def loadHistos(self):
''' Load the PDF and Scale histos and norm histos '''
t = TopHistoReader(self.path)
t.SetHistoNamePrefix(self.histoprefix)
t.SetIsData(1)
n = self.GetSampleName()
t.SetProcess(n)
t.SetChan(self.GetChan())
t.SetLevel(self.GetLevel())
#if self.GetNgenEvents() <= 0 : self.SetNgenEvents(t.GetNGenEvents())
self.SetYield(t.GetYield() * self.GetLumi())
self.hpdf = t.GetHisto(n, self.PDFhistoName)
self.hscale = t.GetHisto(n, self.scaleHistoName)
#self.hPS = t.GetHisto(n,self.PShistoName)
if self.pathToTrees != '' and self.motherfname != '':
self.LoadTreeSumOfWeights(self.pathToTrees, self.motherfname)
self.hsumpdf = t.GetNamedHisto(
self.normPDFhistoName
) if self.normPDFhistoName != '' else self.GetSumPDFhistoFromSumWTree(
)
self.hsumscale = t.GetNamedHisto(
self.normScaleHitstoName
) if self.normScaleHitstoName != '' else self.GetSumScaleHistoFromSumWTree(
)
self.SetNgenEvents(self.count)
self.nPDFweights = self.hsumpdf.GetNbinsX()
self.nScaleWeighs = self.hsumscale.GetNbinsX()
print '>> Count : ', self.count
print '>> SumOfWeights : ', self.sow
def GetYield2(path,
files,
ch='eee',
level='sr',
inc=None,
histopref='',
filepref='',
var='',
isdata=False):
t = TopHistoReader(path, files)
t.SetLevel(level)
t.SetChan(ch)
t.SetHistoNamePrefix(histopref)
#t.SetLumi(GetLumi(2018)*1000)
#t.SetLumi(GetLumi(year)*1000)
#t.SetLumi(1)
t.SetFileNamePrefix(filepref)
t.SetIsData(isdata)
if var != '':
pref = histopref + '_' if histopref != '' else ''
if inc == None:
h = t.GetNamedHisto(pref + var + '_' + ch)
else:
h = t.GetNamedHisto(pref + var + '_' + ch + '_' + inc)
y = h.GetBinContent(9)
else:
y = t.GetYield()
return y
def SavePlots(s, var='mt2', sampName='tt', tag='PDF uncertainty'):
tr = TopHistoReader(outpath + s)
a = HistoUnc(out + '/PDF%s/' % sampName,
var + sampName + s,
tag=tag,
xtit=titdic[var] if var in titdic.keys() else '')
a.SetLumi(GetLumi(year))
a.AddHistoNom(tr.GetNamedHisto(sampName, var))
a.AddHistoUp(tr.GetNamedHisto(sampName + '_' + s + 'Up', var))
a.AddHistoDown(tr.GetNamedHisto(sampName + '_' + s + 'Down', var))
a.Draw()
#gr.GetXaxis().SetLimits(165,180);
c.SetRightMargin(0.03)
c.Update()
for form in ['png', 'pdf']:
c.Print(outpath + outname + '_' + mode + '.' + form)
ch = 'ElMu'
lev = '2jets'
level = {'dilepton': 1, 'ZVeto': 2, 'MET': 3, '2jets': 4, '1btag': 5}
# Get acceptance numbers
from plotter.TopHistoReader import TopHistoReader
thr = TopHistoReader(path)
dic = {'tt': 'TT', 'up': 'TT_mtop178p5', 'down': 'TT_mtop166p5'}
GetAcc = lambda samp, ch, lev: thr.GetNamedHisto('Lep0Eta_%s_%s' % (ch, lev),
dic[samp]).Integral()
GetUnc = lambda samp, ch, lev: thr.GetNamedHisto('Yields_%s' % (ch), dic[samp]
).GetBinError(level[lev])
nom = GetAcc('tt', ch, lev)
up = GetAcc('up', ch, lev)
do = GetAcc('down', ch, lev)
mass = [166.5, 172.5, 178.5]
xsec = [xsecnom * (nom / do), xsecnom, xsecnom * (nom / up)]
#= [xsecunc*(nom/do), xsecunc, xsecunc*(nom/up)]
xsecerr = [GetUnc(x, ch, lev) for x in ['down', 'tt', 'up']]
DrawTopMassFit(mass, xsec, xsecerr, 'lin')
class CrossSection:
### Add background, signal and data numbers
def AddBkg(self, name, val, normunc=0, systunc=0, statunc=0, samples=''):
''' Add a bkg process (must include yield, name, uncertainties...) '''
self.bkg.append(
Process(name,
