def __init__(self, directory, filenames, isData):
self.dataPlotters = []
sampleTypes = filenames.split(',')
for filename in os.listdir(directory):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
self.dataPlotters.append(
TreePlotter(directory + '/' + fname + '.root', 'tree'))
if not isData:
self.dataPlotters[-1].setupFromFile(directory + '/' +
fname + '.pck')
self.dataPlotters[-1].addCorrectionFactor(
'xsec', 'tree')
self.dataPlotters[-1].addCorrectionFactor(
'genWeight', 'tree')
self.dataPlotters[-1].addCorrectionFactor(
'puWeight', 'tree')
self.plotter = MergedPlotter(self.dataPlotters)
cuts['b'] = '(lnujj_nMediumBTags>0)*lnujj_btagWeight'
cuts['resW']='(lnujj_l2_mergedVTruth==1)'
cuts['nonres']='(lnujj_l2_mergedVTruth==0)'
#change the CMS_lumi variables (see CMS_lumi.py)
lumi_13TeV = "35.9 fb^{-1}"
lumi_sqrtS = "13 TeV" # used with iPeriod = 0, e.g. for simulation-only plots (default is an empty string)
iPeriod=4
iPos = 11
#zjPlotters=[]
VJetsPlotters = getPlotters('DYJetsToLL_M50_HT,WJetsToLNu_HT',False)
VJets = MergedPlotter(VJetsPlotters)
TTVVPlotters = getPlotters('TT_pow,T_tWch,TBar_tWch,WWTo1L1Nu2Q,WZTo1L1Nu2Q',False)
ttVV=MergedPlotter(TTVVPlotters)
BKGPlotters = getPlotters('DYJetsToLL_M50_HT,WJetsToLNu_HT,TT_pow,T_tWch,TBar_tWch,WWTo1L1Nu2Q,WZTo1L1Nu2Q',False,cuts['nonres'])
BKG = MergedPlotter(BKGPlotters)
WPlotters = getPlotters('TT_pow,T_tWch,TBar_tWch,WWTo1L1Nu2Q,WZTo1L1Nu2Q',False,cuts['resW'])
W = MergedPlotter(WPlotters)
TTJets.addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
TTJets.setFillProperties(1001,ROOT.kGreen-5)
qcdPlotters=[]
for sample in [
"QCD_Pt1000to1400_50ns","QCD_Pt120to170_50ns","QCD_Pt1400to1800_50ns","QCD_Pt170to300_50ns","QCD_Pt1800to2400_50ns","QCD_Pt2400to3200_50ns","QCD_Pt300to470_50ns","QCD_Pt3200_50ns","QCD_Pt470to600_50ns","QCD_Pt600to800_50ns","QCD_Pt800to1000_50ns","QCD_Pt80to120_50ns"
]:
qcdPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
qcdPlotters[-1].setupFromFile('samples/'+sample+'.pck')
qcdPlotters[-1].addCorrectionFactor('xsec','xsec',0.0,'lnN')
qcdPlotters[-1].addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
QCD = MergedPlotter(qcdPlotters)
QCD.setFillProperties(1001,ROOT.kAzure-9)
#QCD.setFillProperties(1001,ROOT.kGreen-5)
singleMu = TreePlotter('samples/SingleMuon_Run2015B.root','tree')
singleMu.addCorrectionFactor('hlt','(HLT_ISOMU_50ns==1||(HLT_MU==1))',0.0,'lnN')
singleEle = TreePlotter('samples/SingleElectron_Run2015B.root','tree')
singleEle.addCorrectionFactor('hlt','((HLT_ISOELE_50ns==1||(HLT_ELE==1))&&(!(HLT_ISOMU_50ns==1||(HLT_MU==1))))',0.0,'lnN')
jetHT = TreePlotter('samples/JetHT_Run2015B.root','tree')
#jetHT.addCorrectionFactor('hlt','((HLT_JJ==1||HLT_HT==1)&&(!(HLT_ISOMU_50ns==1||(HLT_MU==1)||(HLT_ISOELE_50ns==1||(HLT_ELE==1)))))',0.0,'lnN')
for sampleType in sampleTypes:
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
if options.data==0:
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
data=MergedPlotter(dataPlotters)
pvars=options.vars.split(',')
pmins=options.mins.split(',')
pmaxes=options.maxes.split(',')
pbins=options.bins.split(',')
if len(pvars)==1:
histo=data.drawTH1(pvars[0],options.cut,"1",int(pbins[0]),float(pmins[0]),float(pmaxes[0]))
if len(pvars)==2:
histo=data.drawTH2(pvars[1]+":"+pvars[0],options.cut,"1",int(pbins[0]),float(pmins[0]),float(pmaxes[0]),int(pbins[1]),float(pmins[1]),float(pmaxes[1]))
if len(pvars)==3:
histo=data.drawTH3(pvars[2]+":"+pvars[1]+":"+pvars[0],options.cut,"1",int(pbins[0]),float(pmins[0]),float(pmaxes[0]),int(pbins[1]),float(pmins[1]),float(pmaxes[1]),int(pbins[2]),float(pmins[2]),float(pmaxes[2]))
#create the W+jets plotters
wjPlotters = []
for sample in [
