'eta' : {'xaxis': '#eta', 'yaxis': 'Events', 'rebin': 5, 'rangex': [-2.5,2.5]},
#'met' : {'xaxis': 'E_{T}^{miss} (GeV)', 'yaxis': 'Events/0.2 GeV', 'rebin': 2, 'rangex': [0,200]},
'wMass' : {'xaxis': 'm_{T}^{l^{+},MET} (GeV)', 'yaxis': 'Events/0.5 GeV', 'rebin': 5, 'rangex': [0,200]},
}
# signal region
for plot in plots:
for lepton in ['loose','medium','tight']:
for chan in chans:
plotname = '{0}/{1}/{2}'.format(lepton,chan,plot)
savename = '{0}/{1}/{2}'.format(lepton,chan,plot)
dijetFakeRatePlotter.plot(plotname,savename,**plots[plot])
# plots of multiple ptcuts on same plot
dijetFakeRatePlotter.clearHistograms()
jetPts = [20,25,30,35,40,45,50]
jetPts = [20,30,40,50]
dRs = [0.5,0.75,1.,1.25,1.5]
jetPtColors = {
10 : ROOT.TColor.GetColor('#000000'),
15 : ROOT.TColor.GetColor('#330000'),
20 : ROOT.TColor.GetColor('#660000'),
25 : ROOT.TColor.GetColor('#800000'),
30 : ROOT.TColor.GetColor('#990000'),
35 : ROOT.TColor.GetColor('#B20000'),
40 : ROOT.TColor.GetColor('#CC0000'),
45 : ROOT.TColor.GetColor('#FF0000'),
50 : ROOT.TColor.GetColor('#FF3333'),
}
for jetPt in jetPts:
### MC based BG estimate ###
############################
for s in samples:
plotter.addHistogramToStack(s, sigMap[s])
if not blind: plotter.addHistogram('data', sigMap['data'])
for plot in plots:
for sel in sels:
kwargs = deepcopy(plots[plot])
plotname = '{0}/{1}'.format(sel, plot)
savename = '{0}/mc/{1}'.format(sel, plot)
plotter.plot(plotname, savename, **kwargs)
# ratios of tight/loose as func of pt/eta
plotter.clearHistograms()
plotter.addHistogram('MC', sigMap['BG'])
plotter.addHistogram('Z', sigMap['Z'])
plotter.addHistogram('data',
sigMap['data'],
style={
'linecolor': ROOT.kBlack,
'name': 'Data'
})
plotter.addHistogram('data_uncorrected',
sigMap['data'],
style={
'linecolor': ROOT.kRed,
'name': 'Uncorrected'
})
# partially blinded plots
if blind:
hpp3lPlotter.addHistogram('data',sigMap['data'])
for plot in blind_cust:
kwargs = deepcopy(plots[plot])
kwargs.update(blind_cust[plot])
plotWithCategories(hpp3lPlotter,plot,saveDir='mc',baseDir='default',postfix='blinder',perCatBins=True,**kwargs)
##############################
### datadriven backgrounds ###
##############################
if plotDatadriven:
hpp3lPlotter.clearHistograms()
hpp3lPlotter.addHistogramToStack('datadriven',datadrivenSamples)
for s in samples:
hpp3lPlotter.addHistogramToStack(s,sigMapDD[s])
for signal in signals:
hpp3lPlotter.addHistogram(signal,sigMapDD[signal],signal=True)
if not blind: hpp3lPlotter.addHistogram('data',sigMapDD['data'])
if plotCount: plotCounts(hpp3lPlotter,baseDir='default',saveDir='datadriven',datadriven=True)
for plot in plots:
kwargs = deepcopy(plots[plot])
# #hpp4lPlotter.plot(plotvars,savename,**kwargs)
# for cat in cats:
# plotvars = {}
# for mode in ['default','zveto']:
# plotvars[mode] = []
# for subcat in subCatChannels[cat]:
# plotvars[mode] += ['{0}/{1}/{2}'.format(mode,chan,plot) for chan in subCatChannels[cat][subcat]]
# savename = 'zVeto/{0}/{1}'.format(cat,plot)
# if doCat: hpp4lPlotter.plotNormalized(plotnames,savename,**kwargs)
# #if doCat: hpp4lPlotter.plot(plotnames,savename,**kwargs)
##############################