Yield=val,
NormUnc=normunc,
SystUnc=systunc,
StatUnc=statunc,
samples=samples))
def SetSignal(self, name, val, statunc=0, samples=''):
''' Set the signal process (must include yield, name, uncertainties...) '''
self.signal = Process(name,
Yield=val,
StatUnc=statunc,
samples=samples)
def SetData(self, n):
''' Number of observed events '''
self.data = n
self.dataunc = sqrt(n)
### Add uncertainties... experimental and modeling
def AddExpUnc(self, name, val):
''' Add the uncertainty 'name' with value 'val' to the experimental uncertainties '''
self.effUnc[name] = val
def AddModUnc(self, name, val=0., do=''):
''' Add the uncertainty 'name' with value 'val' to the modeling uncertainties (on acceptance)
if sample names are given (up/down) the uncertainty is read from the histos in that samples
'''
if isinstance(val, float):
self.accUnc[name] = val
else:
nom = self.GetSignalYield()
up = self.t.GetYield(val)
do = self.t.GetYield(do)
var = max(abs(up - nom), abs(do - nom)) / nom
self.AddModUnc(name, var)
### Setting methods
def SetTextFormat(self, textformat):
''' Set the format of the output tables (txt, tex) '''
self.textformat = textformat
def SetChan(self, ch):
''' Set the channel '''
self.chan = ch
def SetLevel(self, lev):
''' Set level '''
self.lev = lev
def SetThXsec(self, t):
''' Set the theoretical cross section using to normalize signal events '''
self.thxsec = t
def SetDoFiducial(self, val=True):
''' Boolean to activate printing the fiducial cross section '''
self.doFiducial = val
def SetLumi(self, l):
''' Set the luminosity '''
self.lumi = l
def SetLumiUnc(self, l):
''' Set relative lumi unc '''
self.lumiunc = l
def SetFiduEvents(self, f):
''' Number of fiducual (unweighted) events '''
self.nfidu = f
def SetGenEvents(self, g):
''' Number of generated events in the sample '''
self.ngen = g
def SetBR(self, b): # Use relative unc
''' The branching ratio to what we consider signal '''
self.BR = b
def SetOutPath(self, p):
''' Set the output path '''
self.outpath = p
### Get parameters...
def GetThXsec(self):
return self.thxsec
def GetLumi(self):
return self.lumi
def GetLumiUnc(self):
return self.lumiunc
def GetFiduEvents(self, sys=''):
return self.nfidu
def GetGenEvents(self):
return self.ngen
def GetBR(self):
return self.BR
def GetLevel(self):
return self.lev
def GetChan(self):
return self.chan
def GetBkg(self, name):
for b in self.bkg:
if b.GetName() == name: return b
print 'WARNING: not found background ' + name
def GetBkgTotRelUnc(self, name):
return self.GetBkg(name).GetTotRelUnc()
def GetBkgTotAbsUnc(self, name):
return self.GetBkgYield(name) * self.GetBkgTotRelUnc(name)
def GetBkgYield(self, name, sys=''):
pr = self.GetBkg(name)
if sys == '': return pr.GetYield()
elif IsUpSyst(sys): return pr.GetYield() * (1 + pr.GetTotRelUnc())
elif IsDownSyst(sys): return pr.GetYield() * (1 - pr.GetTotRelUnc())
else: return pr.GetYield() * (1 + pr.GetTotRelUnc())
def GetData(self):
return self.data
def GetDataUnc(self):
return self.dataunc
def GetSignal(self):
return self.signal
def GetSignalYield(self, sys='', d=''):
y = self.signal.GetYield()
if sys == '': return y
u = self.GetUnc(sys)
if IsDownSyst(d): return y * (1 - u)
return y * (1 + u)
def GetExpUnc(self, name=''):
if name == '': return self.effUnc