"WJetsToLNu_HT1200to2500", "WJetsToLNu_HT2500toInf",
"WJetsToLNu_HT400to600", "WJetsToLNu_HT600to800",
"WJetsToLNu_HT800to1200", 'WJetsToLNu_HT100to200',
'WJetsToLNu_HT200to400'
]:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'tree')
wjPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wjPlotters[-1].addCorrectionFactor('puWeight', 'tree')
WJets = MergedPlotter(wjPlotters)
tt = TreePlotter('samples/TTJets.root', 'tree')
tt.setupFromFile('samples/TTJets.pck')
tt.addCorrectionFactor('xsec', 'tree')
tt.addCorrectionFactor('genWeight', 'tree')
tt.addCorrectionFactor('puWeight', 'tree')
#create the Z+jets plotters
#zPlotters=[]
#for sample in ['DYJetsToLL_M50_HT100to200','DYJetsToLL_M50_HT200to400','DYJetsToLL_M50_HT400to600','DYJetsToLL_M50_HT600toInf']:
# zPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
# zPlotters[-1].setupFromFile('samples/'+sample+'.pck')
# zPlotters[-1].addCorrectionFactor('xsec','tree')
# zPlotters[-1].addCorrectionFactor('genWeight','tree')
cuts['mu'] = '(abs(ljj_l1_l1_pdgId)==13)'
cuts['e'] = '(abs(lljj_l1_l1_pdgId)==11)'
cuts['HP'] = '(lljj_l2_tau2/lljj_l2_tau1<0.55)'
cuts['LP'] = '(lljj_l2_tau2/lljj_l2_tau1>0.55&&lljj_l2_tau2/lljj_l2_tau1<0.75)'
#change the CMS_lumi variables (see CMS_lumi.py)
lumi_13TeV = "35.9 fb^{-1}"
lumi_sqrtS = "13 TeV" # used with iPeriod = 0, e.g. for simulation-only plots (default is an empty string)
iPeriod = 4
iPos = 11
#zjPlotters=[]
BKGPlotters = getPlotters(
'DYJetsToLL_M50_HT,WJetsToLNu_HT,TT_pow,T_tWch,TBar_tWch', False)
BKG = MergedPlotter(BKGPlotters)
VVPlotters = getPlotters('WZTo2L2Q,WZTo1L1Nu2Q', False)
VV = MergedPlotter(VVPlotters)
DATAPlotters = getPlotters('SingleMuon_,SingleElectron_', True)
data = MergedPlotter(DATAPlotters)
SigPlotters = getPlotters('WprimeToWZToWhadZlep_narrow_1400', False)
sig = MergedPlotter(SigPlotters)
#Fill properties
BKG.setFillProperties(1001, ROOT.kAzure - 9)
VV.setFillProperties(1001, ROOT.kSpring - 5)
#Stack for lnu+J
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
if options.data == 0 or options.data == 2:
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
corrFactors = options.factors.split(',')
for c in corrFactors:
if len(c.split(':')) < 2: continue
if c.split(':')[0] in fname:
print "Add correction factor:", fname, c.split(':')[1]
dataPlotters[-1].addCorrectionFactor(
float(c.split(':')[1]), 'flat')
data = MergedPlotter(dataPlotters)
pvars = options.vars.split(',')
pmins = options.mins.split(',')
pmaxes = options.maxes.split(',')
pbins = options.bins.split(',')
if len(pvars) == 1:
histo = data.drawTH1(pvars[0], options.cut, "1", int(pbins[0]),
float(pmins[0]), float(pmaxes[0]))
if len(pvars) == 2:
histo = data.drawTH2(pvars[1] + ":" + pvars[0], options.cut, "1",
int(pbins[0]), float(pmins[0]), float(pmaxes[0]),
int(pbins[1]), float(pmins[1]), float(pmaxes[1]))
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
denominator = data.drawTH1("0.5", options.cutDenominator, "1", 1, 0, 1)
cut = options.cutNumerator
nominal = data.drawTH1("0.5", '*'.join([options.cutDenominator, cut]), "1", 1,
0, 1)
cut = options.cutNumerator.replace(
options.var, "(" + str(options.factor) + "*" + options.var + ")")
up = data.drawTH1("0.5", '*'.join([options.cutDenominator, cut]), "1", 1, 0, 1)
cut = options.cutNumerator.replace(
options.var, "(" + str(1.0 / options.factor) + "*" + options.var + ")")
down = data.drawTH1("0.5", '*'.join([options.cutDenominator, cut]), "1", 1, 0,
1)
legs = ["l1", "l2"]
plotters = []
for name in samples.keys():
plotters.append(
TreePlotter(args[0] + '/' + samples[name] + '.root', 'tree'))
plotters[-1].setupFromFile(args[0] + '/' + samples[name] + '.pck')
plotters[-1].addCorrectionFactor('xsec', 'tree')
