def GetFFHist(f,
k,
r,
c,
p='ttbar',
v='GRL',
num_or_den='Den',
syst='',
add_desert=False): # file key region channel process variable
import pennSoftLepton.PyAnalysisPlotting as anaplot
other = '%s_%s' % (p, v)
rtmp = r
if r == 'all':
rtmp = 'ltt'
fullkey = ('FFTool_%s_%s_%s_%s%s' %
(k, rtmp, syst, c, num_or_den)).replace('__', '_')
hists = anaplot.GetPassEventBkgHistos(v, fullkey, p, f)
if r == 'all' and ((c not in ['euu', 'uee']) or add_desert):
hists += anaplot.GetPassEventBkgHistos(v,
fullkey.replace('ltt',
'tlt'), p, f)
hists += anaplot.GetPassEventBkgHistos(v,
fullkey.replace('ltt',
'ttl'), p, f)
if not hists:
print 'Found no histograms for', fullkey
return 0
hist = hists[0]
if len(hists) > 1: hist.Add(hists[1])
if len(hists) > 2: hist.Add(hists[2])
return hist
def GetFFHist(f,
k,
r,
c,
p='ttbar',
v='MTW',
num_or_den='Den'): # file key region channel process variable
other = '%s_%s' % (p, v)
rtmp = r
if r == 'all':
rtmp = 'ltt'
keyregionchannel = 'PassEvent_FFTool_%s_%s_%s%s' % (k, rtmp, c, num_or_den)
#print 'Adding','%s/%s_%s'%(keyregionchannel,keyregionchannel,other)
print 'Adding', ('FFTool_%s_%s_%s%s' % (k, rtmp, c, num_or_den)).replace(
'__', '_')
hists = anaplot.GetPassEventBkgHistos(
v, ('FFTool_%s_%s_%s%s' % (k, rtmp, c, num_or_den)).replace('__',
'_'), p, f)
if not hists:
return 0
hist = hists[0]
if r == 'all' and c not in ['euu', 'uee']:
hist.Add(GetFFHist(f, k, 'tlt', c, p, v, num_or_den))
hist.Add(GetFFHist(f, k, 'ttl', c, p, v, num_or_den))
return hist
def main(options, args):
pm = u"\u00B1"
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
#
# Tables. E.g. MakeDetailedTable('')
#
MakeDetailedTable(options)
print 'done.'
return
def GetFFHistNew(f,k,r,c,p='ttbar',v='MTW',num_or_den='Den') : # file key region channel process variable
other = '%s_%s'%(p,v)
rtmp = r
if r == 'all' :
rtmp = 'ltt'
keyregionchannel = ('FFTool_%s_%s_%s%s'%(k,rtmp,c,num_or_den)).replace('__','_')
print 'Adding',keyregionchannel
hists = anaplot.GetPassEventBkgHistos(v,keyregionchannel,p,f)
if not hists :
print 'NOT Adding (was missing): ',keyregionchannel
return 0
hist = hists[0]
if r == 'all' :
hist.Add(GetFFHistNew(f,k,'tlt',c,p,v,num_or_den))
hist.Add(GetFFHistNew(f,k,'ttl',c,p,v,num_or_den))
return hist
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
#
# Tables. E.g. MakeDetailedTable('')
#
MakeDetailedTable(options)
print 'done.'
return
if __name__ == '__main__':
p = anaplot.PassEventPlottingOptParser()
p.p.remove_option('--susy')
p.p.remove_option('-p')
p.p.add_option('--region',
'-r',
type='string',
default='all',
dest='region',
help='Region (ttt,ltt,tlt,ttl,all (all means ltt+tlt+ttl)')
p.p.add_option('--channel',
'-c',
type='string',
default='all',
dest='channel',
help='Channel (eee,euu,uee,uuu,all)')
p.p.add_option('--bkgs',
def main(options,args) :
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
ROOT.gStyle.SetPaintTextFormat("4.3f ")
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(',') :
if not v : continue
xlabel = options.histformat[v][3]
n,low,high = options.histformat[v][:3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,'rebin') and v in options.usermodule.rebin.keys() :
rebin = options.usermodule.rebin[v]
if options.file :
bkg_processes = options.processes.replace('data','').replace(',,',',')
bkg_hists = anaplot.GetPassEventBkgHistos(v,options.key,bkg_processes,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if 'data' in options.processes :
data_hist = anaplot.GetPassEventBkgHistos(v,options.key,'data',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
#data_hist = anaplot.GetPassEventBkgHistos(v,'FFTool_z_mccl_ltt_allNum','zjetdd',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
if options.susy :
sig_hists = anaplot.GetPassEventSigHistos(v,options.key,options.susy,normalize=options.normalize,rebin=rebin)
cans.append(anaplot.DrawHistos('%s_%s'%(options.key,v),v,xlabel,bkg_hists,sig_hists,data_hist=data_hist,dostack=options.stack,log=options.log,ratio=options.ratio,fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1],low,high)
#
# Cutflow
#
f = ROOT.TFile(options.file)
if f.IsZombie() :
print 'exiting'
return
PrintCutflow(options.key
,f.Get('PassEvent_%s/PassEvent_%s_PassW'%(options.key,options.key))
,samp_list=options.processes.split(',')+['all']
,scientific=True)
f.Close()
raw_input('Pausing. Press enter to exit.')
if options.save :
for can in cans :
can.Print(can.GetName()+'.pdf')
can.Print(can.GetName()+'.eps')
print 'done.'
