if cutMode == "mumu":

if tree.metPF2PATPt < 10.: return 0.8841

if tree.metPF2PATPt < 20.: return 0.9386

if tree.metPF2PATPt < 30.: return 1.0131

if tree.metPF2PATPt < 40.: return 1.1012

if tree.metPF2PATPt < 50.: return 1.1850

if tree.metPF2PATPt < 60.: return 1.2500

else: return 1.3071

if cutMode == "ee":

if tree.metPF2PATPt < 10.: return 0.9215

if tree.metPF2PATPt < 20.: return 0.9608

if tree.metPF2PATPt < 30.: return 1.0246

if tree.metPF2PATPt < 40.: return 1.0964

if tree.metPF2PATPt < 50.: return 1.1633

if tree.metPF2PATPt < 60.: return 1.2529

else: return 1.2194

if cutMode == "emu":

if tree.metPF2PATPt < 10.: return 0.9028

if tree.metPF2PATPt < 20.: return 0.9497

if tree.metPF2PATPt < 30.: return 1.0189

if tree.metPF2PATPt < 40.: return 1.0988

if tree.metPF2PATPt < 50.: return 1.17415

if tree.metPF2PATPt < 60.: return 1.25145

ibin = 0

for i in range(puA.GetNbinsX()):

if pileupWeight == puA.GetBinContent(i):

ibin = i

p0_minus = [ 1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1. ]

p1_minus = [-0.677786, -0.619614, -0.49465, -0.357963, -0.238359, -0.110002, 0.0348629, 0.191263, 0.347648, 0.516615, 0.679646, 0.836673, 0.97764, 1.135, 1.29922, 1.42467, 1.55901, 1.61762, 1.67275, 1.96008]

p2_minus = [ 0.526164, 0.251816, 0.11049, 0.026917, -0.0464692, -0.087022, -0.0931581, -0.0714295, -0.0331772, 0.0347473, 0.108658, 0.193048, 0.272314, 0.376357, 0.4964, 0.58854, 0.684959, 0.731063, 0.760044, 1.02386]

p1_expoM = [ 1.63363e-03, 6.79290e-04, 3.69900e-04, 2.24349e-04, 9.87156e-06]

p2_expoM = [ 2.64692, 3.26585, 3.53229, 4.18035, 5.64027]

p0_plus = [ 1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1. ]

p1_plus = [ -0.739059, -0.594445, -0.477276, -0.359707, -0.233573, -0.103458, 0.0373401, 0.176571, 0.337617, 0.499074, 0.675126, 0.840522, 1.00917, 1.15847, 1.23816, 1.44271, 1.52982, 1.46385, 1.5802, 0.988689]

p2_plus = [ 0.208068, 0.130033, 0.0850356, 0.0448344, 0.000749832, -0.0331347, -0.0653281, -0.0746009, -0.0800667, -0.0527636, -0.00402649, 0.103338, 0.261261, 0.491084, 0.857966, 1.19495, 1.75071, 2.65559, 3.35433, 5.48835]

p1_expoP = [ 1.42463e-01, 4.18966e-02, 1.12697e-01, 1.66197e-01, 1.50768e-01]

p2_expoP = [ 1.98758, 2.27217, 2.26799, 2.38455, 2.52428]

Shift = 0

if puUD == 1:

Shift = 0.6

else:

Shift = -0.6

Pweight = 1.

if ibin >= 0 and ibin < 20:

if Shift < 0.:

Pweight = p0_minus[ibin] + p1_minus[ibin]*Shift + p2_minus[ibin]*Shift*Shift

else:

Pweight = p0_plus[ibin] + p1_plus[ibin]*Shift + p2_plus[ibin]*Shift*Shift

elif ibin < 25.:

if Shift < 0.:

Pweight = p1_expoM[ibin-20]*exp(p2_expoM[ibin-20]*Shift)

else:

Pweight = p1_expoP[ibin-20]*exp(p2_expoP[ibin-20]*Shift)

else:

Pweight = 0.

# print ibin, pileupWeight,Pweight

parser = OptionParser("usage: %prog [options] arg")

parser.add_option("-c","--config",dest="configFile",help="Config file containing list of files for each dataset")

parser.add_option("-m","--mode",dest="cutMode",help="Cut mode to be used on the full dataset")

parser.add_option("-o","--outFolder",dest="outFolder",default="",help="Name of the folder to save the cut flows (root and png) to")

parser.add_option("-e","--postfix",dest="postfix",default="ANotHelpfulPostfix",help="A sensible name that will allow you to identify the cut flows")

parser.add_option("-s","--sysOut",dest="sysOut",help="Folder the one bin histograms will be put into")

parser.add_option("-p","--postOBH",dest="obhPostfix",default="",help = "Post fix on the one bin histograms. This means the systematic and up or down.")