plotters[-1].addCorrectionFactor('genWeight', 'tree')
plotters[-1].addCorrectionFactor('puWeight', 'tree')
corrFactor = options.corrFactorW
if samples[name].find('Z') != -1: corrFactor = options.corrFactorZ
plotters[-1].addCorrectionFactor(corrFactor, 'flat')
plotter = MergedPlotter(plotters)
print 'Fitting Mjet:'
for leg in legs:
fitter = Fitter(['x'])
#fitter.jetResonanceVjets('model','x')
fitter.gaus('model', 'x')
if options.fixPars != "1":
fixedPars = options.fixPars.split(',')
if len(fixedPars) > 1:
print " - Fix parameters: ", fixedPars
for par in fixedPars:
if par == "c_0" or par == "c_1" or par == "c_2": continue
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
histos = []
histosSUP = []
histosSDWN = []
histosRUP = []
histosRDWN = []
bins = [
500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1500, 1750, 2000, 2500,
3000, 3500, 4000, 4500, 5000
]
axis = ROOT.TAxis(len(bins) - 1, array('d', bins))
for i in range(1, axis.GetNbins() + 1):
center = axis.GetBinCenter(i)
# h2=p2.drawTH1Binned(var,cut2,lumi,bins,title,unit, "SAMEHIST")
legend.AddEntry(h1, leg1, "LEP")
legend.AddEntry(h2, leg2, "LF")
legend.AddEntry(h3, leg3, "LF")
legend.Draw("same")
cmslabel_prelim(canvas, '2016', 11)
canvas.Update()
return canvas, h1, h2, h3, legend #,pt
QCDPtPlotters = getPlotters(nonResTemplate, False)
QCDhtPlotters = getPlotters('QCD_HT', False)
QCDherwigPlotters = getPlotters('QCD_Pt-', False)
QCD = MergedPlotter(QCDPtPlotters)
QCDht = MergedPlotter(QCDhtPlotters)
QCDherwig = MergedPlotter(QCDherwigPlotters)
#
# # DATAPlotters = getPlotters('SingleJet',True)
# # data=MergedPlotter(DATAPlotters)
#
# SigPlotters = getPlotters('QstarToQW_2000',False)
# sig = MergedPlotter(SigPlotters)
#
#
QCD.setFillProperties(1001, 921)
QCDht.setLineProperties(1, 633, 2)
QCDht.setFillProperties(1001, 0)
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters=[]
for sample in ['WJetsToLNu_HT100to200','WJetsToLNu_HT200to400','WJetsToLNu_HT400to600','WJetsToLNu_HT600toInf']:
wjPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
wjPlotters[-1].setupFromFile('samples/'+sample+'.pck')
wjPlotters[-1].addCorrectionFactor('xsec','xsec',0.0,'lnN')
wjPlotters[-1].addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
WJets = MergedPlotter(wjPlotters)
WJets.setFillProperties(1001,ROOT.kAzure-9)
RSGWWLNuQQ = TreePlotter('samples/RSGravToWWToLNQQ_kMpl01_2500.root','tree')
RSGWWLNuQQ.setupFromFile('samples/RSGravToWWToLNQQ_kMpl01_2500.pck')
RSGWWLNuQQ.setFillProperties(0,ROOT.kWhite)
RSGWWLNuQQ.setLineProperties(1,ROOT.kOrange+10,3)
RSGWWLNuQQ.addCorrectionFactor('xsec',0.001,0.0,'lnN')
#Stack
vvStack = StackPlotter()
vvStack.addPlotter(WJets,"W+jets","W+Jets","background")
vvStack.addPlotter(RSGWWLNuQQ,"RSG2000","RSGWW #rightarrow l#nu QQ","signal")
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
if options.data == 0 or options.data == 2:
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
if options.data == 2:
sigmas = []
for d in dataPlotters:
sigmas.append(d.tree.GetMaximum("xsec") / d.weightinv)
sigmaW = max(sigmas)
for p in dataPlotters:
p.addCorrectionFactor(1.0 / sigmaW, 'flat')
parameterization = {}
data = MergedPlotter(dataPlotters)
dataset = data.makeDataSet(options.genvar, options.genCut, -1)
histo = data.drawTH1(options.var, options.cut, "1", options.bins, options.mini,
options.maxi)
fitter = Fitter([options.var])
fitter.importBinnedData(histo, [options.var], 'data')
fitter.gaussianSum('model', options.var, dataset, options.genvar)
fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(1)])
chi = fitter.projection("model", "data", options.var,
"debugPlot_" + options.output + ".root", 'x')
print 'Chi2', chi
print 'make systematics'
