n")
f.close()
f = open(os.path.join(taskDir, "codeStatus.txt"), "w")
f.write(git.getStatus()+"\n")
f.close()
f = open(os.path.join(taskDir, "codeDiff.txt"), "w")
f.write(git.getDiff()+"\n")
f.close()
f = open(os.path.join(taskDir, "inputInfo.txt"), "w")
f.write("Embedded directories:\n%s\n\nNormal directory:\n%s\n" % ("\n".join(dirEmbs), dirSig))
f.write("\nEmbedded analysis: %s\nNormal analysis: %s\n" % (analysisEmb, analysisSig))
f.close()
operate = lambda dn: operateDataset(taskDir, datasetsEmb, datasetsSig, dn)
operate("Data")
operate("DYJetsToLL_M50_TuneZ2_Summer11")
operate("WW_TuneZ2_Summer11")
def main():
dirSeeds = [
"embedding_mc_seedTest1_fix_140807_103811",
"embedding_mc_seedTest1_140807_084326"
]
labels = [
"Fixed",
"Current"
]
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.02)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.createLegendRatio.moveDefaults(dh=-0.1, dx=-0.53)
plots._legendLabels["BackgroundStatError"] = "Avg. stat. unc."
for optMode in [
# "OptQCDTailKillerZeroPlus",
# "OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
# "OptQCDTailKillerTightPlus",
# "OptQCDTailKillerVeryTightPlus",
None
]:
datasetsSeeds = [
dataset.getDatasetsFromMulticrabCfg(directory=d, dataEra=dataEra, analysisName=analysisEmb, optimizationMode=optMode) for d in dirSeeds
]
doDataset(datasetsSeeds, optMode, labels)
for d in datasetsSeeds:
d.close()
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 getMulticrabPsets(options, multicrabDir):
'''
def getMulticrabPsets(options, multicrabDir):
'''
### Get the user-defined (or default) data-era
myDataEra = options.dataEra
### Get the ROOT files for all datasets, merge datasets and reorder them
if options.verbose:
print "+++ VERBOSE: Obtaining datasets from multicrab directory \"%s\"" % (multicrabDir)
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabDir, dataEra=myDataEra)
### Print PSets used in ROOT-file generation
saveFileName = "PSet_Multicrab.txt" # + multicrabDir.strip("../") + ".txt"
saveFilePath = os.getcwd() + "/" + saveFileName
### Check that file does not already exist
fileExists(saveFilePath, False)
saveFile = open(saveFilePath, "w")
print "+++ Saving PSets from Multicrab directory \"%s\" to:\n \"%s\"" % (multicrabDir, saveFilePath)
saveFile.write(datasets.getSelections())
saveFile.close()
if options.verbose:
print "+++ VERBOSE: Obtained PSets from %s" % (multicrabDir)
return saveFilePath
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 embeddingPlots():
datasets = None
if os.path.exists("histograms.root"):
datasets = dataset.getDatasetsFromRootFiles([("Test", "histograms.root")], counters=None)
else:
datasets = dataset.getDatasetsFromMulticrabCfg(counters="countAnalyzer")
datasets.selectAndReorder(["TTJets_TuneZ2_Summer11"])
# datasets.selectAndReorder(["WJets_TuneZ2_Summer11"])
# datasets.selectAndReorder(["WJets_TuneZ2_Spring11"])
# datasets.selectAndReorder(["QCD_Pt20_MuEnriched_TuneZ2_Winter10"])
datasets.updateNAllEventsToPUWeighted()
#isoAnalyses = ["EmbeddingAnalyzer"+x for x in ["RelIso05", "RelIso10", "RelIso15", "RelIso20", "RelIso25", "RelIso50", ""]]
isoAnalyses = ["EmbeddingAnalyzer"]
muonTau = PlotMuonTau()
muonTauPFCand = PlotMuonPFCand()
genTauNu = PlotGenTauNu()
met = PlotMet()
muonTauMetDeltaPhi = PlotMuonTauMetDeltaPhi()
muonTauIso = PlotMuonTauIso()
#muonTauIso.plot(datasets, isoAnalyses)
#muonTauIso.plot(datasets, isoAnalyses, normalizeToOne=True)
for analysis in [
"EmbeddingAnalyzer",
# "tauIdEmbeddingAnalyzer",
# "tauPtIdEmbeddingAnalyzer"
# "EmbeddingAnalyzer/matched",
# "tauIdEmbeddingAnalyzer/matched",
# "tauPtIdEmbeddingAnalyzer/matched"
]:
for q in ["Pt", "Eta", "Phi"]:
muonTau.plot(datasets, analysis, q)
#genTauNu.plot(datasets, analysis, q)
for q in ["TrackDxy", "TrackDz"]:
