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()
def PrintPSunc(self, name='PSuncertainties'):
''' Prints a table with the ISR and FSR info '''
t = OutText(self.outpath, name)
#[0] is ISR=0.5 FSR=1; [1] is ISR=1 FSR=0.5; [2] is ISR=2 FSR=1; [3] is ISR=1 FSR=2
s = lambda i, isr, fsr, lab: '[%i] ISR=%1.1f, FSR=%1.1f (%s): %1.4f (%1.3f %s)' % (
i, fsr, isr, lab, self.GetPSyield(i), self.GetPSrelUnc(
i) * 100, '%')
l1 = s(1, 0.5, 1.0, 'ISR down')
t.SetSeparatorLength(len(l1))
t.line(' PS uncertainties')
t.line(' Yield: %1.2f' % self.GetYield())
t.bar()
t.line(l1)
t.line(s(2, 1.0, 0.5, 'FSR down'))
t.line(s(3, 2.0, 1.0, 'ISR up '))
t.line(s(4, 1.0, 2.0, 'FSR up '))
t.bar()
t.write()
def PrintPDFyields(self, name='PDFvariations'):
''' Prints a table with the info of PDF systematics '''
t = OutText(self.outpath, name)
s = lambda i: ' ' + t.fix('[%d]' % i, 4, 'l', False
) + ' %1.2f (%1.2f %s)' % (self.GetPDFyield(
i), self.GetRelUncPDF(i) * 100, '%')
c0 = s(1) + ' (nominal) '
t.SetSeparatorLength(len(c0))
t.line('### PDF and alpha_s uncertianties')
t.line()
if self.nPDFweights == 33:
t.line(
' Using PDF4LHC15_nlo_nf4_30_pdfas, 1+30+2 weights, see Table 6 in '
)
t.line(' > https://arxiv.org/pdf/1510.03865.pdf')
elif self.nPDFweights == 100:
t.line('### NNPDF variations: 100 (2 alpha_s variations missing)')
#cout << " >>>> NNPDF systematic uncertainty" << endl;
#cout << " Evaluated by taking the RMS under the 100 weights" << endl;
#cout << " Alpha_s variations are added in quadrature after rescaling by 0.75" << endl;
#cout << " The formula is: sqrt(RMS^2 + ((alphas var 1 - alphas var 2)*0.75/2)^2 )" << endl;
t.bar()
t.line(c0)
for i in range(2, self.nPDFweights + 1):
t.line(s(i))
t.sep()
pdfunc = self.GetPDFunc()
alphas = self.GetAlphaSunc()
totunc = self.GetPDFandAlphaSunc()
if self.nPDFweights == 33:
t.line(' See reference: ')
t.line(' > https://arxiv.org/pdf/1510.03865.pdf')
t.line(' Eq [20] for PDF unc: %1.2f (%1.2f %s)' %
(pdfunc * self.GetPDFnom(), pdfunc * 100, '%'))
t.line(' Eq [27] for alpha_S: %1.2f (%1.2f %s)' %
(alphas * self.GetPDFnom(), alphas * 100, '%'))
t.sep()
t.line(' Total PDF + alpha_S uncertainty: ')
t.line(' ## %1.2f (%1.2f %s)' %
(totunc * self.GetPDFnom(), totunc * 100, '%'))
t.bar()
t.write()
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 PrintMEscale(self, name='ScaleMEvariations'):
''' Prints a table with the info of scale systematics '''
t = OutText(self.outpath, name)
s = lambda i, muF, muR: ' [%d] muF = %1.2f, muR = %1.2f | %1.2f (%1.2f %s)' % (
i, muF, muR, self.GetScaleYield(i), self.GetRelUncScale(
i) * 100, '%')
nom = s(1, 0.5, 0.5)
t.SetSeparatorLength(len(nom))
t.line(" Scale ME uncertainties on tt acceptance")
t.bar()
t.line(nom)
t.line(s(2, 0.5, 1.0))
t.line(s(3, 0.5, 2.0) + ' (unphysical)')
t.line(s(4, 1.0, 0.5))
t.line(s(5, 1.0, 1.0) + ' (nominal)')
t.line(s(6, 1.0, 2.0))
t.line(s(7, 2.0, 0.5) + ' (unphysical)')
t.line(s(8, 2.0, 1.0))
t.line(s(9, 2.0, 2.0))
t.sep()