meanDefault = fitter.w.var("scale").getVal()
sigmaDefault = fitter.w.var("sigma").getVal()
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
sigmas = []
for d in dataPlotters:
sigmas.append(d.tree.GetMaximum("xsec") / d.weightinv)
sigmaW = max(sigmas)
for p in dataPlotters:
p.addCorrectionFactor(1.0 / sigmaW, 'flat')
data = MergedPlotter(dataPlotters)
orderInfo = {}
orders = options.order.split('|')
for v in orders:
sp = v.split(':')
orderInfo[sp[0]] = int(sp[1])
h = data.drawTH2(options.vary + ':' + options.varx, options.cut,
str(options.lumi), options.binsx, options.minx, options.maxx,
options.binsy, options.miny, options.maxy)
histo = copy.deepcopy(h)
fitter = Fitter(['M', 'mjj'])
fitter.w.var("M").setVal((options.maxx - options.minx) / 2.0)
fitter.w.var("M").setMax(options.maxx)
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
if options.data == 0 or options.data == 2:
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
# dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
if options.data == 2:
sigmas = []
for d in dataPlotters:
sigmas.append(d.tree.GetMaximum("xsec") / d.weightinv)
sigmaW = max(sigmas)
for p in dataPlotters:
p.addCorrectionFactor(1.0 / sigmaW, 'flat')
data = MergedPlotter(dataPlotters)
cBinsStr = options.condBins.split(',')
cBins = []
for b in cBinsStr:
cBins.append(float(b))
axis = ROOT.TAxis(len(cBins) - 1, array('d', cBins))
graph = {'scale': ROOT.TGraphErrors(), 'sigma': ROOT.TGraphErrors()}
#dataset = data.makeDataSet(options.genvar,options.genCut,-1)
for i in range(1, axis.GetNbins() + 1):
cBinLo = axis.GetBinLowEdge(i)
cBinHi = axis.GetBinUpEdge(i)
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
dataPlotters[-1].addCorrectionFactor('lnujj_sf','branch')
dataPlotters[-1].addCorrectionFactor('lnujj_btagWeight','branch')
dataPlotters[-1].addCorrectionFactor('truth_genTop_weight','branch')
dataPlotters[-1].filename=fname
data=MergedPlotter(dataPlotters)
histI=data.drawTH1(options.var,options.cut,"1",1,0,1000000000)
norm=histI.Integral()
histograms={}
histograms['nominal'] = {'scale':1.0,'weight':'1'}
histograms['scale_Up'] = {'scale':1.2,'weight':'1'}
histograms['scale_Down'] = {'scale':0.8,'weight':'1'}
histograms['ptSpectrum_Up'] = {'scale':1.0,'weight':'(1.2*lnujj_l2_gen_pt)'}
histograms['ptSpectrum_Down'] = {'scale':1.0,'weight':'(0.8*lnujj_l2_gen_pt)'}
f=ROOT.TFile(options.output,"RECREATE")
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
#STandard histogramming
histo = data.drawTH2Keys(options.varx + "," + options.vary, options.cut,
options.binsx, options.minx, options.maxx,
options.binsy, options.miny, options.maxy)
if histo.Integral() > 0:
histoNorm = data.drawTH2(options.vary + ":" + options.varx, options.cut,
"1", options.binsx, options.minx, options.maxx,
options.binsy, options.miny, options.maxy)
histo.Scale(1.0 / histo.Integral())
histo.Scale(histoNorm.Integral())
F = ROOT.TFile(options.output, "UPDATE")
F.cd()
histo.Write(options.name)
F.Close()
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
data=MergedPlotter(dataPlotters)
histoQ=data.drawTH1(options.mvv+"/13000.0",options.cut+"&&"+options.quarkCut,"1",options.bins,options.min/13000.0,options.max/13000.0)
histoA=data.drawTH1(options.mvv+"/13000.0",options.cut,"1",options.bins,options.min/13000.0,options.max/13000.0)
histoQ.Divide(histoA)
func=ROOT.TF1("func",options.function,options.min/13000.0,options.max/13000.0)
histoQ.Fit(func)
parameterization={'quarkFraction':returnString(func)}
f=open(options.output+".json","w")
json.dump(parameterization,f)
f.close()
for sample in [
"WJetsToLNu_HT1200to2500", "WJetsToLNu_HT2500toInf",
"WJetsToLNu_HT400to600", "WJetsToLNu_HT600to800",
"WJetsToLNu_HT800to1200", 'WJetsToLNu_HT100to200',