parser.add_option("-d","--data",action="store_true",dest="dataFlag",default=False,help="Only run on data")

parser.add_option("-a","--saveSkim",dest="skimSaveFile",default="",help="If you want to save the skims, set this option to the out-folder on data0.")

parser.add_option("-q","--mc",action="store_true",dest="mcFlag",default=False,help="Only run on MC")

parser.add_option("-r","--reweightPU",action="store_true",dest="reweightPileup",default=False,help="Use new distribution to reweight pileup in MC")

parser.add_option("-x","--plotConfig",dest="plotConfig",help="A configuration containing plot information")

parser.add_option("-l","--lumiSpecified",action="store_true",dest="lumiSpecified",default=False,help="Set this flag if running over a specific run range and have lumi information for the data in the config.")

parser.add_option("-k","--recordEventNumbers",action="store_true",default=False,dest="eventDumpFlag",help="Set this flag to record the event run,lumi and number for each region of passing events.")

parser.add_option("-t","--ttbarReweight",action="store_true",default=False,dest="ttbarFlag",help="Set this flag for doing the top pt reweighting on ttbar. Will also produce systematic samples.")

parser.add_option("--JERPlus",action="store_true",dest="jerUFlag",default=False,help="JER up systematic")

parser.add_option("--JERMinus",action="store_true",dest="jerDFlag",default=False,help="JER down systematic")

parser.add_option("--JESPlus",action="store_true",dest="jesUFlag",default=False,help="JES up systematic")

parser.add_option("--JESMinus",action="store_true",dest="jesDFlag",default=False,help="JES down systematic")

parser.add_option("--btagsUp",action="store_true",dest="btagUFlag",default=False,help="b-tag SF up")

parser.add_option("--btagsDown",action="store_true",dest="btagDFlag",default=False,help="b-tag SF down")

parser.add_option("--pileupUp",action="store_true",dest="puUFlag",default=False,help="PU up")

parser.add_option("--pileupDown",action="store_true",dest="puDFlag",default=False,help="PU down")

parser.add_option("--metUp",action="store_true",dest="metUFlag",default=False,help="unclustered MET Up")

parser.add_option("--metDown",action="store_true",dest="metDFlag",default=False,help="Unclustered MET Down")

parser.add_option("--lepSFUp",action="store_true",dest="lepSFUFlag",default=False,help="Lepton scale Factor Up")

parser.add_option("--lepSFDown",action="store_true",dest="lepSFDFlag",default=False,help="Lepton Scale Factor Down")

parser.add_option("--zPlusJetsUp",action="store_true",dest="zPlusJetsUp",default=False,help="Scale up lepton scale factor")

parser.add_option("--zPlusJetsDown",action="store_true",dest="zPlusJetsDown",default=False,help="Scale down z+jets scale factor")

parser.add_option("--LESUp",action="store_true",dest="LESUp",default=False,help="Scale up lepton energies")

parser.add_option("--LESDown",action="store_true",dest="LESDown",default=False,help="Scale Down lepton energies")

(options, args) = parser.parse_args()

systs = [options.jerUFlag,options.jerDFlag,options.jesUFlag,options.jesDFlag,options.btagUFlag,options.btagDFlag,options.puUFlag,options.puDFlag,options.metUFlag,options.metDFlag,options.lepSFUFlag,options.lepSFDFlag,options.zPlusJetsUp,options.zPlusJetsDown,options.LESUp,options.LESDown]

print systs

datasets = []

config = ConfigParser.RawConfigParser()

plotConf = ConfigParser.RawConfigParser()

plots = []

# print options.plotConfig

if options.plotConfig:

plotConf.read(options.plotConfig)

plots = plotConf.sections()

#config file will contain a list of sections that each correspond to a dataset

if options.configFile:

config.read(options.configFile)

datasets = config.sections()

sampleNamesForPlots = ['tW','zPlusJets','ttbar','other', 'data']

cutFlowStages = ["lepSel","lepMass","MET","1jet","btag","Ht","1j1t","2j1t","2j2t"]

plotList = {}

if options.eventDumpFlag:

eventDumpFiles = {}

for dataset in datasets:

eventDumpFiles[dataset] = {}

for region in ['1j1t','2j1t','2j2t']:

eventDumpFiles[dataset][region] = open("eventDumpLists/"+dataset+"_"+region + "_eventDump.txt","w")

for plot in plots:

plotList[plot] = {}

for stage in cutFlowStages:

plotList[plot][stage] = {}

for sample in sampleNamesForPlots:

plotList[plot][stage][sample] = TH1F(sample + "_" + plot + "_" + stage, sample + "_" + plot + "_" + stage, int(plotConf.get(plot,"bins")),float(plotConf.get(plot,"minX")),float(plotConf.get(plot,"maxX")) )

#Initialise the one bin histograms here.