### datadriven backgrounds ###
##############################
if plotDatadriven:
hpp4lPlotter.clearHistograms()
hpp4lPlotter.addHistogramToStack('datadriven',datadrivenSamples)
for s in samples:
hpp4lPlotter.addHistogramToStack(s,sigMapDD[s])
for signal in signals:
hpp4lPlotter.addHistogram(signal,sigMapDD[signal],signal=True)
if not blind: hpp4lPlotter.addHistogram('data',sigMapDD['data'])
if plotCount: plotCounts(hpp4lPlotter,baseDir='default',saveDir='datadriven',datadriven=True)
for plot in plots:
kwargs = deepcopy(plots[plot])
savename = '{0}/{1}/{2}'.format(sign,chan,plot)
chargePlotter.plot(plotname,savename,**plots[plot])
# sum gen matched
for plot in plots:
for chan in chans:
plotnames = {}
for sample in samples:
plotnames[sample] = ['{0}/{1}/{2}'.format('SS1',chan,plot), '{0}/{1}/{2}'.format('SS2',chan,plot)]
plotnames['data'] = ['{0}/{1}/{2}'.format('SS',chan,plot)]
savename = '{0}/{1}/{2}'.format('SS12',chan,plot)
chargePlotter.plot(plotnames,savename,**plots[plot])
# ratios of SS/OS as func of pt/eta
chargePlotter.clearHistograms()
allSamplesDict = {'MC':[]}
for s in samples:
allSamplesDict['MC'] += sigMap[s]
chargePlotter.addHistogram('MC',allSamplesDict['MC'],style={'linecolor': ROOT.kRed})
chargePlotter.addHistogram('data',sigMap['data'],style={'linecolor':ROOT.kBlack})
ptbins = [10,20,30,40,50,60,80,100,200,1000]
etabins = [-2.5,-2.0,-1.479,-1.0,-0.5,0.,0.5,1.0,1.479,2.0,2.5]
ratio_cust = {
'zLeadingLeptonPt' : {'yaxis': 'N_{SS}/N', 'rebin': ptbins},
'zLeadingLeptonEta' : {'yaxis': 'N_{SS}/N', 'rebin': etabins},
zzPlotter.addHistogram('data',sigMap['data'])
if plotCount: plotCounts(zzPlotter,baseDir='default',saveDir='mc')
if plotCount: plotCounts(zzPlotter,baseDir='zWindow',saveDir='mc-zWindow')
for plot in plots:
kwargs = deepcopy(plots[plot])
plotWithChannels(zzPlotter,plot,baseDir='default',saveDir='mc',**kwargs)
plotWithChannels(zzPlotter,plot,baseDir='zWindow',saveDir='mc-zWindow',**kwargs)
##############################
### datadriven backgrounds ###
##############################
if plotDatadriven:
zzPlotter.clearHistograms()
zzPlotter.addHistogramToStack('datadriven',datadrivenSamples)
for s in samples:
zzPlotter.addHistogramToStack(s,sigMapDD[s])
zzPlotter.addHistogram('data',sigMapDD['data'])
if plotCount: plotCounts(zzPlotter,baseDir='',saveDir='datadriven',datadriven=True)
if plotCount: plotCounts(zzPlotter,baseDir='zWindow',saveDir='datadriven-zWindow',datadriven=True)
for plot in plots:
kwargs = deepcopy(plots[plot])
plotWithChannels(zzPlotter,plot,baseDir='',saveDir='datadriven',datadriven=True,**kwargs)
plotWithChannels(zzPlotter,plot,baseDir='zWindow',saveDir='datadriven-zWindow',datadriven=True,**kwargs)