'WJetsToLNu_HT200to400'
]:
#for sample in ["WJetsToLNu_HT1200to2500","WJetsToLNu_HT2500toInf","WJetsToLNu_HT400to600","WJetsToLNu_HT600to800","WJetsToLNu_HT800to1200",'WJetsToLNu_HT100to200','WJetsToLNu_HT200to400']:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'tree')
wjPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wjPlotters[-1].addCorrectionFactor('puWeight', 'tree')
# wjPlotters[-1].addCorrectionFactor('0.82','flat')
WJets = MergedPlotter(wjPlotters)
ttO = TreePlotter('samples/TTJets.root', 'tree')
ttO.setupFromFile('samples/TTJets.pck')
ttO.addCorrectionFactor('xsec', 'tree')
ttO.addCorrectionFactor('genWeight', 'tree')
ttO.addCorrectionFactor('puWeight', 'tree')
ttO.addCorrectionFactor(
'(!(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8))', 'tree')
ttM = TreePlotter('samples/TTJets.root', 'tree')
ttM.setupFromFile('samples/TTJets.pck')
ttM.addCorrectionFactor('xsec', 'tree')
ttM.addCorrectionFactor('genWeight', 'tree')
ttM.addCorrectionFactor('puWeight', 'tree')
ttM.addCorrectionFactor(
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
#STandard histogramming
if not options.keys:
histo = data.drawTH2(options.vary + ":" + options.varx, options.cut, "1",
options.binsx, options.minx, options.maxx,
options.binsy, options.miny, options.maxy)
histoSUP = data.drawTH2(options.vary + "Up:" + options.varx, options.cut,
"1", options.binsx, options.minx, options.maxx,
options.binsy, options.miny, options.maxy)
histoSDWN = data.drawTH2(options.vary + "Down:" + options.varx,
options.cut, "1", options.binsx, options.minx,
options.maxx, options.binsy, options.miny,
options.maxy)
histoRUP = data.drawTH2(options.vary + "Smear:" + options.varx,
options.cut, "1", options.binsx, options.minx,
leg1.AddEntry(
profiles[4], "400-500 GeV, slope = %.3f #pm %.3f" %
(frRes4.Parameter(1), frRes4.ParError(1)), "LEP")
profiles[5].Draw("same")
leg1.AddEntry(
profiles[5], "1000-1100 GeV, slope = %.3f #pm %.3f" %
(frRes5.Parameter(1), frRes5.ParError(1)), "LEP")
profiles[7].Draw("same")
leg1.AddEntry(
profiles[7], "All jets, slope = %.4f #pm %.4f" %
(frRes7.Parameter(1), frRes7.ParError(1)), "LEP")
leg1.Draw("")
cmslabel_sim(canvas1, '2016', 11)
canvas1.Update()
canvas1.SaveAs("rho_" + file.replace(".root", ".pdf"))
sleep(10)
QCDPtPlotters = getPlotters("QCD_Pt_", False)
QCD = MergedPlotter(QCDPtPlotters)
# QCDherwigPlotters = getPlotters('QCD_Pt-',False)
# QCDherwig = MergedPlotter(QCDherwigPlotters)
QCD.setLineProperties(1, 434, 2)
QCD.setFillProperties(1001, 0)
file1 = doDDT(QCD, cuts['common'], "rho_pythia.root")
file2 = doDDT(QCD, cuts['commonTOT'], "rho_pythia_FullSel.root")
doFit("rho_pythia.root", False)
doFit("rho_pythia_FullSel.root", True)
def loadSignalNtuples(samples, sampleDir, minMX, maxMX, corr=1.):
sampleTypes = samples.split(',')
plotters = {}
pcuts = {}
filelist = []
if sampleDir == 'ntuples':
filelist = [
g for flist in [[(path + '/' + f)
for f in os.listdir(sampleDir + '/' + path)]
for path in os.listdir(sampleDir)] for g in flist
]
else:
filelist = os.listdir(sampleDir)
for filename in filelist:
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
fpath = sampleDir + '/' + fname
mass = float(fname.split('_')[-1])
if mass < minMX or mass > maxMX:
continue
if not mass in plotters.keys():
plotters[mass] = []
pcuts[mass] = []
plotters[mass].append(TreePlotter(fpath + '.root', 'tree'))
## Fix for cuts and weights for which the branches differ between years:
if "ntuples2016" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2017" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2018" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET)')
else:
sys.exit("Year not found, aborting.")