regionNames = ['1j1t','2j1t','2j2t']

sampleNames = ['twdr','tt','other','DATA']

systematicName = ""

lesFlag = 0

upDown = ""

if systs[0]:

systematicName = "JER"

upDown = "plus"

elif systs[1]:

systematicName = "JER"

upDown = "minus"

elif systs[2]:

systematicName = "JES"

upDown = "plus"

elif systs[3]:

systematicName = "JES"

upDown = "minus"

elif systs[4]:

systematicName = "BtagSF"

upDown = "plus"

elif systs[5]:

systematicName = "BtagSF"

upDown = "minus"

elif systs[6]:

systematicName = "PU"

upDown = "plus"

elif systs[7]:

systematicName = "PU"

upDown = "minus"

elif systs[8]:

systematicName = "UnclusteredMET"

upDown = "plus"

elif systs[9]:

systematicName = "UnclusteredMET"

upDown = "minus"

elif systs[10]:

systematicName = "lepSF"

upDown = "plus"

elif systs[11]:

systematicName = "lepSF"

upDown = "minus"

elif systs[12]:

systematicName = "zJetsSF"

upDown = "plus"

elif systs[13]:

systematicName = "zJetsSF"

upDown = "minus"

elif systs[14]:

systematicName = "LES"

upDown = "plus"

lesFlag = 1

elif systs[15]:

systematicName = "LES"

lesFlag = 2

upDown = "minus"

oneBinHistos = {}

histoPostfix = ""

if upDown == "plus" or upDown == "minus":

histoPostfix = "__" + systematicName + "__" + upDown

if not options.obhPostfix == "":

histoPostfix = options.obhPostfix

for sample in sampleNames:

oneBinHistos[sample] = {}

for region in regionNames:

oneBinHistos[sample][region] = TH1F(options.cutMode + region + "__" + sample + histoPostfix,options.cutMode + region + "__" + sample + histoPostfix,1,0.5,1.5)

#oneBinHistos[sample][region].Sumw2()

oneBinHistosFilled = {}

for sample in sampleNames:

oneBinHistosFilled[sample] = False

cutFlows = {}

for dataset in ['data','tW','ttbar','zPlusJets','other']:

cutFlows[dataset]=TH1F(dataset+"_cutFlow_"+options.cutMode,dataset+"_cutFlow_"+options.cutMode,6,1,7)

regionPlots = {}

for dataset in ['data','tW','ttbar','zPlusJets','other']:

regionPlots[dataset]=TH1F(dataset+"_regionPlot_"+options.cutMode,dataset+"_regionPlot_"+options.cutMode,3,1,4)

#Add in some extra one bin histograms only if doing top pt reweighting

ttbarSystHist = {}

if options.ttbarFlag:

for region in regionNames:

ttbarSystHist[region] = {}

ttbarSystHist[region]["plus"] = TH1F(options.cutMode + region + "__tt__topPt__plus",options.cutMode + region + "__tt__topPt__plus",1,0.5,1.5)

ttbarSystHist[region]["minus"] = TH1F(options.cutMode + region + "__tt__topPt__minus",options.cutMode + region + "__tt__topPt__minus",1,0.5,1.5)

totalLumi = 0.

lumiA = 0.

lumiB = 0.

lumiC = 0.

lumiA = 808.472 + 82.136

if not options.lumiSpecified:

if options.cutMode == "mumu":

lumiB = 4426.

else:

lumiB = 4429.

if options.cutMode == "emu":

lumiC = 495.003 + 6401.

else:

lumiC = 486.186 + 6396.

if options.cutMode == "ee":

lumiC = 486.168 + 6401.

#If running over a specific nrun range set the lumi here so MC is properly normalised.oith three, Rockstar has the flexibility to move between them to pace the both story and the gameplay. Seeing Michael beat up a bunch of gang members with a baseball bat might not gel too well with the reformed-gangster-trying-to-be-good that we see in his cutscenes, but Trevor after a few too many whiskies? I can definitely imagine that.

totalLumi = lumiA + lumiB + lumiC

# for dataset in datasets:

# if config.get(dataset,'runType') == 'mc':continue

# totalLumi += float(config.get(dataset,"luminosity"))

# if 'A13Jul' in dataset or 'A06Aug' in dataset:

# lumiA += float(config.get(dataset,"luminosity"))

# if 'B13Jul' in dataset:

# lumiB += float(config.get(dataset,"luminosity"))

# if 'C24Aug' in dataset or 'CPrompt' in dataset:

# lumiC += float(config.get(dataset,"luminosity"))

#Set up reweighting of pileup if using the data-driven distributions

pileupA, pileupB, pileupC = 0 ,0,0#These two are used by both reweighting and systematic options, so are left outside the if statements.

mcName = "pileupHistos/pileup_MC_Summer12.root"

getNPV = PileupReweighting("pileupHistos/run2012A_13Jul.root","pileupHistos/pileup_MC_Summer12.root")

if options.reweightPileup:

pileupA = PileupReweighting("pileupHistos/systematics/run2012A_13Jul.root",mcName)

pileupB = PileupReweighting("pileupHistos/systematics/run2012B_13Jul.root",mcName)

pileupC = PileupReweighting("pileupHistos/systematics/run2012C_v2.root",mcName)

#dummy variables for pileup systematic.

pileupAUp, pileupBUp, pileupCUp,pileupADown, pileupBDown, pileupCDown = 0,0,0,0,0,0

if systs[6] or systs[7]: #set up pile-up histograms. Will need these to get npv later on.