t.line(' Maximum variation: %1.2f %s ' %
(self.GetMaxRelUncScale() * 100, '%'))
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 PrintLine(sample, chan):
print "Nominal - Variation %s - uncertainty"%sample
nom, uncnom, var, uncvar, syst, systunc = GetGAandUnc(sample, chan)
print "%s - %s - %s"%(GetValAndUncString(nom, uncnom), GetValAndUncString(var, uncvar), GetValAndUncString(syst, systunc))
PrintLine('hdampUp', 'ElMu')
'''
if printRecoAndGen:
t = OutText(outpath+'/genSyst/', 'genSyst_'+l, "new", textformat='tex')
t.SetTexAlign("l c c c c c")
nsem = 12
t.SetSeparatorLength(nsem)
#t.line('Underlying event and hdamp uncertainties at reco and gen level (%s)'%l)
t.bar()
firstline = ''
for lab in snames:
firstline += t.vsep() + t.fix(lab,20)
t.line(firstline)
t.sep()
for ch in ['ElEl', 'MuMu', 'ElMu']:
for mode in ['Reco', 'Gen']:
name = ('ee' if ch=='ElEl' else ('$\mu\mu$' if ch =='MuMu' else 'e$\mu$')) +' '+ mode
name = t.fix(name, 10)
for lab in snames:
val, unc = GA(lab, ch) if mode == 'Gen' else RS(lab, ch)
name += t.vsep() + (t.fix("%1.2f %s"%(unc, '\%'), 20) if lab!='tt' else t.fix("%g"%(val), 20))
#name += t.vsep() + t.fix("%1.1f (%1.2f %s)"%(val, unc, '%'), 20)
t.line(name)
t.bar()
def PrintYields(self,
var='counts',
tform='%1.2f',
save=False,
multicategories={},
bkgprocess=None,
signalprocess=None,
doData=True,
doTotBkg=True):
if bkgprocess != None: self.SetBkgProcesses(bkgprocess)
if signalprocess != None: self.SetSignalProcesses(signalprocess)
if multicategories != {}:
k0 = multicategories.keys()[0]
if not isinstance(multicategories[k0],
dict): # Not a multicategory, but single one
self.SetMultiCategores({'Yields': multicategories})
else:
self.SetMultiCategores(multicategories)
else:
self.SetMultiCategores(multicategories)
if self.multicategories == {}:
print('[plotter.PrintYields] ERROR: no categories found!')
exit()
# Output name
name = save if (save and save != '') else 'yields'
# Create an OutText object: the output will be a tex file
t = OutText(self.outpath, name, 'new', 'tex')
t.bar()
ncolumns = len(self.multicategories)
t.SetTexAlign('l' + ' c' * ncolumns)
dic = {}
for k in self.multicategories.keys():
self.SetCategories(self.multicategories[k])
dic[k] = self.GetYields(var)
# header
header = ''
for label in dic:
header += t.vsep() + ' ' + label
t.line(header)
t.sep()
# backgrounds
for bkg in self.bkglist:
line = bkg
for label in dic:
line += t.vsep() + ' ' + (tform % (dic[label][bkg]))
t.line(line)
if len(self.bkglist) > 0: t.sep()
if doTotBkg and len(self.bkglist) > 0:
line = 'Total background'
for label in dic:
line += t.vsep() + ' ' + (
tform % (sum([dic[label][bkg] for bkg in self.bkglist])))
t.line(line)
t.sep()
for sig in self.signallist:
line = sig
for label in dic:
line += t.vsep() + ' ' + (tform % (dic[label][sig]))
t.line(line)
if len(self.signallist) > 0: t.sep()
if doData:
line = self.dataName
for label in dic:
line += t.vsep() + ' ' + tform % (dic[label][self.dataName])
t.line(line)
t.sep()
t.write()