else: return self.effUnc[name]
def GetModUnc(self, name=''):
if name == '': return self.accUnc
else: return self.accUnc[name]
def GetUnc(self, name):
if name in self.modUnc.keys(): return self.GetModUnc(name)
elif name in self.effUnc.keys(): return self.GetEffUnc(name)
else: print 'WARNING: not found uncertainty \'%d\'' % name
return 0
def GetTotBkg(self, sys='', d=''):
''' Returns the total expected bkg '''
if sys != '' and sys in [x.GetName() for x in self.bkg]:
y = self.GetTotBkg()
var = self.GetBkgTotAbsUnc(sys)
y = y - var if IsDownSyst(sys + d) else y + var
else:
y = sum([x.GetYield() for x in self.bkg])
return y
def GetTotBkgStatUnc(self):
''' Returns the total stat unc on bkg '''
b = 0
for pr in self.bkg:
b += pr.GetStatUnc() * pr.GetStatUnc()
return sqrt(b)
def GetTotBkgSystUnc(self):
''' Returns the total syst unc on bkg '''
b = 0
for pr in self.bkg:
b += pr.GetSystAbsUnc() * pr.GetSystAbsUnc()
return sqrt(b)
def GetXsec(self, sys='', d=''):
''' Returns the measured cross section '''
data = self.GetData()
bkg = self.GetTotBkg(sys, d) if sys in [x.GetName() for x in self.bkg
] else self.GetTotBkg()
y = self.GetSignalYield(sys, d)
thxsec = self.GetThXsec()
return self.ComputeXsec(data, bkg, y)
def GetFiduXsec(self):
''' Returns the fiducial cross section '''
# fidu = inclusive*(A)
return self.ComputeXsec() * self.GetAcc()
def GetAcc(self, sys=''):
''' Returns the measured acceptance '''
return self.GetFiduEvents(sys) / (self.GetGenEvents() * self.GetBR())
def GetAccUnc(self):
''' Return the syst unc on acceptance '''
err = 0
for a in self.accUnc.values():
err += a * a
return sqrt(err)
def GetEff(self, sys=''):
''' Returns the measured efficiency '''
y = self.GetSignalYield(sys)
A = self.GetAcc()
BR = self.GetBR()
lum = self.GetLumi()
xth = self.GetThXsec()
return (y) / (A * lum * xth * BR)
def GetEffUnc(self):
''' Return the syst unc on efficiency '''
err = 0
for a in self.effUnc.values():
err += a * a
return sqrt(err)
def GetXsecSystUnc(self):
''' Returns the xsec syst unc on cross section '''
effunc = self.GetEffUnc()
accunc = self.GetAccUnc()
bkgunc2 = 0
for b in [x.GetName() for x in self.bkg]:
bkgunc2 += self.GetXsecBkgRelUnc(b) * self.GetXsecBkgRelUnc(b)
return sqrt(effunc * effunc + accunc * accunc + bkgunc2)
def GetXsecLumiUnc(self):
''' Returns the xsec lumi uncertainty on cross section '''
#return self.GetXsec()*(1/self.GetLumi() - 1/(self.GetLumi() * (1+self.GetLumiUnc()) ))
r = self.GetLumiUnc()
return (abs(r / (1 - r)) + abs(r / (1 + r))) / 2
def GetXsecStatUnc(self):
''' Returns the stat unc on cross section '''
xsec = self.ComputeXsec()
varUp = self.ComputeXsec(self.GetData() + self.GetDataUnc(),
self.GetTotBkg(), self.GetSignalYield())
varDo = self.ComputeXsec(self.GetData() - self.GetDataUnc(),
self.GetTotBkg(), self.GetSignalYield())
return max([abs(xsec - varDo) / xsec, abs(xsec - varUp) / xsec])
def GetXsecBkgRelUnc(self, bkgname):
''' Returns the relative unc on the xsec due to the total unc on a bkg estimation '''
nom = self.ComputeXsec()
varUp = self.ComputeXsec(self.GetData(), self.GetTotBkg(bkgname, 'Up'),
self.GetSignalYield())
varDo = self.ComputeXsec(self.GetData(),
self.GetTotBkg(bkgname, 'Down'),
self.GetSignalYield())
return max([abs(nom - varUp) / nom, abs(nom - varDo) / nom])
