def makeControlSampleHists(regionName="TTJetsSingleLepton", filenames={}, samples=[], cutsMC="", cutsData="", bins={}, logX=True, lumiMC=1, lumiData=3000, weightHists={}, sfHists={}, treeName="ControlSampleEvent",dataName="Data", weightOpts=["doPileupWeights", "doLep1Weights", "do1LepTrigWeights"], shapeErrors=[], debugLevel=0):
#setup files and trees
inputs = filenames
files = {name:rt.TFile.Open(inputs[name]) for name in inputs} #get input files
for name in inputs:
assert files[name] #check input files
if debugLevel > 0: print "Opened file",inputs[name]
trees = macro.makeTreeDict(files, treeName, debugLevel)
#define histograms to fill
hists = {name:{} for name in inputs}
shapeHists = {name:{} for name in inputs}
for name in inputs:
#1D histograms
for var in bins:
if var in titles: title=titles[var]
else: title = var
hists[name][var] = rt.TH1F(regionName+var+name, title, len(bins[var])-1, array('d',bins[var]))
#add up/down histograms for each systematic uncertainty
if name in samples:
for shape in shapeErrors:
if shape+"Down" not in shapeHists[name]: shapeHists[name][shape+"Down"] = {}
if shape+"Up" not in shapeHists[name]: shapeHists[name][shape+"Up"] = {}
shapeHists[name][shape+"Down"][var] = hists[name][var].Clone(hists[name][var].GetName()+shape+"Down")
shapeHists[name][shape+"Up"][var] = hists[name][var].Clone(hists[name][var].GetName()+shape+"Up")
#2D MR-Rsq histogram
if "MR" in bins and "Rsq" in bins:
hists[name][("MR","Rsq")] = rt.TH2F(regionName+"MRRsq"+name, "R^{2} vs M_{R}", len(bins["MR"])-1, array('d',bins["MR"]), len(bins["Rsq"])-1, array('d',bins["Rsq"]))
if name in samples:
for shape in shapeErrors:
shapeHists[name][shape+"Down"][("MR","Rsq")] = hists[name][("MR","Rsq")].Clone(hists[name][("MR","Rsq")].GetName()+shape+"Down")
shapeHists[name][shape+"Up"][("MR","Rsq")] = hists[name][("MR","Rsq")].Clone(hists[name][("MR","Rsq")].GetName()+shape+"Up")
for var in hists[name]:
hists[name][var].Sumw2()
hists[name][var].SetDirectory(0)
if name in samples:
for shape in shapeErrors:
shapeHists[name][shape+"Down"][var].Sumw2()
shapeHists[name][shape+"Up"][var].Sumw2()
shapeHists[name][shape+"Down"][var].SetDirectory(0)
shapeHists[name][shape+"Up"][var].SetDirectory(0)
listOfVars = hists.itervalues().next().keys() #list of the variable names
#fill histograms
print("\nData:")
macro.loopTree(trees[dataName], weightF=weight_data, cuts=cutsData, hists=hists[dataName], weightHists=weightHists, weightOpts=[], debugLevel=debugLevel)
print("\nMC:")
macro.loopTrees(trees, weightF=weight_mc, cuts=cutsMC, hists={name:hists[name] for name in samples}, weightHists=weightHists, sfHists=sfHists, scale=lumiData*1.0/lumiMC, weightOpts=weightOpts, debugLevel=debugLevel)
#get up/down histogram variations
for shape in shapeErrors:
print "\n"+shape,"Up:"
macro.loopTrees(trees, weightF=weight_mc, cuts=cutsMC, hists={name:shapeHists[name][shape+"Up"] for name in samples}, weightHists=weightHists, sfHists=sfHists, scale=lumiData*1.0/lumiMC, weightOpts=weightOpts, errorOpt=shape+"Up", debugLevel=debugLevel)
print "\n"+shape,"Down:"