plotters[mass][-1].setupFromFile(fpath + '.pck')
plotters[mass][-1].addCorrectionFactor('xsec', 'tree')
plotters[mass][-1].addCorrectionFactor('genWeight', 'tree')
plotters[mass][-1].addCorrectionFactor('puWeight', 'tree')
#plotters[mass][-1].addCorrectionFactor('lnujj_sfWV','branch')
#plotters[mass][-1].addCorrectionFactor('lnujj_btagWeight','branch')
plotters[mass][-1].addCorrectionFactor(corr, 'flat')
plotters[mass][-1].filename = fname
print 'found', fpath, 'mass', str(mass)
mergedplotters = {}
for mass in sorted(plotters.keys()):
if len(plotters[mass]) != (
1, (3, 2)['Wprime_VBF_Wh_Wlephinc_narrow' in samples]
)[sampleDir == 'ntuples']: ##FIXME: rechange when 2017 VBFWH is ready
continue
mergedplotters[mass] = MergedPlotter(plotters[mass], pcuts[mass])
return mergedplotters
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters = []
for sample in [
'WJetsToLNu_HT100to200', 'WJetsToLNu_HT200to400',
'WJetsToLNu_HT400to600', 'WJetsToLNu_HT600toInf'
]:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
WJets = MergedPlotter(wjPlotters)
WJets.setFillProperties(1001, ROOT.kAzure - 9)
RSGWWLNuQQ = TreePlotter('samples/RSGravToWWToLNQQ_2000.root', 'tree')
RSGWWLNuQQ.setupFromFile('samples/RSGravToWWToLNQQ_2000.pck')
RSGWWLNuQQ.setFillProperties(0, ROOT.kWhite)
RSGWWLNuQQ.setLineProperties(1, ROOT.kOrange + 10, 3)
#RSGWWLNuQQ..addCorrectionFactor('xsec',0.001,0.0,'lnN')
#Stack
vvStack = StackPlotter()
vvStack.addPlotter(WJets, "W+jets", "W+Jets", "background")
vvStack.addPlotter(RSGWWLNuQQ, "RSG2000", "RSGWW #rightarrow l#nu QQ",
"signal")
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
print fname
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
data=MergedPlotter(dataPlotters)
binsxStr=options.binsx.split(',')
binsx=[]
for b in binsxStr:
binsx.append(float(b))
binsz=[]
for b in range(0,51):
binsz.append(0.7+0.7*b/50.0)
scalexHisto=ROOT.TH1F("scalexHisto","scaleHisto",len(binsx)-1,array('d',binsx))
resxHisto=ROOT.TH1F("resxHisto","resHisto",len(binsx)-1,array('d',binsx))
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
histo = data.drawTH1(options.var, options.cut, "1", options.bins, options.min,
options.max)
histoUp = data.drawTH1(options.var + "Up", options.cut, "1", options.bins,
options.min, options.max)
histoDown = data.drawTH1(options.var + "Down", options.cut, "1", options.bins,
options.min, options.max)
histoRUp = data.drawTH1(options.var + "Smear", options.cut, "1", options.bins,
options.min, options.max)
histoRDown = mirror(histo, histoRUp)
F = ROOT.TFile(options.output, "UPDATE")
F.cd()
histo.Write(options.name)
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters=[]
for sample in ["WJetsToLNu_HT1200to2500","WJetsToLNu_HT2500toInf","WJetsToLNu_HT400to600","WJetsToLNu_HT600to800","WJetsToLNu_HT800to1200",'WJetsToLNu_HT100to200','WJetsToLNu_HT200to400']:
wjPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
wjPlotters[-1].setupFromFile('samples/'+sample+'.pck')
wjPlotters[-1].addCorrectionFactor('xsec','tree')
wjPlotters[-1].addCorrectionFactor('genWeight','tree')