#Initialise pileup reweighting stuff.

pileupAUp = PileupReweighting("pileupHistos/systematics/run2012A_13Jul_Up.root",mcName)

pileupBUp = PileupReweighting("pileupHistos/systematics/run2012B_13Jul_Up.root",mcName)

pileupCUp = PileupReweighting("pileupHistos/systematics/run2012C_v2_Up.root",mcName)

pileupADown = PileupReweighting("pileupHistos/systematics/run2012A_13Jul_Down.root",mcName)

pileupBDown = PileupReweighting("pileupHistos/systematics/run2012B_13Jul_Down.root",mcName)

pileupCDown = PileupReweighting("pileupHistos/systematics/run2012C_v2_Down.root",mcName)

jecUnc = 0

jecUnc = JetCorrectionUncertainty("JESscaleFactors.txt")

#This is here in case I ned the eta dependent scale factor. Hopefully I won't, as the other way is far easier.

# lepSFs = 0

# dataFilelepsf = ""

# if options.cutMode == "ee":

# dataFilelepsf = "trigger_SF_ee.root"

## elif options.cutMode == "emu":

# dataFilelepsf = "trigger_SF_emu.root"

# elif options.cutMode == "mumu":

# dataFilelepsf = "trigger_SF_mumu.root"

#

# lepSFs = leptonSF(dataFilelepsf)

leptonScaleFactor = 1.0

if options.cutMode == "ee":

leptonScaleFactor *= (0.9623 * 0.9623 * 0.975)

if systs[10]:

leptonScaleFactor += 0.021

if systs[11]:

leptonScaleFactor -= 0.021

elif options.cutMode == "emu":

leptonScaleFactor *= (0.9623 * 0.999 * 0.953)

if systs[10]:

leptonScaleFactor += .017

if systs[11]:

leptonScaleFactor -= .017

elif options.cutMode == "mumu":

leptonScaleFactor *= (0.999 * 0.999 * 0.965)

if systs[10]:

leptonScaleFactor += 0.022

if systs[11]:

leptonScaleFactor -= 0.022

foundCount = {}

foundCountWeighted = {}

for dataset in datasets:

if options.dataFlag and config.get(dataset,"runType") == "mc" : continue

if options.mcFlag and config.get(dataset,"runType") == "data" : continue

#Here I will build a TChain for each dataset I guess, coz it looks like that might make this work better.

tree = TChain("tree")

files = open(config.get(dataset,"fileName"),"r")

for file in files:

tree.Add(file[:-1])

if not options.skimSaveFile == "":

outFile = TFile("/data0/tW2012/" + options.skimSaveFile + options.cutMode + "_" + dataset + "_fullSkim.root","RECREATE")

outTree = tree.CloneTree(0)

weight = 1.0

numberOfAcceptedEvents = 0

ttbarWeight = 1.0

#If processing top pt reweighted events, find the overall weight here.

if options.ttbarFlag:

ttbarFiles = open(config.get(dataset,"fileName"),"r")

ttbarTopWeight = 0.

totalEvents = 0

for file in ttbarFiles:

tempFile = TFile(file[:-1],"READ")

ttbarTopWeight += (tempFile.Get("topPtWeightSum")).GetBinContent(1)

totalEvents += (tempFile.Get("eventcount")).GetBinContent(1)

ttbarWeight = ttbarTopWeight / float(totalEvents)

print "Average ttbar weight: {0}".format(ttbarWeight)

print dataset

if config.get(dataset,"runType") == 'mc':

if 'tW' in dataset or 'tbarW' in dataset:

regionPlotName = 'tW'

sampleName = 'twdr'

elif 'zPlusJets' in dataset:

regionPlotName = 'zPlusJets'

sampleName = 'other'

elif 'ttbar' in dataset:

regionPlotName = 'ttbar'

sampleName = 'tt'

else :

regionPlotName = 'other'

sampleName = 'other'

weight = totalLumi * float(config.get(dataset,"crossSection")) / (float(config.get(dataset,"totalEvents")) * ttbarWeight)

print "Dataset {0} contains {1} events, cross sections of {2} and therefore a weight of {3}".format(dataset,config.get(dataset,"totalEvents"),config.get(dataset,"crossSection"),weight)

oneBinHistosFilled[sampleName] = True

if config.get(dataset,"runType") == 'data':

weight = 1.0

regionPlotName = 'data'

sampleName = 'DATA'