for s in samples:
plotter.addHistogramToStack(s,sigMap[s])
if not blind: plotter.addHistogram('data',sigMap['data'])
for plot in plots:
for sel in sels:
kwargs = deepcopy(plots[plot])
plotname = '{0}/{1}'.format(sel,plot)
savename = '{0}/mc/{1}'.format(sel,plot)
plotter.plot(plotname,savename,**kwargs)
# ratios of tight/loose as func of pt/eta
plotter.clearHistograms()
plotter.addHistogram('MC',sigMap['BG'])
plotter.addHistogram('Z',sigMap['Z'])
plotter.addHistogram('data',sigMap['data'],style={'linecolor':ROOT.kBlack,'name':'Data'})
plotter.addHistogram('data_uncorrected',sigMap['data'],style={'linecolor':ROOT.kRed,'name':'Uncorrected'})
ptbins = [3,5,10,15,20,25,30,50,100]
etabins = [-2.4,-1.5,-1.0,0.,1.0,1.5,2.4]
cust = {
'mPt' : {'rebin': ptbins, 'overflow': False, 'logy': False},
#'mEta' : {'rebin': etabins},
}
numDenoms = [('iso0.15','default'),('iso0.25','default'),('iso0.40','default'),('iso0.15','iso0.40'),]
numDenoms += [('iso0.15trig','defaulttrig'),('iso0.25trig','defaulttrig'),('iso0.40trig','defaulttrig'),('iso0.15trig','iso0.40trig'),]
plotname = '{0}/{1}/{2}'.format(region,chan,plot)
savename = '{0}/{1}/{2}'.format(region,chan,plot)
fakeratePlotter.plot(plotname,savename,**plots[plot])
#for sel in ['SS','ZVeto','WMt','full']:
for sel in ['WVeto','WMt','ZVeto','full']:
plotname = '{0}/{1}/{2}/{3}'.format(region,sel,chan,plot)
savename = '{0}/{1}/{2}/{3}'.format(region,sel,chan,plot)
fakeratePlotter.plot(plotname,savename,**plots[plot])
# ratios of tight/loose as func of pt/eta
sigMap['MC'] = []
for sample in ['TTsub','Z','WWsub']:
sigMap['MC'] += sigMap[sample]
fakeratePlotter.clearHistograms()
fakeratePlotter.addHistogram('MC',sigMap['MC'])
fakeratePlotter.addHistogram('W',sigMap['W'])
fakeratePlotter.addHistogram('data',sigMap['data'],style={'linecolor':ROOT.kBlack,'name':'Corrected'})
fakeratePlotter.addHistogram('data_uncorrected',sigMap['data'],style={'linecolor':ROOT.kRed,'name':'Uncorrected'})
ptbins = [0,10,15,20,25,30,50,100]#,200,1000]
etabins = [-2.5,-2.0,-1.479,-1.0,-0.5,0.,0.5,1.0,1.479,2.0,2.5]
cust = {
'lPt' : {'yaxis': 'N_{{{num}}} / N_{{{denom}}}', 'rebin': ptbins, 'xrange': [0,100]},
'lEta' : {'yaxis': 'N_{{{num}}} / N_{{{denom}}}', 'rebin': etabins},
}
numDenom = [('medium','loose'),('tight','loose'),('tight','medium')]
'TTV' : ['TTWJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8'],
'ZG' : ['ZGTo2LG_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'WW' : ['WWTo2L2Nu_13TeV-powheg'],
'Z' : ['DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8',
'DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'TT' : ['TTJets_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'data': ['DoubleMuon',
'DoubleEG',
'MuonEG',
'SingleMuon',
'SingleElectron'],
'HppHmm500GeV' : ['HPlusPlusHMinusMinusHTo4L_M-500_13TeV-pythia8'],
}
mPlotter.addHistogram('HppHmm500GeV',sigMap['HppHmm500GeV'])
plots = {