return
def main(options,args) :
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
style = ROOT.gROOT.GetStyle('mystyle')
style.SetEndErrorSize(0)
channel = 'all'
if options.e :
channel = 'Ele'
if options.mu :
channel = 'Mu'
options.key = 'FFTool_ttt_%sNum'%(channel)
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(',') :
if not v : continue
xlabel = options.histformat[v][3]
n,low,high = options.histformat[v][:3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,'rebin') and v in options.usermodule.rebin.keys() :
rebin = options.usermodule.rebin[v]
if options.file :
bkg_processes = options.processes.replace('data','').replace(',,',',')
#bkg_hists = anaplot.GetPassEventBkgHistos(v,options.key,bkg_processes,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)
bkg_hists.append(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'vvv',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.05,0.20))[0])
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'tother',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.05,0.13))[0])
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'tz',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.05,0.15))[0])
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'ttv',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.05,0.13))[0])
# bkg_hists[-1].Scale(3.15813/3.20905) # all other MC (but not ttbar) scaled down lumi-wise
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'ttbar',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.32)[0])
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'tw',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.32)[0])
AddIf(bkg_hists[-1],anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'qqww',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.32))
#bkg_hists[-1].SetTitle('t#bar{t}/Wt/WW/ttv/other')
bkg_hists[-1].SetTitle('Others')
bkg_hists.append(anaplot.GetPassEventBkgHistos(v,'FFTool_ttt_%sNum'%(channel),'zz',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.05,0.08,0.04))[0])
# bkg_hists[-1].Scale(3.15813/3.20905) # ZZ scaled down lumi-wise
bkg_hists[-1].SetTitle('ZZ')
bkg_hists.append(anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'zjetdd' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True)[0])
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'ttbar' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True)[0],-1)
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'tw' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True)[0],-1)
AddIf(bkg_hists[-1],anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'qqww',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True),-1)
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'wz' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True)[0],-1)
bkg_hists[-1].Add(anaplot.GetPassEventBkgHistos(v,'FFTool_z_data_ltt_%sNum'%(channel),'zz' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.00,ltt_tlt_ttl=True)[0],-1)
for i in range(bkg_hists[-1].GetNbinsX()) :
bkg_hists[-1].SetBinError(i+1,bkg_hists[-1].GetBinContent(i+1)*0.38)
bkg_hists[-1].SetTitle('Z+j / Z#gamma')
import math
pm = u"\u00B1"
print '%s: %2.2f%s%2.2f'%('zjetdd',bkg_hists[-1].Integral(0,bkg_hists[-1].GetNbinsX()+1),pm,math.sqrt(sum(list(bkg_hists[-1].GetSumw2()))))
bkg_hists += anaplot.GetPassEventBkgHistos(v,options.key,'wz',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=Q(0.07,0.05))
bkg_hists[-1].Scale(1.17/1.15)
bkg_hists[-1].SetTitle('W^{#pm}Z #times 1.17')
# bkg_hists = []
# bkg_hists.append(ROOT.TH1F('hist','hist',500,0,500))
# for i in range(bkg_hists[-1].GetNbinsX()) :
# bkg_hists[-1].Fill(i+0.5)
# for i in bkg_hists :
# taxisfunc.PutOverflowIntoLastBin(i,high)
# for b in bkg_hists :
# if b.GetTitle() == 'zjetdd' :
# for i in range(b.GetNbinsX()) :
# b.SetBinError(i+1,b.GetBinContent(i+1)*0.38)
# if b.GetTitle() == 't#bar{t}/Wt/WW/ttv/other' :
# for i in range(b.GetNbinsX()) :
# b.SetBinError(i+1,b.GetBinContent(i+1)*0.32)
# if b.GetTitle() == '' :
# for i in range(b.GetNbinsX()) :
# b.SetBinError(i+1,b.GetBinContent(i+1)*0.32)
anaplot.PrepareBkgHistosForStack(bkg_hists,colors_dict = colors_dict)
for i in bkg_hists[:-1] :
i.SetLineColor(i.GetFillColor())
bkg_hists[-1].SetLineColor(ROOT.kRed)
if 'data' in options.processes :
data_hist = anaplot.GetPassEventBkgHistos(v,options.key,'data',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
#data_hist = anaplot.GetPassEventBkgHistos(v,'FFTool_z_mccl_ltt_%sNum'%(channel),'zjetdd',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
taxisfunc.PutOverflowIntoLastBin(data_hist,high)
if options.susy :
sig_hists = anaplot.GetPassEventSigHistos(v,options.key,options.susy,normalize=options.normalize,rebin=rebin)
cans.append(DrawHistos('%s_%s'%(options.key,v),v,xlabel,bkg_hists,sig_hists,data_hist=data_hist,dostack=options.stack,log=options.log,ratio=options.ratio,fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1],low,high)
taxisfunc.SetYaxisRanges(cans[-1],0,57.15)
#
# Cutflow
#
f = ROOT.TFile(options.file)
if f.IsZombie() :
print 'exiting'
return
PrintCutflow(options.key
,f.Get('PassEvent_%s/PassEvent_%s_PassW'%(options.key,options.key))
,samp_list=options.processes.split(',')+['all']
,scientific=True)
f.Close()
raw_input('Pausing. Press enter to exit.')
if options.save :
for can in cans :
can.Print(can.GetName()+'.pdf')
can.Print(can.GetName()+'.eps')
print 'done.'
return
#!/usr/bin/env python
import ROOT
import pennSoftLepton.PyAnalysisPlotting as anaplot
import math
from array import array
from pennSoftLepton.PyRandomStuff import GetFFHist,AddFFHistIf
anaplot.LoadRootCore()
version_emmanuel = True
variables = []
if version_emmanuel :
variables = ['PtW','MTW','M3l','Mll','met_Et','NJets','NJetsLtEta2p5','PtllZ','PtllZ_Rebinned','YZminusYlW','MtWZ','DeltaPhiZWSyst','MWZ','NPV','jetPt','jetRapidity']
else :
variables = list(ROOT.PSL.GetAllVariableStrings())
for i in ['lepPt','lepEta','lepCharge'] :
for j in ['lep0_index','lep1_index','lep2_index',
'lepW_index','lepleadZ_index','lepsubleadZ_index'] :
variables += ['%s[%s]'%(i,j)]
skip_them = '\
nBaselineMuons nBaselineElectrons met_sumet jet0_index jet1_index \
DeltaRll PassTriggerEle PassTriggerMu PassTriggerMatch \
AntiIDSF_lep3 AntiIDSF_lep3_pt AntiIDSF_lep3_eta AntiIDSF_lep3_phi AntiIDSF_lep3_flavor \