### Several printing methods!
def PrintYields(self, name='yields', doStat=True, doSyst=True):
t = OutText(self.outpath, name, "new", textformat=self.textformat)
t.SetTexAlign("l c")
nsem = 16 + 3 + 8 + (5 + 8 if doStat else 0) + (5 + 8 if doSyst else 0)
t.SetSeparatorLength(nsem)
t.line('%' + 'Yields for channel \'%s\' and level \'%s\'' %
(self.GetChan(), self.GetLevel()))
t.bar()
for pr in self.bkg:
name = t.fix(" %s" % pr.GetName(), 16, 'l', 0)
y = t.fix("%1.2f" % pr.GetYield(), 8, 0)
stat = t.fix("%1.2f" % pr.GetStatUnc(), 8, 0)
syst = t.fix("%1.2f" % pr.GetSystAbsUnc(), 8, 0)
t.line(name + t.vsep() + y + ((t.pm() + stat) if doStat else '') +
((t.pm() + syst) if doSyst else ''))
t.sep()
totbkg = t.fix("%1.2f" % self.GetTotBkg(), 8, 0)
totbkgstat = t.fix("%1.2f" % self.GetTotBkgStatUnc(), 8, 0)
totbkgsyst = t.fix("%1.2f" % self.GetTotBkgSystUnc(), 8, 0)
t.line(
t.fix(" Total bkg", 16, 'l', 0) + t.vsep() + totbkg +
((t.pm() + totbkgstat) if doStat else '') +
((t.pm() + totbkgsyst) if doSyst else ''))
t.sep()
y = self.GetSignalYield()
signal = t.fix(" %s" % (self.GetSignal().GetName()), 16, 'l', 0)
ysig = t.fix("%1.2f" % y, 8, 0)
sigunc = t.fix("%1.2f" % (self.GetXsecSystUnc() * y), 8, 0)
sigsta = t.fix("%1.2f" % self.GetSignal().GetStatUnc(), 8, 0)
t.line(signal + t.vsep() + ysig +
((t.pm() + sigsta) if doStat else '') +
((t.pm() + sigunc) if doSyst else ''))
t.sep()
t.line(
t.fix(" Data", 16, 'l', 0) + t.vsep() +
t.fix("%i" % self.GetData(), 8, 0))
t.bar()
t.write()
def PrintXsec(self, name='xsec'):
t = OutText(self.outpath, name, "new", textformat=self.textformat)
t.SetTexAlign("l c")
t.SetSeparatorLength(26 + 3 + 20 + 5)
t.SetDefaultFixOption(False)
t.line('%' + 'tt cross section for channel \'%s\' and level \'%s\'' %
(self.GetChan(), self.GetLevel()))
acc = self.GetAcc()
eff = self.GetEff()
t.bar()
t.line(
t.fix(' Acceptance', 16, 'r') + t.vsep() +
t.fix("%1.4f" % acc, 6) + t.pm() +
t.fix("%1.2f" % (acc * self.GetAccUnc()), 8))
t.line(
t.fix(' Efficiency', 16, 'r') + t.vsep() +
t.fix("%1.4f" % eff, 6) + t.pm() +
t.fix("%1.2f" % (eff * self.GetEffUnc()), 8))
t.sep()
t.line(
t.fix(' Branching ratio', 16, 'r') + t.vsep() +
t.fix("%1.4f" % self.GetBR(), 6))
t.line(
t.fix(' Gen events', 16, 'r') + t.vsep() +
t.fix("%d" % self.GetGenEvents(), 9))
t.line(
t.fix(' Fiducial events', 16, 'r') + t.vsep() +
t.fix("%d" % self.GetFiduEvents(), 9))
if self.doFiducial:
t.sep()
xsec = self.GetFiduXsec()
stat = self.GetXsecStatUnc()
syst = self.GetEffUnc()
lumi = self.GetXsecLumiUnc()
#t.line(t.fix(' Fiducial cross section', 26, 'r') + t.vsep() + t.fix("%1.2f"%xsec,6))
#t.line(t.fix(' +\- ', 26, 'r') + ' ' + t.fix('%1.2f (%1.2f'%(stat*xsec,stat*100) + ' %) (stat)',20, 'l'))