muonTauPFCand.plot(datasets, analysis, q)
muonTauDR(datasets, analysis)
muonTauIso2(datasets, analysis)
# tauGenMass(datasets, analysis)
# muonTauMetDeltaPhi.plot(datasets, analysis, "Met")
for t in [
"Met",
# "MetNoMuon",
# "GenMetTrue",
# "GenMetCalo",
# "GenMetCaloAndNonPrompt",
# "GenMetNuSum",
# "GenMetNu"
]:
muonTauMetDeltaPhi.plot(datasets, analysis, t)
for q, log in [
("Et", True),
("X", True),
("Y", True),
("Phi", False)
]:
met.plot(datasets, analysis, t=t, q=q, log=log)
def getDatasets(multicrabPath, myDataEra):
'''
def getDatasets(multicrabPath, myDataEra):
This module used the user-defined path to a multicrab directory to
get the available datasets for a given Data-Era.
According to the boolean dictionary in the beginning of this file
the datasets are merged and reordered. Optionally the PSet parameters
are also printed for a specified dataset, also selected at the beginning
of this file with the "pSetToPrint" string.
'''
### Get the ROOT files for all datasets, merge datasets and reorder them
print "*** Obtaining datasets from: %s" % (multicrabPath)
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabPath, dataEra=myDataEra)
#print "*** Available datasets: %s" % (datasets.getAllDatasetNames())
### Print PSets used in ROOT-file generation
if getBool("bPrintPSet"):
print datasets.getDataset(pSetToPrint).getParameterSet()
### Take care of PU weighting, luminosity, signal merging etc... of the datatasets
manageDatasets(datasets)
### Print the dataset information for sanity checks
datasets.printInfo()
return datasets
def main():
dirSeeds = [
"embedding_mc_seedTest1_fix_140807_103811",
"embedding_mc_seedTest1_140807_084326"
]
labels = ["Fixed", "Current"]
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.02)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.createLegendRatio.moveDefaults(dh=-0.1, dx=-0.53)
plots._legendLabels["BackgroundStatError"] = "Avg. stat. unc."
for optMode in [
# "OptQCDTailKillerZeroPlus",
# "OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
# "OptQCDTailKillerTightPlus",
# "OptQCDTailKillerVeryTightPlus",
None
]:
datasetsSeeds = [
dataset.getDatasetsFromMulticrabCfg(directory=d,
dataEra=dataEra,
analysisName=analysisEmb,
optimizationMode=optMode)
for d in dirSeeds
]
doDataset(datasetsSeeds, optMode, labels)
for d in datasetsSeeds:
d.close()
def getDatasets(multicrabPath, myDataEra):
# Get the ROOT files for all datasets, merge datasets and reorder them
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabPath, dataEra=myDataEra)
#print "%sAvailable datasets:\n %s" % (" "*0, datasets.getAllDatasetNames())
# Print PSets used in ROOT-file generation
if bPrintPSet:
#print "*** Printing PSets for dataset \"%s\"" % ("TTToHplusBHminusB_M120_Fall11")
#print datasets.getDataset("TTToHplusBHminusB_M120_Fall11").getParameterSet()
psets = datasets.getSelections()
f = open("PSets.txt", "w")
f.write(psets)
f.close()
# Take care of PU weighting, luminosity, signal merging etc... of the datatasets
print "\n*** Datasets:"
manageDatasets(datasets)
# Print the dataset information for sanity checks
print "="*70
datasets.printInfo()
print "="*70
# Do sanity checks before returning the datasets object
nDatasets = len(datasets.getAllDatasetNames())
nDataDatasets = len(datasets.getDataDatasets())
nMCDatasets = len(datasets.getMCDatasets())
if nDatasets > 0:
return datasets
else:
print "%sERROR! There are zero (0) datasets. Check your settings. " % (" "*0)
sys.exit()
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():
# 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)
# 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():
# dirEmb = "../embedding_mc_nooptmodes_140826_094514"
dirEmb = "../embedding_mc_mtweightedfit_140822_101246"
dirSig = "."