AntiIDSF_lep3_pt_reco AntiIDSF_lep3_eta_reco AntiIDSF_lep3_phi_reco AntiIDSF_lep3_flavor_reco \
AntiIDSF_lep3_match_DR AntiIDSF_lep3_origin AntiIDSF_lep3_type NlepsfromZ AntiIDSF_lep3_truth_origin \
AntiIDSF_lep3_truth_type XCheckAntiIDSF_lep3_pt XCheckAntiIDSF_lep3_eta XCheckAntiIDSF_lep3_phi \
XCheckAntiIDSF_lep3_flavor XCheckAntiIDSF_lep3_origin XCheckAntiIDSF_lep3_type \
passLarError passTileError passSctError passCoreBit passPrimaryVtx \
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_b, trees_b, keys_b, cf_b = anaplot.GetTreesFromFiles(options.bkgs)
files_s, trees_s, keys_s, cf_s = anaplot.GetTreesFromFiles(options.susy)
file_d, tree_d, key_d, cf_d = anaplot.GetTreesFromFiles(options.data)
options.fb, lumi_scale_factor = helpers.GetTTreeLumiScaleFactor(
files_b + files_s, options.fb)
dweight = ''
weight = 'TotalWeightNoSF*lepSFRecoIdIso[lep0_index]*lepSFRecoIdIso[lep1_index]*lepSFRecoIdIso[lep2_index]*EvtTrigSF*AntiIDSF_lep3*PassEvent_SMWZsig'
#weight = 'TotalWeightNoPupNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
dweight = '(' + ' && '.join(options.cuts) + ')'
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
if hasattr(options.usermodule, 'dataweight'):
dweight += '*(%s)' % (options.usermodule.dataweight)
cans = []
# get the histograms from the files
for vi, v1 in enumerate(options.variables.split(',')):
n1, low1, high1 = options.histformat[v1][:3]
xlabel1 = options.histformat[v1][3]
rebin1 = []
if hasattr(options.usermodule,
'rebin') and v1 in options.usermodule.rebin.keys():
rebin1 = options.usermodule.rebin[v1]
for vj, v2 in enumerate(options.variables.split(',')):
if v2 == v1: continue
if vj > vi: continue
n2, low2, high2 = options.histformat[v2][:3]
xlabel2 = options.histformat[v2][3]
rebin2 = []
if hasattr(options.usermodule,
'rebin') and v2 in options.usermodule.rebin.keys():
rebin2 = options.usermodule.rebin[v2]
bkg_hists = []
sig_hists = []
data_hist = None
if options.bkgs:
bkg_hists = anaplot.Get2dVariableHistsFromTrees(
trees_b,
keys_b,
v1,
v2,
weight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)
anaplot.PrepareBkgHistosForStack(bkg_hists)
for i, h in enumerate(bkg_hists):
canname = '%s_%s_%s' % (v1, v2, keys_b[i])
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
if options.susy:
sig_hists = anaplot.Get2dVariableHistsFromTrees(
trees_s,
keys_s,
v1,
v2,
weight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)
for i, h in enumerate(sig_hists):
canname = '%s_%s_%s' % (v1, v2, keys_s[i])
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
if options.data:
data_hist = anaplot.Get2dVariableHistsFromTrees(
tree_d,
key_d,
v1,
v2,
dweight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)[0]
data_hist.SetLineWidth(2)
data_hist.SetLineColor(1)
data_hist.SetMarkerColor(1)
canname = '%s_%s_%s' % (v1, v2, 'data')
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
bkg_hists,
sig_hists,
data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return
v,
xlabel,
bkg_hists,
sig_hists,
data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return
if __name__ == '__main__':
p = anaplot.TreePlottingOptParser()
options, args = p.parse_args()
if not options.variables:
print 'Error! Please specify a variable!'
sys.exit()
main(options, args)
def main(options, args):
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
style = ROOT.gROOT.GetStyle('mystyle')
style.SetEndErrorSize(0)
ROOT.gStyle.SetPaintTextFormat("4.3f ")
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(','):
if not v: continue
xlabel = options.histformat[v][3]
n, low, high = options.histformat[v][:3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if options.file:
bkg_hists = []
bkg_hists.append(
anaplot.GetPassEventBkgHistos(v,
options.key,
'zz',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=Q(0.05, 0.08,
0.04))[0])
bkg_hists[-1].Add(
anaplot.GetPassEventBkgHistos(v,
options.key,
'vvv',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=Q(0.05, 0.20))[0])
bkg_hists[-1].SetTitle('Others')
bkg_hists.append(
anaplot.GetPassEventBkgHistos(v,
options.key,
'ttv',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=Q(0.05, 0.13))[0])
bkg_hists[-1].SetTitle('tt+V')
bkg_hists.append(
anaplot.GetPassEventBkgHistos(v,
options.key,
'wz',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=Q(0.05, 0.07))[0])
bkg_hists[-1].Scale(1.17 / 1.15)
bkg_hists[-1].SetTitle('W^{#pm}Z #times 1.17')
bkg_hists.append(
anaplot.GetPassEventBkgHistos(v,
options.key,
'ttbar',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=0.)[0])
bkg_hists[-1].Add(
anaplot.GetPassEventBkgHistos(v,
options.key,
'tw',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=0.)[0])
bkg_hists[-1].Add(
anaplot.GetPassEventBkgHistos(v,
options.key,
'qqww',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high,
globalError=0.)[0])
bkg_hists[-1].SetTitle('t#bar{t} / Wt / WW')
#bkg_hists.append(anaplot.GetPassEventBkgHistos(v,options.key,'zjet' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.)[0])
#bkg_hists.append(anaplot.GetPassEventBkgHistos(v,options.key,'zgam' ,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high,globalError=0.)[0])
anaplot.PrepareBkgHistosForStack(bkg_hists,
colors_dict=colors_dict)
for i in bkg_hists:
i.SetLineColor(i.GetFillColor())
data_hist = anaplot.GetPassEventBkgHistos(
v,
options.key,
'data',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high)[0]
#data_hist = anaplot.GetPassEventBkgHistos(v,'FFTool_z_mccl_ltt_allNum','zjetdd',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
if options.susy:
sig_hists = anaplot.GetPassEventSigHistos(
v,
options.key,
options.susy,
normalize=options.normalize,
rebin=rebin)
#bkg_hists[0].GetXaxis().SetNdivisions(5,0,0)
cans.append(
DrawHistos('%s_%s' % (options.key, v),
v,
xlabel,
bkg_hists,
sig_hists,
data_hist=data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1], low, high)
taxisfunc.SetYaxisRanges(cans[-1], 0, 12 * 0.9525)
taxisfunc.SetNdivisions(cans[-1], 9, 0, 0)
#
# Cutflow
#
f = ROOT.TFile(options.file)
if f.IsZombie():
print 'exiting'
return
PrintCutflow(options.key,
f.Get('PassEvent_%s/PassEvent_%s_PassW' %
(options.key, options.key)),
samp_list=options.processes.split(',') + ['all'],
scientific=True)
f.Close()
raw_input('Pausing. Press enter to exit.')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
can.Print(can.GetName() + '.eps')
print 'done.'