oneBinHistosFilled["DATA"] = True

runType = config.get(dataset,"runType")

cutFlowMode = options.cutMode

foundCount[dataset] = 0

foundCountWeighted[dataset]=0

for i in range(tree.GetEntries()):

sys.stdout.write("\rProcessing event: {0} [{1:.1%}] Found {2} events, weighted at {3:.2f}".format(str(i) +"/" + str(tree.GetEntries()),(i * 1.) / tree.GetEntries(),foundCount[dataset],foundCountWeighted[dataset]))

sys.stdout.flush()

tree.GetEntry(i)

eventWeight = weight

if (config.get(dataset,"runType")) == 'mc':

pileupweight = 1.0

#This is decide whether to use the nominal pileup distributions (the ones I've been using) or the data-driven ones I got from Danny.

if not options.reweightPileup:

pileupweight = (tree.PileUpWeightRunA * lumiA + tree.PileUpWeightRunB * lumiB + tree.PileUpWeightRunC * lumiC) / totalLumi

else:

npv = getNPV.getNpv(tree.PileUpWeightRunA)

pileupweight = (pileupA.weight(npv) * lumiA + pileupB.weight(npv) * lumiB + pileupC.weight(npv) * lumiC) / totalLumi

puUD = 0

if systs[6] or systs[7]:

if systs[6]:

pileupweight = (pileupAUp.weight(npv) * lumiA + pileupBUp.weight(npv) * lumiB + pileupCUp.weight(npv) * lumiC) / totalLumi

else:

pileupweight = (pileupADown.weight(npv) * lumiA + pileupBDown.weight(npv) * lumiB + pileupCDown.weight(npv) * lumiC) / totalLumi

# pileupweight *= pileupSystWeight(tree.PileUpWeightRunA,puA,puUD)

eventWeight *= pileupweight

eventWeight *= leptonScaleFactor

if options.ttbarFlag:

eventWeight *= tree.topPtReweight

if 'zPlusJets' in dataset:

zWeight = getZWeight(options.cutMode,tree) - 1

# print "\n",getZWeight(options.cutMode,tree),zWeight, eventWeight,

if systs[12]:

zWeight *= 2.

if systs[13]:

zWeight = 0.

# print zWeight,

eventWeight *= 1 + zWeight

# print eventWeight

if config.get(dataset,"runType") == 'data' and not passesTrigger(tree,options.cutMode,dataset): continue

# print plotList

# print plots

if makeCuts(options.cutMode,config.get(dataset,"runType"),tree,systs,True,cutFlows[regionPlotName],eventWeight,jecUnc,plotList,regionPlotName,plotConf,LESFlag=lesFlag):

outTree.Fill()

jerUD = 0

if systs[0]:

jerUD = 1

if systs[1]:

jerUD = 2

jesUD = 0

if systs[2]:

jesUD = 1

if systs[3]:

jesUD = 2

bTagUD = 0

if systs[4]:

bTagUD = 1

if systs[5]:

bTagUD = 2

(jets,tags)=jetRegion(tree,config.get(dataset,"runType"),jerUD,jesUD,jecUnc,bTagUD = bTagUD)

(lepton1,lepton2) = makeLeptonCuts(options.cutMode,config.get(dataset,"runType"),tree,True,LESSyst=lesFlag)

pxsys = 0.

pysys = 0.

htSys = 0.

for i in range(len(jets)):

jetPx = tree.jetPF2PATPx[i]

jetPy = tree.jetPF2PATPy[i]

if config.get(dataset,"runType") == 'mc':

(jetPx,jetPy) = calcJERJetCorr(tree,jets[i],jerUD)

#jetPy = calcJERJetCorr(tree,jets[i],jerUD)[1]

jesUncertainty = jecUnc.getUncertainty(sqrt(jetPx*jetPx + jetPy * jetPy),tree.jetPF2PATEta[i],jesUD)

if jesUD == 1:

jetPx *= (1+jesUncertainty)

jetPy *= (1+jesUncertainty)

elif jesUD == 2:

jetPx *= (1-jesUncertainty)

jetPy *= (1-jesUncertainty)

pxsys += jetPx

pysys += jetPy

htSys += sqrt(jetPx * jetPx + jetPy * jetPy)

pxsys += lepton1.Px() + lepton2.Px()

pysys += lepton1.Py() + lepton2.Py()

htSys += lepton1.Pt() + lepton2.Pt()

eventMetx = tree.metPF2PATPx

eventMety = tree.metPF2PATPy

if config.get(dataset,"runType") == 'mc':

if systs[8] or systs[9]:

uncmetx = tree.metPF2PATPx

uncmety = tree.metPF2PATPy

for i in range(tree.numElePF2PAT):

uncmetx += getLeptonPt(tree,i,True,LES=lesFlag,direction="PX")

uncmety += getLeptonPt(tree,i,True,LES=lesFlag,direction="PY")