#t.line(t.fix(' +\- ', 26, 'r') + ' ' + t.fix('%1.2f (%1.2f'%(syst*xsec,syst*100) + ' %) (syst)',20, 'l'))
#t.line(t.fix(' +\- ', 26, 'r') + ' ' + t.fix('%1.2f (%1.2f'%(lumi*xsec,lumi*100) + ' %) (lumi)',20, 'l'))
t.sep()
xsec = self.GetXsec()
stat = self.GetXsecStatUnc()
syst = self.GetXsecSystUnc()
lumi = self.GetXsecLumiUnc()
t.line(
t.fix(' Inclusive cross section', 26, 'r') + t.vsep() +
t.fix("%1.2f" % xsec, 6))
t.line(
t.fix(' $\pm$ ', 26, 'r') + ' ' +
t.fix('%1.2f (%1.2f' %
(stat * xsec, stat * 100) + ' \%) (stat)', 20, 'l') +
t.vsep())
t.line(
t.fix(' $\pm$ ', 26, 'r') + ' ' +
t.fix('%1.2f (%1.2f' %
(syst * xsec, syst * 100) + ' \%) (syst)', 20, 'l') +
t.vsep())
t.line(
t.fix(' $\pm$ ', 26, 'r') + ' ' +
t.fix('%1.2f (%1.2f' %
(lumi * xsec, lumi * 100) + ' \%) (lumi)', 20, 'l') +
t.vsep())
t.bar()
t.write()
def AddToTxt(self, name='xsec', lab='e#mu'):
t = OutText(self.outpath, name, "new", textformat=self.textformat)
text = t.GetTextFromOutFile(form='txt')
xsec = self.GetXsec()
stat = self.GetXsecStatUnc() * xsec
syst = self.GetXsecSystUnc() * xsec
lum = self.GetXsecLumiUnc() * xsec
isthere = False
for l in text.splitlines():
if l == '' or l.replace(' ', '') == '': continue
if l.startswith(lab):
isthere = True
t.line('%s %1.2f %1.2f %1.2f %1.2f' %
(lab, xsec, stat, syst, lum))
else:
t.line(l)
if not isthere:
t.line('%s %1.2f %1.2f %1.2f %1.2f' % (lab, xsec, stat, syst, lum))
t.write()
def PrintSystTable(self, name='uncertainties'):
t = OutText(self.outpath, name, "new", textformat=self.textformat)
t.SetTexAlign("l c")
t.SetSeparatorLength(30)
t.SetDefaultFixOption(False)
t.line('%Uncertainties on tt inclusive cross section \n% ' +
'for channel \'%s\' and level \'%s\'' %
(self.GetChan(), self.GetLevel()))
exp = self.GetExpUnc()
mod = self.GetModUnc()
stat = self.GetXsecStatUnc()
lum = self.GetXsecLumiUnc()
syst = self.GetXsecSystUnc()
xsec = self.GetXsec()
t.bar()
t.line(t.fix(' Source', 18, 'l') + t.vsep() + fix("value (\%)", 6))
t.sep()
for b in [x.GetName() for x in self.bkg]:
t.line(
fix(' ' + b, 18, 'r') + t.vsep() +
fix('%1.2f' % (self.GetXsecBkgRelUnc(b) * 100), 6))
t.sep()
for e in exp.keys():
t.line(
fix(' ' + e, 18, 'l') + t.vsep() +
fix('%1.2f' % (exp[e] * 100), 6))
t.sep()
for e in mod.keys():
t.line(
fix(' ' + e, 18, 'l') + t.vsep() +
fix('%1.2f' % (mod[e] * 100), 6))
t.sep()
t.line(
fix(' Total systematic', 18, 'l') + t.vsep() +
fix('%1.2f' % (syst * 100), 6))
t.sep()
t.line(
fix(' Statistics', 18, 'l') + t.vsep() +
fix('%1.2f' % (stat * 100), 6))
t.sep()
t.line(
fix(' Luminosity', 18, 'l') + t.vsep() +
fix('%1.2f' % (lum * 100), 6))
t.bar()
t.write()
### Other
def ComputeXsec(self, data='', bkg='', y=''):
''' Computes the xsec from data, bkg and expected yield '''
if data == '': data = self.data