return
def main(options, args):
anaplot.LoadRootCore()
files_b, trees_b, keys_b, cf_b = anaplot.GetTreesFromFiles(options.bkgs)
files_s, trees_s, keys_s, cf_s = anaplot.GetTreesFromFiles(options.susy)
file_d, tree_d, key_d, cf_d = anaplot.GetTreesFromFiles(options.data)
all_cutflows = cf_b + cf_s + cf_d
options.fb, lumi_scale_factor = helpers.GetTTreeLumiScaleFactor(
files_b + files_s, options.fb)
for i in all_cutflows:
for j in i:
j.Scale(lumi_scale_factor)
dweight = ''
weight = 'TotalWeightNoSF'
# if ''.join(options.cuts) :
# weight = weight+'*(%s)'%(' && '.join(options.cuts))
# dweight = '('+' && '.join(options.cuts)+')'
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
if hasattr(options.usermodule, 'dataweight'):
dweight += '*(%s)' % (options.usermodule.dataweight)
cuts = []
samples = []
data_index = -1
if options.bkgs:
samples += list(
a.replace('.root', '') for a in options.bkgs.split(','))
samples += ['Total Bkg.']
totbkg_index = len(samples) - 1
if options.susy:
samples += list(
a.replace('.root', '') for a in options.susy.split(','))
if options.data:
samples += ['data']
data_index = len(samples) - 1
samples += ['s/b']
s_over_b_index = len(samples) - 1
samples += ['purity']
purity_index = len(samples) - 1
print samples
#
# Figure out what all the cuts were
#
firsthistlist = all_cutflows[0]
for i in firsthistlist:
for y in range(i.GetNbinsY(), 0, -1):
cuts.append(i.GetYaxis().GetBinLabel(y))
if hasattr(options.usermodule, 'cutflow'):
for i in options.usermodule.cutflow:
cuts.insert(0, i[0])
cuts.reverse()
print cuts
#
# Make a histogram to fill
#
cutflow_hist = ROOT.TH2F('Cutflow', 'Cutflow', len(samples), 0,
len(samples), len(cuts), 0, len(cuts))
for i in range(len(samples)):
cutflow_hist.GetXaxis().SetBinLabel(i + 1, samples[i])
for i in range(len(cuts)):
cutflow_hist.GetYaxis().SetBinLabel(i + 1, cuts[i])
#
# Grab the bin content from the "all" histograms that were saved in each file. (bkgs)
#
current_sample = 1
for i, histlist in enumerate(cf_b):
current_cut = len(cuts)
if hasattr(options.usermodule, 'cutflow'):
tree_cuts_list = list('(' + a[1] + ')'
for a in options.usermodule.cutflow)
for j in options.usermodule.cutflow:
tmp_weight = weight + '*(%s)' % (' && '.join(tree_cuts_list))
trees_b[keys_b[i]].Draw('GRL>>h1(2,0,2)', tmp_weight, 'egoff')
tree_cuts_list.pop()
hist = ROOT.gDirectory.Get('h1')
hist.Scale(lumi_scale_factor)
cutflow_hist.SetBinContent(current_sample, current_cut,
hist.GetBinContent(2))
cutflow_hist.SetBinError(current_sample, current_cut,
hist.GetBinError(2))
totbkg_content = cutflow_hist.GetBinContent(
totbkg_index + 1, current_cut) + hist.GetBinContent(2)
totbkg_error = math.sqrt(
cutflow_hist.GetBinError(totbkg_index +
1, current_cut)**2 +
hist.GetBinError(2)**2)
cutflow_hist.SetBinContent(totbkg_index + 1, current_cut,
totbkg_content)
cutflow_hist.SetBinError(totbkg_index + 1, current_cut,
totbkg_error)
ROOT.gROOT.ProcessLine('delete h1')
current_cut -= 1
for hist in histlist:
for x in range(hist.GetNbinsX()):
if hist.GetXaxis().GetBinLabel(x + 1) == 'all':
allbin = x + 1
break
for y in range(hist.GetNbinsY(), 0, -1):
cutflow_hist.SetBinContent(current_sample, current_cut,
hist.GetBinContent(allbin, y))
cutflow_hist.SetBinError(current_sample, current_cut,
hist.GetBinError(allbin, y))
totbkg_content = cutflow_hist.GetBinContent(
totbkg_index + 1, current_cut) + hist.GetBinContent(
allbin, y)
totbkg_error = math.sqrt(
cutflow_hist.GetBinError(totbkg_index +
1, current_cut)**2 +
hist.GetBinError(allbin, y)**2)
cutflow_hist.SetBinContent(totbkg_index + 1, current_cut,
totbkg_content)
cutflow_hist.SetBinError(totbkg_index + 1, current_cut,
totbkg_error)