for i in range(tree.numMuonPF2PAT):

uncmetx += getLeptonPt(tree,i,False,LES=lesFlag,direction="PX")

uncmety += getLeptonPt(tree,i,False,LES=lesFlag,direction="PY")

for i in range(tree.numJetPF2PAT):

uncmetx += tree.jetPF2PATPx[i]

uncmety += tree.jetPF2PATPy[i]

if systs[8]:

eventMetx += uncmetx*0.1

eventMety += uncmety*0.1

if systs[9]:

eventMetx -= uncmetx*0.1

eventMety -= uncmety*0.1

if systs[0] or systs[1]:

if systs[0]:

metUD = 1

else:

metUD = 2

(eventMetx,eventMety) = calcMETforJER(eventMetx,eventMety,tree,metUD)

if systs[2] or systs[3]:

if systs[2]:

jesUD = 1

else:

jesUD = 2

(eventMetx,eventMety) = jecUnc.getMetAfterJESUnc(eventMetx,eventMety,tree,jesUD)

pxsys += eventMetx

pysys += eventMety

htSys += sqrt(eventMetx * eventMetx + eventMety * eventMety)

#Fill in the one bin histograms.

if len(jets) == 1 and looseJets(tree,config.get(dataset,"runType"),jerUD,jesUD,jecUnc) == 1 and len(tags) and (htSys > 160. or not options.cutMode == "emu") :

if options.eventDumpFlag:

eventDumpFiles[dataset]["1j1t"].write(str(tree.eventRun)+","+str(tree.eventLumiblock)[:-2]+","+str(tree.eventNum)+"\n")

oneBinHistos[sampleName]['1j1t'].Fill(1.,eventWeight)

foundCount[dataset]+=1

foundCountWeighted[dataset]+=eventWeight

regionPlots[regionPlotName].Fill(1,eventWeight)

if options.ttbarFlag:

ttbarSystHist['1j1t']["minus"].Fill(1.,eventWeight/tree.topPtReweight)

tempWeight = tree.topPtReweight - 1

ttbarSystHist['1j1t']["plus"].Fill(1.,eventWeight*((1 + (2. * tempWeight))/(1+tempWeight)))

# print " ",eventWeight, tree.topPtReweight, eventWeight*((1 + (2. * tempWeight))/(1+tempWeight)), eventWeight/tree.topPtReweight

for plot in plots:

plotList[plot]['1j1t'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

if len(jets) == 2 and len(tags) == 1 and (htSys > 160. or not options.cutMode == "emu"):

if options.eventDumpFlag:

eventDumpFiles[dataset]["2j1t"].write(str(tree.eventRun)+","+str(tree.eventLumiblock)[:-2]+","+str(tree.eventNum)+"\n")

oneBinHistos[sampleName]['2j1t'].Fill(1.,eventWeight)

regionPlots[regionPlotName].Fill(2,eventWeight)

if options.ttbarFlag:

ttbarSystHist['2j1t']["minus"].Fill(1.,eventWeight/tree.topPtReweight)

tempWeight = tree.topPtReweight - 1

ttbarSystHist['2j1t']["plus"].Fill(1.,eventWeight*((1 + (2. * tempWeight))/(1+tempWeight)))

for plot in plots:

plotList[plot]['2j1t'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

if len(jets) == 2 and len(tags) == 2 and (htSys > 160. or not options.cutMode == "emu"):

if options.eventDumpFlag:

eventDumpFiles[dataset]["2j2t"].write(str(tree.eventRun)+","+str(tree.eventLumiblock)[:-2]+","+str(tree.eventNum)+"\n")

oneBinHistos[sampleName]['2j2t'].Fill(1.,eventWeight)

regionPlots[regionPlotName].Fill(3,eventWeight)

if options.ttbarFlag:

ttbarSystHist['2j2t']["minus"].Fill(1.,eventWeight/tree.topPtReweight)

tempWeight = tree.topPtReweight - 1

ttbarSystHist['2j2t']["plus"].Fill(1.,eventWeight*((1 + (2. * tempWeight))/(1+tempWeight)))

for plot in plots:

plotList[plot]['2j2t'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

if not len(jets) == 1: continue

if not looseJets(tree,config.get(dataset,"runType"),jerUD,jesUD,jecUnc) == 1: continue

cutFlows[regionPlotName].Fill(4,eventWeight)

for plot in plots:

plotList[plot]['1jet'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

if not len(tags) == 1:continue

cutFlows[regionPlotName].Fill(5,eventWeight)

for plot in plots:

plotList[plot]['btag'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

# if not options.cutMode == "emu" or lepton1.Pt() + lepton2.Pt() + tree.metPF2PATEt + tree.jetPF2PATPt[jets[0]] > 160.:

if not options.cutMode == "emu" or htSys > 160.:

numberOfAcceptedEvents += 1

cutFlows[regionPlotName].Fill(6,eventWeight)

for plot in plots:

plotList[plot]['Ht'][regionPlotName].Fill(float(eval(plotConf.get(plot,'fillExp'))),eventWeight)