if bkg == '': bkg = self.GetTotBkg()
if y == '': y = self.GetSignalYield()
return (data - bkg) / y * self.GetThXsec()
def SetPathToTrees(self, ptt):
self.pathToTrees = ptt
def SetMotherName(self, mn):
self.motherfname = mn
def GetNGenEvents(self):
self.treesow = TChain('Runs', 'Runs')
files = GetFiles(self.pathToTrees, self.motherfname)
for f in files:
self.treesow.Add(f)
def ReadHistos(self,
path,
chan='ElMu',
level='2jets',
lumi=Lumi,
lumiunc=0.04,
bkg=[],
signal=[],
data='',
expUnc=[],
modUnc=[],
histoPrefix=''):
''' Set the xsec from histos '''
if isinstance(expUnc, str): expUnc = expUnc.replace(' ', '').split(',')
if isinstance(modUnc, str): modUnc = modUnc.replace(' ', '').split(',')
self.SetChan(chan)
self.SetLevel(level)
self.t = TopHistoReader(path)
self.t.SetHistoNamePrefix(histoPrefix)
self.t.SetLumi(lumi)
self.t.SetChan(chan)
self.t.SetLevel(level)
self.ss = SampleSums(self.pathToTrees, self.motherfname, 'Runs')
signalName = signal[0]
signalSample = signal[1]
# GetFiduEvents
hfiduname = 'FiduEvents' #_%s'%chan
fiduEvents = self.t.GetNamedHisto(
hfiduname, signalSample).GetBinContent(invlevel[level])
nGenEvents = self.ss.GetCount(
'Count') #self.GetNGenEvents(signalSample)
self.SetLumiUnc(lumiunc)
self.SetFiduEvents(fiduEvents)
self.SetGenEvents(nGenEvents)
for l in bkg:
if len(l) == 3:
name, pr, unc = l
expunc = expUnc
elif len(l) == 4:
name, pr, unc, expunc = l
self.AddBkg(name, self.t.GetYield(pr), unc,
self.t.GetUnc(pr, chan, level, expUnc),
self.t.GetYieldStatUnc(pr))
self.SetSignal(signalName, self.t.GetYield(signalSample),
self.t.GetYieldStatUnc(signalSample))
self.t.SetIsData(True)
self.SetData(self.t.GetYield(data))
self.t.SetIsData(False)
for e in expUnc:
self.AddExpUnc(e, self.t.GetUnc(signal[1], chan, level, e))
# Modeling uncertainties
if 'pdf' in modUnc or 'PDF' in modUnc or 'Scale' in modUnc or 'ME' in modUnc or 'scale' in modUnc:
pathToTrees = self.pathToTrees #'/pool/ciencias/userstorage/juanr/nanoAODv4/5TeV/5TeV_5sept/'
motherfname = self.motherfname #'TT_TuneCP5_PSweights_5p02TeV'
w = WeightReader(path,
'',
chan,
level,
sampleName='TT',
pathToTrees=pathToTrees,
motherfname=motherfname,
PDFname='PDFweights',
ScaleName='ScaleWeights',
lumi=Lumi,
histoprefix=histoPrefix)
#w.SetSampleName(signalName)
if 'pdf' in modUnc or 'PDF' in modUnc:
self.AddModUnc('PDF', w.GetPDFandAlphaSunc())
if 'scale' in modUnc or 'ME' in modUnc:
self.AddModUnc('Scale ME', w.GetMaxRelUncScale())
if 'ISR' in modUnc or 'isr' in modUnc:
self.AddModUnc('ISR',
self.t.GetUnc(signalSample, chan, level, 'ISR'))
if 'FSR' in modUnc or 'fsr' in modUnc:
self.AddModUnc('FSR',
self.t.GetUnc(signalSample, chan, level, 'FSR'))
def __init__(self,
outpath='./temp/',
lev='',
chan='',
