# build simultaneous mass PDF
print 'P2VV - INFO: createB2CCFitNTuple: building simultaneous PDF "%s":' % ( massPdf.GetName() + '_simul' )
print 13 * ' ' + 'splitting categories: [ %s ]' % ' ], [ '.join(', '.join(cat.GetName() for cat in cats) for cats in splitCats)
print 13 * ' ' + 'split parameters: [ %s ]' % ' ], [ '.join(', '.join(par.GetName() for par in pars) for pars in splitPars)
from P2VV.RooFitWrappers import SimultaneousPdf
sWeightMassPdf = SimultaneousPdf( massPdf.GetName() + '_simul'
, MasterPdf = massPdf
, SplitCategories = splitCats
, SplitParameters = splitPars
)
# set yields for categories
splitCat = sWeightMassPdf.indexCat()
splitCatIter = splitCat.typeIterator()
splitCatState = splitCatIter.Next()
massPdfPars = sWeightMassPdf.getVariables()
from P2VV.Utilities.General import getSplitPar
from math import sqrt
while splitCatState :
KKMassState = -1
if splitCat.isFundamental() :
selStr = '!(%s-%d)' % ( splitCat.GetName(), splitCatState.getVal() )
if splitCat.GetName() == observables['KKMassCat'].GetName() : KKMassState = splitCatState.getVal()
else :
splitCat.setLabel( splitCatState.GetName() )
selStr = ' && '.join( '!(%s-%d)' % ( cat.GetName(), cat.getIndex() ) for cat in splitCat.inputCatList() )
if observables['KKMassCat'] in splitCats[0] :
for cat in splitCat.inputCatList() :
if cat.GetName() == observables['KKMassCat'].GetName() : KKMassState = cat.getIndex()
nEv = dataSets['pre'][0].sumEntries()
# categories for splitting the PDF
if not options.prescaled:
split_cats = [[excl_biased]]
# get mass parameters that are split
split_params = [[par for par in mass_pdf.Parameters() if par.getAttribute("Yield")]]
# build simultaneous mass PDF
from P2VV.RooFitWrappers import SimultaneousPdf
sWeight_mass_pdf = SimultaneousPdf(
mass_pdf.GetName() + "_simul", MasterPdf=mass_pdf, SplitCategories=split_cats, SplitParameters=split_params
)
# set yields for categories
split_cat = sWeight_mass_pdf.indexCat()
split_vars = sWeight_mass_pdf.getVariables()
from P2VV.Utilities.General import getSplitPar
from math import sqrt
for state in split_cat:
sigYield = getSplitPar("N_signal", state.GetName(), split_vars)
bkgYield = getSplitPar("N_background", state.GetName(), split_vars)
selStr = "{0} == {0}::{1}".format(split_cat.GetName(), state.GetName())
nEv = data.sumEntries()
nEvBin = data.sumEntries(selStr)
sigYield.setVal(sigYield.getVal() * nEvBin / nEv)
sigYield.setError(sqrt(sigYield.getVal()))
sigYield.setMin(0.0)