current_cut -= 1
current_sample += 1
current_sample += 1
#
# susy (or wz!)
#
for i, histlist in enumerate(cf_s):
current_cut = len(cuts)
if hasattr(options.usermodule, 'cutflow'):
tree_cuts_list = list('(' + a[1] + ')'
for a in options.usermodule.cutflow)
for j in options.usermodule.cutflow:
#print tree_cuts_list
tmp_weight = weight + '*(%s)' % (' && '.join(tree_cuts_list))
trees_s[keys_s[i]].Draw('GRL>>h1(2,0,2)', tmp_weight, 'egoff')
tree_cuts_list.pop()
hist = ROOT.gDirectory.Get('h1')
hist.Scale(lumi_scale_factor)
signal_n = hist.GetBinContent(2)
cutflow_hist.SetBinContent(current_sample, current_cut,
signal_n)
if signal_n > 0:
cutflow_hist.SetBinError(current_sample, current_cut,
100. / float(math.sqrt(signal_n)))
tot_bkg = cutflow_hist.GetBinContent(totbkg_index + 1,
current_cut)
if tot_bkg:
cutflow_hist.SetBinContent(s_over_b_index + 1, current_cut,
signal_n / float(tot_bkg))
if tot_bkg + signal_n:
cutflow_hist.SetBinContent(
purity_index + 1, current_cut,
100. * signal_n / float(tot_bkg + signal_n))
ROOT.gROOT.ProcessLine('delete h1')
current_cut -= 1
for hist in histlist:
for x in range(hist.GetNbinsX()):
if hist.GetXaxis().GetBinLabel(x + 1) == 'all':
allbin = x + 1
break
for y in range(hist.GetNbinsY(), 0, -1):
signal_n = hist.GetBinContent(allbin, y)
cutflow_hist.SetBinContent(current_sample, current_cut,
signal_n)
cutflow_hist.SetBinError(current_sample, current_cut,
100. / float(math.sqrt(signal_n)))
tot_bkg = cutflow_hist.GetBinContent(totbkg_index + 1,
current_cut)
if tot_bkg:
cutflow_hist.SetBinContent(s_over_b_index + 1, current_cut,
signal_n / float(tot_bkg))
if tot_bkg + signal_n:
cutflow_hist.SetBinContent(
purity_index + 1, current_cut,
100. * signal_n / float(tot_bkg + signal_n))
current_cut -= 1
current_sample += 1
#
# data
#
for i, histlist in enumerate(cf_d):
current_cut = len(cuts)
if hasattr(options.usermodule, 'cutflow'):
tree_cuts_list = list('(' + a[1] + ')'
for a in options.usermodule.cutflow)
for j in options.usermodule.cutflow:
tmp_weight = weight + '*(%s)' % (' && '.join(tree_cuts_list))
tree_d[key_d[i]].Draw('GRL>>h1(2,0,2)', tmp_weight, 'egoff')
tree_cuts_list.pop()
hist = ROOT.gDirectory.Get('h1')
hist.Scale(lumi_scale_factor)
cutflow_hist.SetBinContent(current_sample, current_cut,
hist.GetBinContent(2))
cutflow_hist.SetBinError(current_sample, current_cut,
hist.GetBinError(2))
ROOT.gROOT.ProcessLine('delete h1')
current_cut -= 1
for hist in histlist:
for x in range(hist.GetNbinsX()):
if (hist.GetXaxis().GetBinLabel(x + 1) == 'data'):
allbin = x + 1
break
for y in range(hist.GetNbinsY(), 0, -1):
cutflow_hist.SetBinContent(current_sample, current_cut,
hist.GetBinContent(allbin, y))
cutflow_hist.SetBinError(current_sample, current_cut,
hist.GetBinError(allbin, y))
current_cut -= 1
current_sample += 1
PrintCutflow('Cutflow',
cutflow_hist,
samp_list=','.join(samples),
latex=options.latex)
return
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_b, trees_b, keys_b, cf_b = anaplot.GetTreesFromFiles(options.bkgs)
files_s, trees_s, keys_s, cf_s = anaplot.GetTreesFromFiles(options.susy)
file_d, tree_d, key_d, cf_d = anaplot.GetTreesFromFiles(options.data)
options.fb, lumi_scale_factor = helpers.GetTTreeLumiScaleFactor(
files_b + files_s, options.fb)
dweight = ''
weight = 'TotalWeightNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
dweight = '(' + ' && '.join(options.cuts) + ')'
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
if hasattr(options.usermodule, 'dataweight'):
dweight += '*(%s)' % (options.usermodule.dataweight)
cans = []
# get the histograms from the files
for v in options.variables.split(','):
n, low, high = options.histformat[v][:3]
xlabel = options.histformat[v][3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if options.bkgs:
bkg_hists = anaplot.GetVariableHistsFromTrees(
trees_b,
keys_b,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if options.susy:
sig_hists = anaplot.GetVariableHistsFromTrees(
trees_s,
keys_s,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)
if options.data:
data_hist = anaplot.GetVariableHistsFromTrees(
tree_d,
key_d,
v,
dweight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)[0]
data_hist.SetLineWidth(2)
data_hist.SetLineColor(1)
data_hist.SetMarkerColor(1)
nsignal = 0
for si, s in enumerate(keys_s):
mass_map = GetMassesMap()
for i in mass_map.keys():
if str(i) in sig_hists[si].GetName():
title = '%s,%s' % (mass_map[i]['mc1'], mass_map[i]['mn1'])
sig_hists[si].SetTitle(title)
sig_hists[si].SetLineWidth(2)
sig_hists[si].SetLineColor(signal_colors[nsignal])
sig_hists[si].SetMarkerColor(signal_colors[nsignal])
nsignal += 1
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
bkg_hists,
sig_hists,
data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return
def main(options, args):
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
options.keys = []
if not options.e:
options.keys += [
options.key + '_ttt_MuNum', options.key + '_ltt_MuDen'
]
if not options.mu:
options.keys += [
options.key + '_ttt_EleNum', options.key + '_ltt_EleDen'
]
print options.keys
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(','):
if not v: continue
n, low, high = options.histformat[v][:3]
lep_pt_dijet_num = None
lep_pt_dijet_den = None
for k in options.keys:
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if ('lepPt' in v) and ('Mu' in k):
rebin = [0, 9, 15, 20, 30, 100]
if options.file:
bkg_processes = options.processes.replace('data', '').replace(
',,', ',')
bkg_hists = anaplot.GetPassEventBkgHistos(
v,
k,
bkg_processes,
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if 'data' in options.processes:
data_hist = anaplot.GetPassEventBkgHistos(
v,
k,
'data',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high)[0]