genEvents=1,
fiduEvents=1,
textformat="txt"):
self.SetTextFormat(textformat)
self.SetThXsec(68.9)
self.SetLumi(Lumi)
self.SetLumiUnc(0.035) # Relative
self.SetChan(chan)
self.SetLevel(lev)
self.SetGenEvents(genEvents)
self.SetFiduEvents(fiduEvents)
self.SetBR((0.108 * 3) * (0.108 * 3)) # By default, tt dilepton
self.bkg = [] # List of 'Process'
self.data = 0 # This is just an integer
self.signal = '' # Process
self.accUnc = {} # 'Name' : value
self.effUnc = {} # 'Name' : value
self.SetOutPath(outpath)
self.doFiducial = True
self.SetMotherName("TT_TuneCP5_5p02TeV")
self.SetPathToTrees("")
histos = [
'mt2', 'met', 'mll', 'dnn', 'dileppt', 'deltaphi', 'deltaeta', 'ht',
'lep0pt', 'lep1pt', 'lep0eta', 'lep1eta', 'njets', 'nbtags', 'jet0pt',
'jet1pt', 'jet0eta', 'jet1eta'
]
histos += ['dnn_5bins', 'dnn_10bins', 'dnn_30bins', 'dnn_40bins']
out = l.Run()
if sendJobs: exit()
t = TopHistoReader(outpath + 'tempfiles/')
print "Creating outputs in %s ..." % outpath
for var in histos:
PDFhistosNom = t.GetNamedHisto(var + '_PDF0', 'tt')
PDFhistos = [
t.GetNamedHisto(var + '_PDF%i' % i, 'tt')
for i in range(1, nPDFweights - 2 if year != 2016 else nPDFweights)
]
AlphaShistos = [
t.GetNamedHisto(var + '_PDF%i' % (nPDFweights - 2), 'tt'),
t.GetNamedHisto(var + '_PDF%i' % (nPDFweights - 1), 'tt')
] if year != 2016 else []
pdfNom, pdfUp, pdfDown = GetPDFuncHisto(PDFhistosNom,
PDFhistos,
AlphaShistos,
prName='tt',
year=year)
if not os.path.isdir(outpath + '/PDF/'):
def DrawPostFit(ms=235, ml=60, htype='fit_s', var='dnn', ch='', year=''):
getdir = lambda dirtype, ch: 'shapes_%s/%s/' % (dirtype, ch)
getfname = lambda ms, ml: 'postfit_%s_%s_%s' % (var, str(ms), str(ml))
# Get channels
if not isinstance(ch, list):
if ch == '': ch = ['ee', 'mumu', 'emu']
elif ',' in ch: ch = ch.replace(' ', '').split(',')
else: ch = [ch]
if not isinstance(year, list):
if year == '': year = [2016, 2017, 2018]
elif isinstance(year, str) and ',' in year:
year = year.replace(' ', '').split(',')
else:
year = [year]
pch = []
for y in year:
for c in ch:
pch.append(chdic[y][c])
if len(year) == 3: yearname = 'comb'
else: yearname = str(year[0])
if len(ch) == 3: chname = 'all'
else: chname = ch[0]
# test or not depending on var
ttname = 'tt' if not 'dnn' in var else 'tt_test'
pr = bkg + [ttname]
sig = ('stop'
if not 'dnn' in var else 'stop_test') if htype != 'fit_b' else []
hm = HistoManager(pr, '', path=pathToPostFit, signalList=sig)
pathInTree = [getdir(htype, x) for x in pch]
hm.SetPathInTree(pathInTree)
hm.ReadHistosFromFile(getfname(ms, ml), dataname='data', rebin=1)
hm.ReArrangeDic({
'Others': ['ttW', 'ttZ', 'Nonprompt', 'VV'],
't#bar{t}+tW': ['tW', ttname],
'Drell-Yan': ['DY']
})
hm.GetDataHisto()
#hm.indic['data_obs']['data_obs'] = hm.GetSumBkg()