macro.loopTrees(trees, weightF=weight_mc, cuts=cutsMC, hists={name:shapeHists[name][shape+"Down"] for name in samples}, weightHists=weightHists, sfHists=sfHists, scale=lumiData*1.0/lumiMC, weightOpts=weightOpts, errorOpt=shape+"Down", debugLevel=debugLevel)
#propagate up/down systematics to central histograms
for name in samples:
for var in bins:
for shape in shapeErrors:
if debugLevel > 0: print "Adding",shape,"uncertainty in quadrature with",name,"errors for",var
#loop over histogram bins
for bx in range(1, hists[name][var].GetNbinsX()+1):
#use difference between Up and Down histograms as uncertainty
sysErr = abs(shapeHists[name][shape+'Up'][var].GetBinContent(bx) - shapeHists[name][shape+'Down'][var].GetBinContent(bx))
#add in quadrature with existing error
oldErr = hists[name][var].GetBinError(bx)
hists[name][var].SetBinError(bx, (oldErr**2 + sysErr**2)**(0.5))
if debugLevel > 1: print "Error on bin ",bx,"increases from",oldErr,"to",hists[name][var].GetBinError(bx)
#2D case
if "MR" in bins and "Rsq" in bins:
for shape in shapeErrors:
if debugLevel > 0: print "Adding",shape,"uncertainty in quadrature with",name,"errors for razor histogram"
#loop over histogram bins
for bx in range(1, hists[name][("MR","Rsq")].GetNbinsX()+1):
for by in range(1, hists[name][("MR","Rsq")].GetNbinsY()+1):
#use difference between Up and Down histograms as uncertainty
sysErr = abs(shapeHists[name][shape+'Up'][("MR","Rsq")].GetBinContent(bx,by) - shapeHists[name][shape+'Down'][("MR","Rsq")].GetBinContent(bx,by))
#add in quadrature with existing error
oldErr = hists[name][("MR","Rsq")].GetBinError(bx,by)
hists[name][("MR","Rsq")].SetBinError(bx,by, (oldErr**2 + sysErr**2)**(0.5))
if debugLevel > 1: print "Error on bin (",bx,by,") increases from",oldErr,"to",hists[name][("MR","Rsq")].GetBinError(bx,by)
#print histograms
c = rt.TCanvas(regionName+"c", regionName+"c", 800, 600)
rt.SetOwnership(c, False)
macro.basicPrint(hists, mcNames=samples, varList=listOfVars, c=c, printName=regionName, logx=logX, dataName=dataName, ymin=0.1, lumistr=str(lumiData)+" pb^{-1}")
#close files and return
for f in files: files[f].Close()
return hists
files = {name:rt.TFile.Open(inputs[name]) for name in inputs} #get input files
for name in inputs: assert files[name] #check input files
hists = {name:{} for name in inputs}
for name in inputs:
files[name] = rt.TFile.Open(inputs[name])
#load trees
trees = macro.makeTreeDict(files, "ControlSampleEvent", debug)
#load weight histograms
weightHists = macro.loadWeightHists(debug)
#define histograms to fill
for name in hists:
hists[name]["MR"] = rt.TH1F("MR"+name, "M_{R} (GeV)", 20, 300, 4000)
hists[name]["Rsq"] = rt.TH1F("Rsq"+name, "R^{2}", 20, 0.15, 1.5)
for var in hists[name]:
hists[name][var].Sumw2()
#fill histograms
print("MC:")
macro.loopTrees(trees, cuts_TTJetsSingleLepton, weight_mc, weightHists, Fill, {name:hists[name] for name in hists if name != "Data"}, maxEvents=maxEvents, scale=LUMI*1.0/MCLUMI, debug=debug) #MC
print("Data:")
macro.loopTree(trees["Data"], cuts_TTJetsSingleLepton, weight_data, {}, Fill, hists["Data"], debug=debug) #Data
#print histograms
c = rt.TCanvas("c", "c", 800, 600)
Print(hists, c)
#close files
print("Cleaning up")
for f in files: files[f].Close()