xlabel = ROOT.PSL.GetXaxisLabel(v.split('[')[0])
cans.append(
anaplot.DrawHistos('%s_%s' % (k, v),
v,
xlabel,
bkg_hists,
sig_hists,
data_hist=data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1], low, high)
#
# Specifically get the fake factor in pt:
#
cans_divide = []
v = 'lepPt[lepW_index]'
rebin_mu = [0, 9, 15, 20, 30, 100]
rebin_e = [0, 9, 15, 20, 30, 50, 100]
hists_MuNum = dict()
hists_MuDen = dict()
hists_EleNum = dict()
hists_EleDen = dict()
mu_options = options.file, options.normalize, rebin_mu
e_options = options.file, options.normalize, rebin_e
for p in options.processes.split(','):
hists_MuNum[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ttt_MuNum', p, *mu_options)[0]
hists_MuDen[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ltt_MuDen', p, *mu_options)[0]
hists_EleNum[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ttt_EleNum', p, *e_options)[0]
hists_EleDen[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ltt_EleDen', p, *e_options)[0]
z_w = ''
tmp = ROOT.TFile(options.file)
syst_check = 'PassEvent_FFTool_forsyst_%s_ttt_MuNum/PassEvent_FFTool_forsyst_%s_ttt_MuNum_zjet_lepPt_antilep0_index' % (
'wid', 'wid')
print syst_check
if tmp.Get(syst_check):
z_w = 'wid'
elif tmp.Get(syst_check.replace('wid', 'zid')):
z_w = 'zid'
if z_w and options.syst:
do_z = (z_w == 'zid')
# try to get SR FF
hists_MuNum['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'zjet', *mu_options)[0]
if True:
hists_MuDen['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_MuDen', 'zjet',
*mu_options)[0]
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'zjet', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'zjet', *mu_options)[0])
hists_MuNum['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'zgam', *mu_options)[0])
if True:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepW_index',
'FFTool_forsyst_ltt_MuDen',
'zgam', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'zgam', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'zgam', *mu_options)[0])
hists_EleNum['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'zjet', *e_options)[0]
if True:
hists_EleDen['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_EleDen', 'zjet',
*e_options)[0]
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'zjet', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'zjet', *e_options)[0])
hists_EleNum['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'zgam', *e_options)[0])
if True:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepW_index',
'FFTool_forsyst_ltt_EleDen',
'zgam', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'zgam', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'zgam', *e_options)[0])
# now for ttbar
hists_MuNum['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'ttbar', *mu_options)[0]
if True:
hists_MuDen['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_MuDen', 'ttbar',
*mu_options)[0]
if do_z:
hists_MuDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'ttbar', *mu_options)[0])
if do_z:
hists_MuDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'ttbar', *mu_options)[0])
hists_EleNum['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'ttbar', *e_options)[0]
if True:
hists_EleDen['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_EleDen', 'ttbar',
*e_options)[0]
if do_z:
hists_EleDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'ttbar', *e_options)[0])
if do_z:
hists_EleDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'ttbar', *e_options)[0])
hists_MuNum['zjet_sr'].SetName('zjet_sr')
hists_MuNum['zjet_sr'].SetTitle('zjet+z#gamma SR FF')
hists_EleNum['zjet_sr'].SetName('zjet_sr')
hists_EleNum['zjet_sr'].SetTitle('zjet+z#gamma SR FF')
if False:
hists_MuDen['zjet_sr'].Add(hists_MuDen['ttbar_sr'])
hists_EleDen['zjet_sr'].Add(hists_EleDen['ttbar_sr'])
hists_MuNum['zjet_sr'].Add(hists_MuNum['ttbar_sr'])
hists_EleNum['zjet_sr'].Add(hists_EleNum['ttbar_sr'])
hists_MuNum['zjet_sr'].SetTitle('zjet+z#gamma+ttbar SR FF')
hists_EleNum['zjet_sr'].SetTitle('zjet+z#gamma+ttbar SR FF')
hists_MuNum['zjet_sr'].Divide(hists_MuDen['zjet_sr'])
hists_EleNum['zjet_sr'].Divide(hists_EleDen['zjet_sr'])
hists_MuNum['ttbar_sr'].SetName('ttbar_sr')
hists_MuNum['ttbar_sr'].SetTitle('ttbar SR FF')
hists_EleNum['ttbar_sr'].SetName('ttbar_sr')
hists_EleNum['ttbar_sr'].SetTitle('ttbar SR FF')
hists_MuNum['ttbar_sr'].Divide(hists_MuDen['ttbar_sr'])
hists_EleNum['ttbar_sr'].Divide(hists_EleDen['ttbar_sr'])
print hists_MuNum.keys()
if (options.region == 'dijet') and 'dijet' in hists_EleNum.keys():
hists_MuNum['dijet'].SetLineColor(ROOT.kBlue + 1)
hists_MuNum['dijet'].SetMarkerColor(ROOT.kBlue + 1)
hists_EleNum['dijet'].SetLineColor(ROOT.kBlue + 1)
hists_EleNum['dijet'].SetMarkerColor(ROOT.kBlue + 1)
hists_MuNum['dijet'].Divide(hists_MuDen['dijet'])
hists_EleNum['dijet'].Divide(hists_EleDen['dijet'])
if (options.region == 'zjet') and 'zjet' in hists_EleNum.keys():
hists_MuNum['zjet'].SetTitle('zjet (no z#gamma) MC')
hists_EleNum['zjet'].SetTitle('zjet (no z#gamma) MC')
if 'zgam' in hists_EleNum.keys():
print '##############################################################################'
print '## Adding zgam to your estimate'
print '##############################################################################'
hists_MuNum['zjet'].Add(hists_MuNum['zgam'])
hists_EleNum['zjet'].Add(hists_EleNum['zgam'])
hists_MuNum['zjet'].SetTitle('zjet+z#gamma MC')
hists_EleNum['zjet'].SetTitle('zjet+z#gamma MC')
hists_MuNum['zjet'].SetLineColor(ROOT.kBlue + 1)
hists_MuNum['zjet'].SetMarkerColor(ROOT.kBlue + 1)
hists_EleNum['zjet'].SetLineColor(ROOT.kBlue + 1)
hists_EleNum['zjet'].SetMarkerColor(ROOT.kBlue + 1)
hists_MuNum['zjet'].Divide(hists_MuDen['zjet'])
hists_EleNum['zjet'].Divide(hists_EleDen['zjet'])