for optMode in [
"OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
# "OptQCDTailKillerTightPlus",
# None
]:
datasetsEmb = dataset.getDatasetsFromMulticrabCfg(directory=dirEmb, dataEra=dataEra, analysisName=analysisEmb, optimizationMode=optMode)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(directory=dirSig, dataEra=dataEra, analysisName=analysisSig, optimizationMode=optMode)
doDataset(datasetsEmb, datasetsSig, optMode)
datasetsEmb.close()
datasetsSig.close()
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 getMulticrabPsets(options, multicrabDir):
'''
def getMulticrabPsets(options, multicrabDir):
'''
### Get the user-defined (or default) data-era
myDataEra = options.dataEra
### Get the ROOT files for all datasets, merge datasets and reorder them
if options.verbose:
print "+++ VERBOSE: Obtaining datasets from multicrab directory \"%s\"" % (
multicrabDir)
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabDir,
dataEra=myDataEra)
### Print PSets used in ROOT-file generation
saveFileName = "PSet_Multicrab.txt" # + multicrabDir.strip("../") + ".txt"
saveFilePath = os.getcwd() + "/" + saveFileName
### Check that file does not already exist
fileExists(saveFilePath, False)
saveFile = open(saveFilePath, "w")
print "+++ Saving PSets from Multicrab directory \"%s\" to:\n \"%s\"" % (
multicrabDir, saveFilePath)
saveFile.write(datasets.getSelections())
saveFile.close()
if options.verbose:
print "+++ VERBOSE: Obtained PSets from %s" % (multicrabDir)
return saveFilePath
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 getDatasets(multicrabPath, myDataEra):
'''
def getDatasets(multicrabPath, myDataEra):
This module used the user-defined path to a multicrab directory to
get the available datasets for a given Data-Era.
According to the boolean dictionary in the beginning of this file
the datasets are merged and reordered. Optionally the PSet parameters
are also printed for a specified dataset, also selected at the beginning
of this file with the "pSetToPrint" string.
'''
### Get the ROOT files for all datasets, merge datasets and reorder them
print "*** Obtaining datasets from: %s" % (multicrabPath)
datasets = dataset.getDatasetsFromMulticrabCfg(directory=multicrabPath,
dataEra=myDataEra)
#print "*** Available datasets: %s" % (datasets.getAllDatasetNames())
### Print PSets used in ROOT-file generation
if getBool("bPrintPSet"):
print datasets.getDataset(pSetToPrint).getParameterSet()
### Take care of PU weighting, luminosity, signal merging etc... of the datatasets
manageDatasets(datasets)
### Print the dataset information for sanity checks
datasets.printInfo()
return datasets
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():
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()
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 = 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 main():
parser = OptionParser(usage="Usage: %prog [options]")
parser.add_option("--dirSig", dest="dirSig", default=None,
help="Path to signalAnalysisGenTau multicrab directory")
(opts, args) = parser.parse_args()
if opts.dirSig is None:
parser.error("--dirSig missing")
dirEmb = "."
dirSig = opts.dirSig
# Apply TDR style
style = tdrstyle.TDRStyle()
#histograms.createLegend.setDefaults(y1=0.93, y2=0.75, x1=0.52, x2=0.93)
# histograms.createLegend.moveDefaults(dx=-0.1, dh=-0.2)
# histograms.createLegend.moveDefaults(dx=-0.15, dy=-0.01, dh=+0.05)
# histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatAndSyst)
# histograms.createLegendRatio.moveDefaults(dh=-0.1, dx=-0.53)
# histograms.createLegendRatio.moveDefaults(dx=-0.08)
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"] = "Norm. stat. unc."