wjPlotters[-1].addCorrectionFactor('puWeight','tree')
WJets = MergedPlotter(wjPlotters)
tt=TreePlotter('samples/TTJets.root','tree')
tt.setupFromFile('samples/TTJets.pck')
tt.addCorrectionFactor('xsec','tree')
tt.addCorrectionFactor('genWeight','tree')
tt.addCorrectionFactor('puWeight','tree')
#create the Z+jets plotters
zPlotters=[]
for sample in ['DYJetsToLL_M50_HT100to200','DYJetsToLL_M50_HT200to400','DYJetsToLL_M50_HT400to600','DYJetsToLL_M50_HT600toInf']:
zPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
data=MergedPlotter(dataPlotters)
binningx=map(float,options.binningx.split(','))
binningy=map(float,options.binningy.split(','))
#STandard histogramming
histo=data.drawTH2Binned(options.vary+":"+options.varx,options.cut,"1",binningx,binningy)
histoSUP=data.drawTH2Binned(options.vary+"Up:"+options.varx,options.cut,"1",binningx,binningy)
histoSDWN=data.drawTH2Binned(options.vary+"Down:"+options.varx,options.cut,"1",binningx,binningy)
histoRUP=data.drawTH2Binned(options.vary+"Smear:"+options.varx,options.cut,"1",binningx,binningy)
histoRDWN = mirror(histo,histoRUP)
def getPlotters(samples, sampleDir, isData=False, corr="1"):
sampleTypes = samples.split(',')
plotters = []
pcuts = []
filelist = []
if sampleDir == 'ntuples':
filelist = [
g for flist in [[(path + '/' + f)
for f in os.listdir(sampleDir + '/' + path)]
for path in os.listdir(sampleDir)] for g in flist
]
else:
filelist = os.listdir(sampleDir)
for filename in filelist:
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
fpath = sampleDir + '/' + fname
print 'Adding file', fpath
plotters.append(TreePlotter(fpath + '.root', 'tree'))
## Fix for cuts and weights for which the branches differ between years:
if "ntuples2016" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2017" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2018" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET)')
else:
sys.exit("Year not found, aborting.")
if not isData:
plotters[-1].setupFromFile(fpath + '.pck')
plotters[-1].addCorrectionFactor('xsec', 'tree')
plotters[-1].addCorrectionFactor('genWeight', 'tree')
plotters[-1].addCorrectionFactor('puWeight', 'tree')
plotters[-1].addCorrectionFactor('truth_genTop_weight',
'branch')
##plotters[-1].addCorrectionFactor('lnujj_sfWV','branch')
##plotters[-1].addCorrectionFactor('lnujj_btagWeight','branch')
plotters[-1].addCorrectionFactor(corr, 'flat')
#''' ## remove the Madgraph background NLO k-factors
if REMOVEBKGDKFAC:
if fname.find("WJetsToLNu_HT") != -1:
wjetsAntiKFactor = 1. / 1.21
plotters[-1].addCorrectionFactor(
wjetsAntiKFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
wjetsAntiKFactor)
elif fname.find("DYJetsToLL_M50_HT") != -1:
dyAntiKFactor = 1. / 1.23
plotters[-1].addCorrectionFactor(
dyAntiKFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
dyAntiKFactor)
#'''
#''' ## rescale the W+jets yields (the current factors were computed from 30 < mjet < 50 GeV, on top of the NLO k-factors)
if RESCALEWJETS:
if fname.find("WJetsToLNu_HT") != -1:
wjetsFactor = 1.