# cans.append(ROOT.TCanvas('%s_Mu_ff_dijet'%(v),'%s_Mu_ff'%(v),500,500))
# plotfunc.AddHistogram(cans[-1],dijet_hist_MuNum)
# plotfunc.FormatCanvasAxes(cans[-1])
# taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
# cans.append(ROOT.TCanvas('%s_Ele_ff_dijet'%(v),'%s_Ele_ff'%(v),500,500))
# plotfunc.AddHistogram(cans[-1],dijet_hist_EleNum)
# plotfunc.FormatCanvasAxes(cans[-1])
# taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
if 'data' in hists_EleNum.keys():
hists_EleNum['data'].SetTitle('With VV subtraction')
hists_EleDen['data'].SetTitle('With VV subtraction')
hists_MuNum['data'].SetTitle('With VV subtraction')
hists_MuDen['data'].SetTitle('With VV subtraction')
if (options.region == 'dijet'):
hists_EleNum['data_bws'] = hists_EleNum['data'].Clone()
hists_EleNum['data_bws'].SetName(
hists_EleNum['data_bws'].GetName() + '_bws')
hists_EleDen['data_bws'] = hists_EleDen['data'].Clone()
hists_EleDen['data_bws'].SetName(
hists_EleDen['data_bws'].GetName() + '_bws')
hists_MuNum['data_bws'] = hists_MuNum['data'].Clone()
hists_MuNum['data_bws'].SetName(hists_MuNum['data_bws'].GetName() +
'_bws')
hists_MuDen['data_bws'] = hists_MuDen['data'].Clone()
hists_MuDen['data_bws'].SetName(hists_MuDen['data_bws'].GetName() +
'_bws')
hists_EleNum['data_bws'].SetTitle('No EW subtraction')
hists_EleDen['data_bws'].SetTitle('No EW subtraction')
hists_MuNum['data_bws'].SetTitle('No EW subtraction')
hists_MuDen['data_bws'].SetTitle('No EW subtraction')
hists_EleNum['data_bzs'] = hists_EleNum['data_bws'].Clone()
hists_EleNum['data_bzs'].SetName(
hists_EleNum['data_bzs'].GetName() + '_bzs')
hists_EleDen['data_bzs'] = hists_EleDen['data_bws'].Clone()
hists_EleDen['data_bzs'].SetName(
hists_EleDen['data_bzs'].GetName() + '_bzs')
hists_MuNum['data_bzs'] = hists_MuNum['data_bws'].Clone()
hists_MuNum['data_bzs'].SetName(hists_MuNum['data_bzs'].GetName() +
'_bzs')
hists_MuDen['data_bzs'] = hists_MuDen['data_bws'].Clone()
hists_MuDen['data_bzs'].SetName(hists_MuDen['data_bzs'].GetName() +
'_bzs')
hists_EleNum['data_bzs'].SetTitle('With W subtraction')
hists_EleDen['data_bzs'].SetTitle('With W subtraction')
hists_MuNum['data_bzs'].SetTitle('With W subtraction')
hists_MuDen['data_bzs'].SetTitle('With W subtraction')
for i in ['wje', 'wjm', 'wjt', 'zjee', 'zjmm', 'zjtt']:
if i in hists_EleNum.keys():
print 'Subtracting', i
hists_EleNum['data'].Add(hists_EleNum[i], -1)
hists_EleDen['data'].Add(hists_EleDen[i], -1)
hists_MuNum['data'].Add(hists_MuNum[i], -1)
hists_MuDen['data'].Add(hists_MuDen[i], -1)
if i not in ['zjee', 'zjmm', 'zjtt']:
hists_EleNum['data_bzs'].Add(hists_EleNum[i], -1)
hists_EleDen['data_bzs'].Add(hists_EleDen[i], -1)
hists_MuNum['data_bzs'].Add(hists_MuNum[i], -1)
hists_MuDen['data_bzs'].Add(hists_MuDen[i], -1)
hists_MuNum['data_bws'].Divide(hists_MuDen['data_bws'])
hists_EleNum['data_bws'].Divide(hists_EleDen['data_bws'])
hists_MuNum['data_bzs'].Divide(hists_MuDen['data_bzs'])
hists_EleNum['data_bzs'].Divide(hists_EleDen['data_bzs'])
if (options.region == 'zjet'):
hists_EleNum['data_bvvs'] = hists_EleNum['data'].Clone()
hists_EleNum['data_bvvs'].SetName(
hists_EleNum['data_bvvs'].GetName() + '_bvvs')
hists_EleDen['data_bvvs'] = hists_EleDen['data'].Clone()
hists_EleDen['data_bvvs'].SetName(
hists_EleDen['data_bvvs'].GetName() + '_bvvs')
hists_MuNum['data_bvvs'] = hists_MuNum['data'].Clone()
hists_MuNum['data_bvvs'].SetName(
hists_MuNum['data_bvvs'].GetName() + '_bvvs')
hists_MuDen['data_bvvs'] = hists_MuDen['data'].Clone()
hists_MuDen['data_bvvs'].SetName(
hists_MuDen['data_bvvs'].GetName() + '_bvvs')
hists_EleNum['data_bvvs'].SetTitle('No VV subtraction')
hists_EleDen['data_bvvs'].SetTitle('No VV subtraction')
hists_MuNum['data_bvvs'].SetTitle('No VV subtraction')
hists_MuDen['data_bvvs'].SetTitle('No VV subtraction')
# 15% systematic on vv subtraction
hists_EleNum['data_vv15sys'] = hists_EleNum['data'].Clone()
hists_EleNum['data_vv15sys'].SetName(
hists_EleNum['data_vv15sys'].GetName() + '_vv15sys')
hists_EleDen['data_vv15sys'] = hists_EleDen['data'].Clone()
hists_EleDen['data_vv15sys'].SetName(
hists_EleDen['data_vv15sys'].GetName() + '_vv15sys')
hists_MuNum['data_vv15sys'] = hists_MuNum['data'].Clone()
hists_MuNum['data_vv15sys'].SetName(
hists_MuNum['data_vv15sys'].GetName() + '_vv15sys')
hists_MuDen['data_vv15sys'] = hists_MuDen['data'].Clone()
hists_MuDen['data_vv15sys'].SetName(
hists_MuDen['data_vv15sys'].GetName() + '_vv15sys')
hists_EleNum['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_EleDen['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_MuNum['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_MuDen['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
for i in ['wz', 'zz']:
if i in hists_EleNum.keys():
print 'Subtracting', i
hists_EleNum['data'].Add(hists_EleNum[i], -1)
hists_EleDen['data'].Add(hists_EleDen[i], -1)
hists_MuNum['data'].Add(hists_MuNum[i], -1)
hists_MuDen['data'].Add(hists_MuDen[i], -1)
hists_EleNum['data_vv15sys'].Add(hists_EleNum[i],
-1 + 0.15)
hists_EleDen['data_vv15sys'].Add(hists_EleDen[i],
-1 + 0.15)
hists_MuNum['data_vv15sys'].Add(hists_MuNum[i], -1 + 0.15)
hists_MuDen['data_vv15sys'].Add(hists_MuDen[i], -1 + 0.15)
hists_MuNum['data_bvvs'].Divide(hists_MuDen['data_bvvs'])
hists_EleNum['data_bvvs'].Divide(hists_EleDen['data_bvvs'])
hists_MuNum['data_vv15sys'].Divide(hists_MuDen['data_vv15sys'])
hists_EleNum['data_vv15sys'].Divide(hists_EleDen['data_vv15sys'])
hists_MuNum['data'].Divide(hists_MuDen['data'])
hists_EleNum['data'].Divide(hists_EleDen['data'])
f = ROOT.TFile('FakeFactors.root', 'recreate')
f.cd()
if 'data' in hists_EleNum.keys():
if not options.e: hists_MuNum['data'].Write("Muons")
if not options.mu: hists_EleNum['data'].Write("Electrons")