plots._legendLabels["BackgroundStatError"] = "Sim. stat. unc" #"Norm. stat. unc."
plots._legendLabels["BackgroundStatSystError"] = "Sim. stat.#oplussyst. unc." # "Norm. stat.#oplussyst. unc."
plots._legendLabels["Data"] = "Embedded data"
for optMode in [
# "OptQCDTailKillerNoCuts",
"OptQCDTailKillerLoosePlus",
# "OptQCDTailKillerMediumPlus",
# "OptQCDTailKillerTightPlus",
# None
]:
datasetsEmb = dataset.getDatasetsFromMulticrabCfg(directory=dirEmb, dataEra=dataEra, analysisName=analysisEmb, optimizationMode=optMode)
datasetsSig = dataset.getDatasetsFromMulticrabCfg(directory=dirSig, dataEra=dataEra, analysisName=analysisSig, optimizationMode=optMode)
doDataset(datasetsEmb, datasetsSig, optMode)
datasetsEmb.close()
datasetsSig.close()
tauEmbedding.writeToFile(optMode+"_embdatasigmc", "input.txt", "Embedded: %s\nSignal analysis (GenTau): %s\n" % (os.getcwd(), dirSig))
def embeddingPlots():
datasets = None
if os.path.exists("histograms.root"):
datasets = dataset.getDatasetsFromRootFiles(
[("Test", "histograms.root")], counters=None)
else:
datasets = dataset.getDatasetsFromMulticrabCfg(
counters="countAnalyzer/weighted")
datasets.selectAndReorder(["TTJets_TuneZ2_Summer11"])
# datasets.selectAndReorder(["WJets_TuneZ2_Summer11"])
# datasets.selectAndReorder(["WJets_TuneZ2_Spring11"])
# datasets.selectAndReorder(["QCD_Pt20_MuEnriched_TuneZ2_Winter10"])
#isoAnalyses = ["EmbeddingAnalyzer"+x for x in ["RelIso05", "RelIso10", "RelIso15", "RelIso20", "RelIso25", "RelIso50", ""]]
isoAnalyses = ["EmbeddingAnalyzer"]
muonTau = PlotMuonTau()
muonTauPFCand = PlotMuonPFCand()
genTauNu = PlotGenTauNu()
met = PlotMet()
muonTauMetDeltaPhi = PlotMuonTauMetDeltaPhi()
muonTauIso = PlotMuonTauIso()
#muonTauIso.plot(datasets, isoAnalyses)
#muonTauIso.plot(datasets, isoAnalyses, normalizeToOne=True)
for analysis in [
"EmbeddingAnalyzer",
# "tauIdEmbeddingAnalyzer",
# "tauPtIdEmbeddingAnalyzer"
# "EmbeddingAnalyzer/matched",
# "tauIdEmbeddingAnalyzer/matched",
# "tauPtIdEmbeddingAnalyzer/matched"
]:
for q in ["Pt", "Eta", "Phi"]:
muonTau.plot(datasets, analysis, q)
#genTauNu.plot(datasets, analysis, q)
for q in ["TrackDxy", "TrackDz"]:
muonTauPFCand.plot(datasets, analysis, q)
muonTauDR(datasets, analysis)
muonTauIso2(datasets, analysis)
# tauGenMass(datasets, analysis)
# muonTauMetDeltaPhi.plot(datasets, analysis, "Met")
for t in [
"Met",
# "MetNoMuon",
# "GenMetTrue",
# "GenMetCalo",
# "GenMetCaloAndNonPrompt",
# "GenMetNuSum",
# "GenMetNu"
]:
muonTauMetDeltaPhi.plot(datasets, analysis, t)
for q, log in [("Et", True), ("X", True), ("Y", True),
("Phi", False)]:
met.plot(datasets, analysis, t=t, q=q, log=log)
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$(jets_btag) > 1.7")
mT = plots.DataMCPlot(datasets, td.clone(varexp="sqrt(2 * tau_p4.Pt() * met_p4.Et() * (1-cos(tau_p4.Phi()-met_p4.Phi())))>>dist(400, 0, 400)"))
# Rebin before subtracting
mT.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(20))
# Create the data-EWK histogram and draw it
dataEwkDiff(mT)
# Draw the mT distribution
transverseMass(mT)
def main():
datasets = dataset.getDatasetsFromMulticrabCfg(counters=counters)