# print numberOfAcceptedEvents

# for i in range(7):

# print cutFlows[regionPlotName].GetBinContent(i)

if not options.skimSaveFile == "":

outFile.Write()

# inputFile.Close()

# outFile.Write()

outFile.Close()

for sample in sampleNames:

if not oneBinHistosFilled[sample]: continue

for region in regionNames:

print oneBinHistos[sample][region],

print oneBinHistos[sample][region].GetBinContent(1),

print oneBinHistos[sample][region].GetBinError(1),

oneBinHistos[sample][region].Sumw2()

print oneBinHistos[sample][region].GetBinError(1)

oneBinHistos[sample][region].SaveAs(options.sysOut + options.cutMode + region + "__" + sample + histoPostfix+".root")

#Save thye ttbar histograms, if necessary

if options.ttbarFlag:

for region in regionNames:

for key in ttbarSystHist[region].keys():

ttbarSystHist[region][key].SaveAs(options.sysOut + options.cutMode + region + "__tt__topPt__"+key+".root")

if systs[2] or systs[3]:

jecUnc.savePlot(options.outFolder + options.cutMode)

#These could probably end up in configuration file at some point. Would

#make my life easier in the long run.

distributionOutFile = TFile(options.outFolder + "rawInfo" + options.cutMode + options.postfix + ".root","RECREATE")

distributionOutFile.cd()

for dataset in sampleNamesForPlots:

cutFlows[dataset].Write()

distributionOutFile.Close()

distNames = ["data","other","zPlusJets","ttbar","tW"]

colourScheme = {"other":kGreen-3,"zPlusJets":kAzure-2,"ttbar":kRed+1}

legendOrder = ["data","tW","ttbar","zPlusJets","other"]

legMap = {"data":("Data","p"),"tW":("tW","f"),"ttbar":('t#bar{t}','f'),"zPlusJets":('Z/#gamma*+jets',"f"),"other":("Other","f")}

#legMap = {"other":("Other","f"),"zPlusJets":('Z/#gamma*+jets',"f"),"ttbar":('t#bar{t}','f'),"tW":("tW","f"),"data":("Data","p")}

labelText1 = "CMS Preliminary, #sqrt{s} = 8TeV"

modeStringForPlot = ""

if options.cutMode == "ee":

modeStringForPlot = "ee"

if options.cutMode == "emu":

modeStringForPlot = "e#mu"

if options.cutMode == "mumu":

modeStringForPlot = "#mu#mu"

labelText2 = "12.2 fb^{-1}, " + modeStringForPlot + " channel"

#create the plotting object

cutFlowPlotter = HistogramPlotter(distNames,colourScheme,legMap,labelText1,labelText2, options.outFolder, options.postfix, options.cutMode, legendOrderList = legendOrder)

xBinNames = ["","Lepton Selection","m_{ll}","E_{T}^{miss}","1 jet","b-tag","H_{T}"]

cutFlowPlotter.makePlot(cutFlows,"CutFlow", "Cut Stage", xBinLabels = xBinNames)

xBinForRegions = ["","1j1t","2j1t","2j2t"]

cutFlowPlotter.makePlot(regionPlots,"RegionPlot","Region Plot", xBinLabels = xBinForRegions)

for plot in plots:

for stage in cutFlowStages:

cutFlowPlotter.makePlot(plotList[plot][stage], plot, plotConf.get(plot,"xAxisLabel"),subLabel = stage)

for key in foundCount.keys():

gROOT.SetBatch()

gStyle.SetOptStat(0)

gStyle.SetOptTitle(0)

gStyle.SetErrorX(0)

setTDRStyle()

labelcms = TPaveText(0.12,0.88,0.5,0.94,"NDCBR")

labelcms.SetTextAlign(12)

labelcms.SetTextSize(0.045)

labelcms.SetFillColor(kWhite)

labelcms.AddText("CMS Preliminary, #sqrt{s} = 8 TeV")

labelcms.SetBorderSize(0)

labelcms2 = TPaveText(0.12,0.85,0.5,0.88,"NDCBR")

labelcms2.SetTextAlign(12)

labelcms2.SetTextSize(0.045)

labelcms2.SetFillColor(kWhite)

if options.cutMode == "ee":

labelcms2.AddText("12.2 fb^{-1}, ee channel")

if options.cutMode == "emu":

labelcms2.AddText("12.2 fb^{-1}, e#mu channel")

if options.cutMode == "mumu":

labelcms2.AddText("12.2 fb^{-1}, #mu#mu channel")