outdir = GetOutpath(region, year, ms, ml, ch)
fprocess = ['Others', 'Drell-Yan', 't#bar{t}+tW']
s = Stack(outpath=outdir + '/postfit/')
colors['Others'] = kTeal + 2
colors['t#bar{t}+tW'] = colors['tt']
colors['Drell-Yan'] = colors['DY']
s.SetColors(colors)
s.SetProcesses(fprocess)
s.SetLumi(
GetLumi(year[0]) if len(year) == 1 else (GetLumi(2016) +
GetLumi(2017) +
GetLumi(2018)))
outname = htype + '_' + var + '%s_%s_%i_%i' % (yearname, chname, ms, ml)
s.SetOutName(outname)
s.SetHistosFromMH(hm)
#s.Set
t = TopHistoReader(pathToPostFit)
t.ReComputeStatUnc = False
t.SetPathInTree(pathInTree)
hbkg = t.GetNamedHisto('total_background', getfname(ms, ml))
hbkg.SetLineStyle(0)
hbkg.SetLineWidth(0)
hbkg.SetMarkerSize(0)
s.SetTotMC(hbkg)
s.SetMCunc(hbkg)
s.SetMCstatUnc(None)
s.SetMCnormUnc(None)
s.SetRatioStatUnc(None)
s.SetRatioNormUnc(None)
s.SetRatioUnc(GetRatioHistoUncFromHisto(hbkg))
s.SetRatioUncStyle()
s.SetUncStyle()
if sig != []:
s.AddSignalHisto(hm.indic[sig][sig],
color=kViolet + 2,
mode='ontop',
ratioBkg=True,
name='stop')
s.SetTextChan('SR: BS + p_{T}^{miss} #geq 50, m_{T2} #geq 80')
s.SetRatioMin(0.5)
s.SetRatioMax(1.5)
s.SetPlotMaxScale(1.8)
xtit = 'DNN score (%i, %i)' % (ms, ml)
chlab = ''
if chname == 'ee': chlab = 'ee'
elif chname == 'mumu': chlab = '#mu#mu'
elif chname == 'emu': chlab = 'e#mu'
flab = 'Prefit'
if htype == 'fit_b': flab = 'Fit background only'
elif htype == 'fit_s': flab = 'Fit S+B'
mlab = '#splitline{m_{#tilde{t}_{1}} = %1.0f GeV}{m_{#tilde{#chi}_{1}^{0}} = %1.0f GeV}' % (
ms, ml)
s.AddTex(flab, x=0.15, y=0.77, s=0.05)
s.AddTex(mlab, x=0.15, y=0.62, s=0.04)
s.AddTex(chlab, x=0.15, y=0.84, s=0.04)
s.DrawStack(xtit, 'Events')
s.SetLogY()
s.SetZoom(False)
if var == 'dnn' and region == 'SR':
s.SetZoom(True)
s.SetOutName('log_' + outname)
s.SetPlotMinimum(1)
s.SetPlotMaxScale(1200)
s.SetYratioTitle('Ratio')
from plotter.TopHistoReader import TopHistoReader, HistoManager
from plotter.Plotter import Stack, HistoComp
from ROOT.TMath import Sqrt as sqrt
from ROOT import kRed, kOrange, kBlue, kTeal, kGreen, kGray, kAzure, kPink, kCyan, kBlack, kSpring, kViolet, kYellow
from ROOT import TCanvas, gROOT
gROOT.SetBatch(1)
tr1 = TopHistoReader(path=path[2016])
tr2 = TopHistoReader(
path=path[2018]
) #'/pool/ciencias/userstorage/juanr/top/2016/nov15/') # TOP-17-001
s = HistoComp(outpath='./temp/', doNorm=True, doRatio=True)
s.autoRatio = True
s.SetTextLumi('Normalized distributions', texlumiX=0.12)
hname = 'H_NJets_ElMu_dilepton'
s.AddHisto(tr1.GetNamedHisto(hname, 'TT'),
'hist',
'hist',
'2016',
color=kAzure + 2)
s.AddHisto(tr2.GetNamedHisto(hname, 'TTTo2L2Nu'),
'hist',
'hist',
'2018',
color=kRed + 1)
s.SetXtitle('Jet multiplicity')
s.SetOutName('temp')
s.Draw()