# Condition to ensure acceptance function is always +ve definite.
# The first condition protects against the undefined nature of the
# function for times less than 0. Whereas the second condition
# ensures the 0.2 ps selection cut present in the sample is
# incorporated into the model.
# acceptance fn parameters: common to both DsK and Dsπ
turnon = RooRealVar('turnon', 'turnon', 1.5, 0.5, 5.0)
exponent = RooRealVar('exponent', 'exponent', 2., 1., 4.)
offset = RooRealVar('offset', 'offset', 0.0, -0.5, 0.5)
beta = RooRealVar('beta', 'beta', 0.04, 0.0, 0.10)
## Dsπ acceptance and pdf
dspi_acceptance = PowLawAcceptance('dspi_acceptance',
'DsPi Power law acceptance', turnon, time,
offset, exponent, beta)
DsPi_Model = RooEffProd('DsPi_Model', 'DsPi acceptance model B_{s}', Bdecay,
dspi_acceptance)
varlist += [turnon, exponent, offset, beta]
pdflist += [dspi_acceptance, DsPi_Model]
# fit to Dsπ only
print '=' * 5, ' 2-step fit: Dsπ ', '=' * 5
dspi_fitresult = DsPi_Model.fitTo(dsetlist[0], RooFit.Optimize(0),
RooFit.Strategy(2), RooFit.Save(True),
RooFit.NumCPU(1), RooFit.SumW2Error(True),
RooFit.Offset(True), RooFit.Verbose(True))
dspi_fitresult.Print()
# Condition to ensure acceptance function is always +ve definite.
# The first condition protects against the undefined nature of the
# function for times less than 0. Whereas the second condition
# ensures the 0.2 ps selection cut present in the sample is
# incorporated into the model.
# acceptance fn parameters: common to both DsK and Dsπ
turnon = RooRealVar('turnon', 'turnon', 1.5, 0.5, 5.0)
exponent = RooRealVar('exponent', 'exponent', 2., 1., 4.)
offset = RooRealVar('offset', 'offset', 0.0, -0.5, 0.5)
beta = RooRealVar('beta', 'beta', 0.04, 0.0, 0.10)
## Dsπ acceptance and pdf
dspi_acceptance = PowLawAcceptance('dspi_acceptance',
'DsPi Power law acceptance',
turnon, time, offset, exponent, beta)
DsPi_Model = RooEffProd('DsPi_Model', 'DsPi acceptance model B_{s}',
Bdecay, dspi_acceptance)
varlist += [turnon, exponent, offset, beta]
pdflist += [dspi_acceptance, DsPi_Model]
# fit to Dsπ only
print '=' * 5, ' 2-step fit: Dsπ ', '=' * 5
dspi_fitresult = DsPi_Model.fitTo(dsetlist[0], RooFit.Optimize(0),
RooFit.Strategy(2),
RooFit.Save(True), RooFit.NumCPU(1),
RooFit.SumW2Error(True),
RooFit.Offset(True),
RooFit.Verbose(True))
RooFit.RecycleConflictNodes())
# retrieve acceptance functions
acceptance1 = workspace.function('acceptance_%s' % mode1) # DsK
acceptance2 = workspace.function('acceptance_%s' % mode2) # Dsπ
# Acceptance ratio FIXME: hardcoded ROOT file
rfile = TFile('data/acceptance-ratio-hists.root', 'read')
hcorr = rfile.Get('haccratio_cpowerlaw')
ardhist = RooDataHist('ardhist', 'DsK/DsPi acceptance ratio datahist',
RooArgList(time), RooFit.Import(hcorr, False))
accratio = RooHistFunc('accratio', 'DsK/DsPi acceptance ratio',
RooArgSet(time), ardhist)
cacceptance = PowLawAcceptance(acceptance2, 'cacceptance', accratio)
# cacceptance = PowLawAcceptance('cacceptance', 'Corrected Power law acceptance',
# turnon, time, offset, exponent, beta, accratio)
ratio = RooFormulaVar('ratio', '@0/@1', RooArgList(acceptance1, cacceptance))
tframe = time.frame(RooFit.Range('fullrange'), RooFit.Name('ptime'),
RooFit.Title('Acceptance ratio (0.2 - 10 ps)'))
acceptance1.plotOn(tframe, RooFit.LineColor(kBlue))
# acceptance2.plotOn(tframe, RooFit.LineColor(kRed))
# accratio.plotOn(tframe, RooFit.LineColor(kBlack))
cacceptance.plotOn(tframe, RooFit.LineColor(kRed))
ratio.plotOn(tframe, RooFit.LineColor(kGreen))
tframe.Draw()