if not options.e: hists_MuNum['data_vv15sys'].Write("Muons_wzsyst")
if not options.mu:
hists_EleNum['data_vv15sys'].Write("Electrons_wzsyst")
f.Close()
g = ROOT.TFile('FakeFactors_mcClosure.root', 'recreate')
g.cd()
if (options.region == 'zjet'):
if not options.e: hists_MuNum['zjet'].Write('Muons')
if not options.mu: hists_EleNum['zjet'].Write('Electrons')
if (options.region == 'dijet'):
if not options.e: hists_MuNum['dijet'].Write('Muons')
if not options.mu: hists_EleNum['dijet'].Write('Electrons')
g.Close()
#
# systematic band histogram
#
from array import array
band = ROOT.TH1F('band', 'band', 5, array('d', [0, 15, 20, 30, 50, 100]))
def SetSysts(h_band, systs):
for i, sys in enumerate(systs):
h_band.SetBinContent(i + 1, 1)
h_band.SetBinError(i + 1, sys)
band.SetFillColor(ROOT.kOrange - 0)
band.SetMarkerSize(0)
band.SetMarkerColor(ROOT.kOrange - 0)
#
# Muon fake factor plots
#
if not options.e:
if 'zjet_sr' in hists_MuNum.keys():
cans.append(
plotfunc.RatioCanvas('lepPt_Mu_ff_systematic',
'%s_Mu_ff_systematic' % (v), 500, 500))
else:
cans.append(ROOT.TCanvas('lepPt_Mu_ff', '%s_Mu_ff' % (v), 500,
500))
if 'data' in hists_EleNum.keys():
if (options.region == 'dijet'):
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bws'])
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bzs'])
if 'dijet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_MuNum['dijet'])
if (options.region == 'zjet'):
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bvvs'])
#plotfunc.AddHistogram(cans[-1],hists_MuNum['data_vv15sys'])
pass
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_MuNum['data'])
if (options.region == 'zjet'):
if 'zjet' in hists_MuNum.keys():
plotfunc.AddHistogram(cans[-1], hists_MuNum['zjet'])
if 'zjet_sr' in hists_MuNum.keys():
if z_w == 'zid':
SetSysts(band, [0.0, 0.25, 0.2, 0.25, 0.25])
else:
SetSysts(band, [0.0, 0.0, 0.2, 0.30, 0.30])
plotfunc.AddHistogram(cans[-1].GetPrimitive('pad_bot'),
band, 'E2')
plotfunc.AddRatio(cans[-1], hists_MuNum['zjet_sr'],
hists_MuNum['zjet'])
#plotfunc.AddRatio(cans[-1],hists_MuNum['ttbar_sr'],hists_MuNum['zjet'])
if not plotfunc.CanvasEmpty(cans[-1]):
plotfunc.FormatCanvasAxes(cans[-1])
#taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
plotfunc.MakeLegend(cans[-1])
additionaltext = ('supporting triggers'
if options.region == 'dijet' else None)
plotfunc.FullFormatCanvasDefault(cans[-1],
sqrts=13,
lumi=options.fb,
additionaltext=additionaltext)
if 'zjet_sr' in hists_MuNum.keys():
taxisfunc.SetYaxisRanges(cans[-1].GetPrimitive('pad_bot'), -1,
3)
plotfunc.SetAxisLabels(cans[-1], 'p_{T} [GeV]', 'fake factor')
#
# electron fake factor plots
#
if not options.mu:
if 'zjet_sr' in hists_EleNum.keys():
cans.append(
plotfunc.RatioCanvas('lepPt_Ele_ff_systematic',
'%s_Ele_ff_systematic' % (v), 500, 500))
else:
cans.append(
ROOT.TCanvas('lepPt_Ele_ff', '%s_Ele_ff' % (v), 500, 500))
if 'data' in hists_EleNum.keys():
if (options.region == 'dijet'):
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bws'])
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bzs'])
if 'dijet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_EleNum['dijet'])
if (options.region == 'zjet'):
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bvvs'])
#plotfunc.AddHistogram(cans[-1],hists_EleNum['data_vv15sys'])
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_EleNum['data'])
if (options.region == 'zjet'):
if 'zjet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_EleNum['zjet'])
if 'zjet_sr' in hists_EleNum.keys():
if z_w == 'zid':
SetSysts(band, [0.0, 0.55, 0.30, 0.40, 0.60])
else:
SetSysts(band, [0.0, 0.0, 0.25, 0.25, 0.65])
plotfunc.AddHistogram(cans[-1].GetPrimitive('pad_bot'),
band, 'E2')
plotfunc.AddRatio(cans[-1], hists_EleNum['zjet_sr'],
hists_EleNum['zjet'])
#plotfunc.AddRatio(cans[-1],hists_EleNum['ttbar_sr'],hists_EleNum['zjet'])
if not plotfunc.CanvasEmpty(cans[-1]):
plotfunc.FormatCanvasAxes(cans[-1])
#taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
plotfunc.MakeLegend(cans[-1])
additionaltext = ('supporting triggers'
if options.region == 'dijet' else None)
plotfunc.FullFormatCanvasDefault(cans[-1],
sqrts=13,
lumi=options.fb,
additionaltext=additionaltext)
if 'zjet_sr' in hists_EleNum.keys():
taxisfunc.SetYaxisRanges(cans[-1].GetPrimitive('pad_bot'), -1,
3)
plotfunc.SetAxisLabels(cans[-1], 'p_{T} [GeV]', 'fake factor')
raw_input('Pausing. Press enter to exit.')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
can.Print(can.GetName() + '.eps')
print 'done.'
return
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_mc1, trees_mc1, keys_mc1, cf_mc1 = anaplot.GetTreesFromFiles(
options.mc1)
files_mc2, trees_mc2, keys_mc2, cf_mc2 = anaplot.GetTreesFromFiles(
options.mc2)
weight = 'TotalWeightNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
cans = []
# get the histograms from the files
for v in options.variables.split(','):
n, low, high = options.histformat[v][:3]
xlabel = options.histformat[v][3]
mc_hists = []
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if options.mc1:
mc_hists.append(
anaplot.GetVariableHistsFromTrees(trees_mc1,
keys_mc1,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin)[0])
mc_hists[-1].SetTitle(options.label1)
mc_hists[-1].SetLineWidth(2)
mc_hists[-1].SetLineColor(1)
mc_hists[-1].SetMarkerColor(1)
if options.mc2:
mc_hists.append(
anaplot.GetVariableHistsFromTrees(trees_mc2,
keys_mc2,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin)[0])
mc_hists[-1].SetTitle(options.label2)
mc_hists[-1].SetLineWidth(ROOT.kRed + 1)
mc_hists[-1].SetLineColor(ROOT.kRed + 1)
mc_hists[-1].SetMarkerColor(ROOT.kRed + 1)
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
mc_hists,
dostack=False,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return