'pt_v_dxy': {'xaxis':'p_{T} (GeV)', 'yaxis': '|#Delta_{xy}|'},
'pt_v_dz' : {'xaxis':'p_{T} (GeV)', 'yaxis': '|#Delta_{z}|'},
}
for plot,kwargs in plots.iteritems():
mPlotter.plot2D(plot,'hpp_{0}'.format(plot),logz=0,**kwargs)
mPlotter.clearHistograms()
mPlotter.addHistogram('Z',sigMap['Z'])
for plot,kwargs in plots.iteritems():
mPlotter.plot2D(plot,'dy_{0}'.format(plot),logz=1,**kwargs)
'TTV' : ['TTWJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8'],
'ZG' : ['ZGTo2LG_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'WW' : ['WWTo2L2Nu_13TeV-powheg'],
'Z' : ['DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8',
'DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'TT' : ['TTJets_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'data': ['DoubleMuon',
'DoubleEG',
'MuonEG',
'SingleMuon',
'SingleElectron'],
'HppHmm500GeV' : ['HPlusPlusHMinusMinusHTo4L_M-500_13TeV-pythia8'],
}
ePlotter.addHistogram('HppHmm500GeV',sigMap['HppHmm500GeV'])
plots = {
'pt_v_dxy': {'xaxis':'p_{T} (GeV)', 'yaxis': '|#Delta_{xy}|'},
'pt_v_dz' : {'xaxis':'p_{T} (GeV)', 'yaxis': '|#Delta_{z}|'},
}
for plot,kwargs in plots.iteritems():
ePlotter.plot2D(plot,'hpp_{0}'.format(plot),logz=0,**kwargs)
ePlotter.clearHistograms()
ePlotter.addHistogram('Z',sigMap['Z'])
for plot,kwargs in plots.iteritems():
ePlotter.plot2D(plot,'dy_{0}'.format(plot),logz=1,**kwargs)
'DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'
],
'TT': ['TTJets_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8'],
'data':
['DoubleMuon', 'DoubleEG', 'MuonEG', 'SingleMuon', 'SingleElectron'],
'HppHmm500GeV': ['HPlusPlusHMinusMinusHTo4L_M-500_13TeV-pythia8'],
}
ePlotter.addHistogram('HppHmm500GeV', sigMap['HppHmm500GeV'])
plots = {
'pt_v_dxy': {
'xaxis': 'p_{T} (GeV)',
'yaxis': '|#Delta_{xy}|'
},
'pt_v_dz': {
'xaxis': 'p_{T} (GeV)',
'yaxis': '|#Delta_{z}|'
},
}
for plot, kwargs in plots.iteritems():
ePlotter.plot2D(plot, 'hpp_{0}'.format(plot), logz=0, **kwargs)
ePlotter.clearHistograms()
ePlotter.addHistogram('Z', sigMap['Z'])
for plot, kwargs in plots.iteritems():
ePlotter.plot2D(plot, 'dy_{0}'.format(plot), logz=1, **kwargs)
# sum gen matched
for plot in plots:
for chan in chans:
plotnames = {}
for sample in samples:
plotnames[sample] = [
'{0}/{1}/{2}'.format('SS1', chan, plot),
'{0}/{1}/{2}'.format('SS2', chan, plot)
]
plotnames['data'] = ['{0}/{1}/{2}'.format('SS', chan, plot)]
savename = '{0}/{1}/{2}'.format('SS12', chan, plot)
chargePlotter.plot(plotnames, savename, **plots[plot])
# ratios of SS/OS as func of pt/eta
chargePlotter.clearHistograms()
allSamplesDict = {'MC': []}
for s in samples:
allSamplesDict['MC'] += sigMap[s]
chargePlotter.addHistogram('MC',
allSamplesDict['MC'],
style={'linecolor': ROOT.kRed})
chargePlotter.addHistogram('data',
sigMap['data'],
style={'linecolor': ROOT.kBlack})
ptbins = [10, 20, 30, 40, 50, 60, 80, 100, 200, 1000]
etabins = [-2.5, -2.0, -1.479, -1.0, -0.5, 0., 0.5, 1.0, 1.479, 2.0, 2.5]