if "ntuples2016" in fpath: wjetsFactor = 1.022
elif "ntuples2017" in fpath: wjetsFactor = 0.926
elif "ntuples2018" in fpath: wjetsFactor = 0.860
plotters[-1].addCorrectionFactor(
wjetsFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
wjetsFactor)
#'''
return MergedPlotter(plotters, pcuts)
'branch')
##dataPlotters[-1].addCorrectionFactor('lnujj_sf','branch')
##dataPlotters[-1].addCorrectionFactor('lnujj_btagWeight','branch')
dataPlotters[-1].filename = fname
dataPlottersNW.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlottersNW[-1].addCorrectionFactor('genWeight', 'tree')
dataPlottersNW[-1].addCorrectionFactor('puWeight', 'tree')
dataPlottersNW[-1].addCorrectionFactor('truth_genTop_weight',
'branch')
##dataPlottersNW[-1].addCorrectionFactor('lnujj_sf','branch')
##dataPlottersNW[-1].addCorrectionFactor('lnujj_btagWeight','branch')
dataPlottersNW[-1].filename = fname
data = MergedPlotter(dataPlotters)
## Make histograms for uncertainty weights
uncWeights = options.uncweight.split(',')
uncw1 = uncWeights[0]
hGenPtUp = ROOT.TH1F("hGenPtUp", "hGenPtUp", 5000, 0, 5000)
hGenPtDn = ROOT.TH1F("hGenPtDn", "hGenPtDn", 5000, 0, 5000)
fGenPtUp = ROOT.TF1("fGenPtUp", uncw1.replace("lnujj_l2_gen_pt", "x"), 0, 5000)
fGenPtDn = ROOT.TF1("fGenPtDn", '1/' + uncw1.replace("lnujj_l2_gen_pt", "x"),
0, 5000)
for i in range(5000):
hGenPtUp.Fill(i + 0.5, fGenPtUp.Eval(i + 0.5))
hGenPtDn.Fill(i + 0.5, fGenPtDn.Eval(i + 0.5))
histograms = []
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
if options.data == 0:
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
pvars = options.vars.split(',')
pmins = options.mins.split(',')
pmaxes = options.maxes.split(',')
pbins = options.bins.split(',')
if len(pvars) == 1:
histo = data.drawTH1(pvars[0], options.cut, "1", int(pbins[0]),
float(pmins[0]), float(pmaxes[0]))
if len(pvars) == 2:
histo = data.drawTH2(pvars[1] + ":" + pvars[0], options.cut, "1",
int(pbins[0]), float(pmins[0]), float(pmaxes[0]),
int(pbins[1]), float(pmins[1]), float(pmaxes[1]))
qcdPlotters = []
for sample in [
"QCD_Pt1000to1400_50ns", "QCD_Pt120to170_50ns",
"QCD_Pt1400to1800_50ns", "QCD_Pt170to300_50ns",
"QCD_Pt1800to2400_50ns", "QCD_Pt2400to3200_50ns",
"QCD_Pt300to470_50ns", "QCD_Pt3200_50ns", "QCD_Pt470to600_50ns",
"QCD_Pt600to800_50ns", "QCD_Pt800to1000_50ns", "QCD_Pt80to120_50ns"
]:
qcdPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
qcdPlotters[-1].setupFromFile('samples/' + sample + '.pck')
qcdPlotters[-1].addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
qcdPlotters[-1].addCorrectionFactor('genWeight', 'genWeight', 0.0, 'lnN')
QCD = MergedPlotter(qcdPlotters)
QCD.setFillProperties(1001, ROOT.kAzure - 9)
#QCD.setFillProperties(1001,ROOT.kGreen-5)
singleMu = TreePlotter('samples/SingleMuon_Run2015B.root', 'tree')
singleMu.addCorrectionFactor('hlt', '(HLT_ISOMU_50ns==1||(HLT_MU==1))', 0.0,
'lnN')
singleEle = TreePlotter('samples/SingleElectron_Run2015B.root', 'tree')
singleEle.addCorrectionFactor(
'hlt',
'((HLT_ISOELE_50ns==1||(HLT_ELE==1))&&(!(HLT_ISOMU_50ns==1||(HLT_MU==1))))',
0.0, 'lnN')
jetHT = TreePlotter('samples/JetHT_Run2015B.root', 'tree')
samples = {}
sampleTypes = options.samples.split(',')
dataPlotters = []
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
graphs = runFits(data, options)
f = ROOT.TFile(options.output + ".root", "RECREATE")
f.cd()
for i, g in enumerate(graphs):
g.Write("p" + str(i))
f.Close()
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('lnujj_sf', 'branch')
dataPlotters[-1].addCorrectionFactor('lnujj_btagWeight', 'branch')
dataPlotters[-1].addCorrectionFactor('truth_genTop_weight',
'branch')
dataPlotters[-1].filename = fname
data = MergedPlotter(dataPlotters)
variables = options.vars.split(',')
histI = data.drawTH1(variables[0], options.cut, "1", 1, 0, 1000000000)
norm = histI.Integral()
histograms = {}
histograms['nominal'] = {'scalex': 1.0, 'scaley': 1.0, 'weight': '1'}
histograms['scalex_Up'] = {'scalex': 1.2, 'scaley': 1.0, 'weight': '1'}
histograms['scalex_Down'] = {'scalex': 0.8, 'scaley': 1.0, 'weight': '1'}
histograms['ptSpectrum_Up'] = {
'scalex': 1.0,
'scaley': 1.0,
'weight': '(1.1*lnujj_l2_gen_pt)'
}
histograms['ptSpectrum_Down'] = {