# labelcms2.AddText("12.2 fb^{-1}, ee,e#mu,#mu#mu channels")

labelcms2.SetBorderSize(0)

gStyle.SetPalette(1)

gStyle.SetCanvasBorderMode(0)

gStyle.SetCanvasColor(kWhite)

gStyle.SetCanvasDefH(600)

gStyle.SetCanvasDefW(600)

gStyle.SetLabelFont(18,"")

gStyle.SetTitleXOffset(1.2)

gStyle.SetTitleYOffset(1.2)

mcDists = THStack("mcDists", "MC Distributions")

cutFlows['other'].SetFillColor(kGreen-3)

cutFlows['other'].SetLineColor(kBlack)

mcDists.Add(cutFlows['other'])

cutFlows['zPlusJets'].SetFillColor(kAzure-2)

cutFlows['zPlusJets'].SetLineColor(kBlack)

mcDists.Add(cutFlows['zPlusJets'])

cutFlows['ttbar'].SetFillColor(kRed+1)

cutFlows['ttbar'].SetLineColor(kBlack)

mcDists.Add(cutFlows['ttbar'])

cutFlows['tW'].SetLineColor(kBlack)

mcDists.Add(cutFlows['tW'])

canvy = TCanvas("Control Region Plots", "Control Region Plots")

canvy.cd()

leg = TLegend(0.7,0.7,0.94,0.94)

leg.SetFillStyle(1001)

leg.SetFillColor(kWhite)

leg.SetBorderSize(1)

leg.AddEntry(cutFlows['data'], 'Data', 'p')

leg.AddEntry(cutFlows['tW'], 'tW','f')

leg.AddEntry(cutFlows['ttbar'], 't#bar{t}','f')

leg.AddEntry(cutFlows['zPlusJets'], 'Z/#gamma*+jets','f')

leg.AddEntry(cutFlows['other'], 'Other','f')

cutFlows['data'].SetMarkerStyle(20)

cutFlows['data'].SetMarkerSize(1.2)

cutFlows['data'].SetLineWidth(1)

cutFlows['data'].SetMarkerColor(kBlack)

cutFlows['data'].SetLineColor(kBlack)

max = TMath.Max(mcDists.GetMaximum(), cutFlows['data'].GetMaximum())

mcDists.Draw('')

mcDists.SetMaximum(max * 1.2)

mcDists.SetMinimum(0)

mcDists.GetXaxis().SetBinLabel(1,"Lepton Selection")

mcDists.GetXaxis().SetBinLabel(2,"m_{ll}")

mcDists.GetXaxis().SetBinLabel(3,"E_{T}^{miss}")

mcDists.GetXaxis().SetBinLabel(4,"1 jet")

mcDists.GetXaxis().SetBinLabel(5,"b-tag")

mcDists.GetXaxis().SetBinLabel(6,"H_{T}")

mcDists.GetYaxis().SetTitle("events / 12.2 fb^{-1}")

mcDists.GetYaxis().CenterTitle()

cutFlows['data'].Draw("e, sames")

leg.Draw()

labelcms.Draw()

labelcms2.Draw()

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + ".png")

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + ".pdf")

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + ".root")

mcDists.SetMinimum(1)

mcDists.SetMaximum(10*max)

canvy.SetLogy()

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + "_log.png")

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + "_log.pdf")

canvy.SaveAs(options.outFolder + "cutFlow_" + options.cutMode + options.postfix + "_log.root")

canvy.SetLogy(0)

hextra =TH1F( cutFlows['other'].Clone())

hextra.Add(cutFlows['zPlusJets'])

hextra.Add(cutFlows['ttbar'])

hextra.Add(cutFlows['tW'])

hextra.Sumw2()

setex2 = TExec("setex2","gStyle.SetErrorX(0.5)")

setex2.Draw()

hextra.Sumw2()

GE = TGraphAsymmErrors(hextra)

GE.SetFillColor(28)

GE.SetFillStyle(3018)

GE.SetMarkerSize(0)

GE.SetLineWidth(0)

GE.SetLineColor(kWhite)

leg.AddEntry(GE,"uncertainty","f")

mcDists.SetMaximum(max*1.2)

mcDists.SetMinimum(0)

GE.Draw("sames, e2")

setex1 = TExec("setex1","gStyle.SetErrorX(0)")

setex1.Draw()

cutFlows['data'].Draw("e, sames")

canvy.SaveAs(options.outFolder + "error_cutFlow_" + options.cutMode + options.postfix + ".png")

canvy.SaveAs(options.outFolder + "error_cutFlow_" + options.cutMode + options.postfix + ".pdf")

canvy.SaveAs(options.outFolder + "error_cutFlow_" + options.cutMode + options.postfix + ".root")

mcDists.SetMaximum(max * 10)

mcDists.SetMinimum(1)

canvy.SetLogy()

canvy.SaveAs(options.outFolder + "error_cutFlow_" + options.cutMode + options.postfix + "_log.png")

canvy.SaveAs(options.outFolder + "error_cutFlow_" + options.cutMode + options.postfix + "_log.pdf")