datasets.updateNAllEventsToPUWeighted()
# remove data datasets
datasets.remove(filter(lambda name: "Tau_" in name, datasets.getAllDatasetNames()))
# remove heavy H+ datasets
datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames()))
plots.mergeRenameReorderForDataMC(datasets)
xsect.setHplusCrossSectionsToBR(datasets, br_tH=0.05, br_Htaunu=1)
plots.mergeWHandHH(datasets) # merging of WH and HH signals must be done after setting the cross section
# Apply TDR style
style = tdrstyle.TDRStyle()
# Define variables and cuts
tauPt = "tau_p4.Pt()"; tauPtCut = tauPt+" > 40"
tauLeadingCandPt = "tau_leadPFChargedHadrCand_p4.Pt()"; tauLeadingCandPtCut = tauLeadingCandPt+" > 20"
met = "met_p4.Et()"; metCut = met+" > 70"
btagMax = "Max$(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():
# 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 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():
dirNormal = "../multicrab_signalAnalysisGenTauSkim_140814_211711"
dirEmb = "."
dsetsNormal = dataset.getDatasetsFromMulticrabCfg(
directory=dirNormal, analysisName="signalAnalysisGenuineTau")
dsetsNormalCut = dataset.getDatasetsFromMulticrabCfg(
directory=dirNormal, analysisName="signalAnalysisGenuineTauCaloMet70")
dsetsEmb = dataset.getDatasetsFromMulticrabCfg(
directory=dirEmb, analysisName="signalAnalysisMIdEffTrgEffWTauMu")
dsetsEmbCut = dataset.getDatasetsFromMulticrabCfg(
directory=dirEmb,
analysisName="signalAnalysisMIdEffTrgEffWTauMuCaloMet70")
dsetsNormal.updateNAllEventsToPUWeighted()
dsetsNormalCut.updateNAllEventsToPUWeighted()
dsetsEmb.updateNAllEventsToPUWeighted()
dsetsEmbCut.updateNAllEventsToPUWeighted()
dsetsEmb.loadLuminosities()
dsetsEmbCut.loadLuminosities()
plots.mergeRenameReorderForDataMC(dsetsNormal)
plots.mergeRenameReorderForDataMC(dsetsNormalCut)
plots.mergeRenameReorderForDataMC(dsetsEmb)
plots.mergeRenameReorderForDataMC(dsetsEmbCut)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.cmsTextMode = histograms.CMSMode.SIMULATION_PRELIMINARY
histograms.createLegend.setDefaults(y1=0.93, y2=0.8, x1=0.82, x2=0.93)
histograms.uncertaintyMode.set(histograms.uncertaintyMode.StatOnly)
histograms.createLegendRatio.moveDefaults(dx=-0.05, dh=-0.1)
plots._legendLabels["BackgroundStatError"] = "Norm. stat. unc."
if not os.path.exists("calometComparison"):
os.mkdir("calometComparison")
#doPlots(dsetsNormal.getDataset("TTJets"), dsetsEmb.getDataset("TTJets"), dsetsEmb.getDataset("Data").getLuminosity())
doEffPlots(dsetsNormalCut.getDataset("TTJets"),
dsetsNormal.getDataset("TTJets"),
dsetsEmbCut.getDataset("TTJets"), dsetsEmb.getDataset("TTJets"),
dsetsEmb.getDataset("Data").getLuminosity())
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 __init__(self, dirs, counters, normalizeMCByLuminosity=False):
self.datasetManagers = []
for d in dirs:
datasets = dataset.getDatasetsFromMulticrabCfg(cfgfile=d +
"/multicrab.cfg",
counters=counters)
datasets.loadLuminosities()
tauEmbedding.updateAllEventsToWeighted(datasets)
self.datasetManagers.append(datasets)
self.normalizeMCByLuminosity = normalizeMCByLuminosity
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
