for it, pars in enumerate(splitPars) :
print 13 * ' ' + '%2d: pars: [ %s ]' % ( it, ', '.join( par.GetName() for par in pars[0] ) )
print 13 * ' ' + ' cats: [ %s ]' % ', '.join( cat.GetName() for cat in pars[1] )
from P2VV.RooFitWrappers import SimultaneousPdf
sWeightMassPdf = SimultaneousPdf( massPdf.GetName() + '_simul'
, MasterPdf = massPdf
, SplitCategories = [ pars[1] for pars in splitPars ]
, SplitParameters = [ pars[0] for pars in splitPars ]
)
massPdfObs = sWeightMassPdf.getObservables(preDataSet)
massPdfPars = sWeightMassPdf.getParameters(preDataSet)
if model == 'ipatia2' :
# set values of constant Ipatia 2 parameters
from P2VV.Utilities.General import getSplitPar
for splitCat in sWeightMassPdf.indexCat() :
sWeightMassPdf.indexCat().setIndex( splitCat.getVal() )
KKState = observables['KKMassCat'].getLabel()
for it, parName in enumerate(constSplitPars) :
par = getSplitPar( parName, KKState, massPdfPars )
par.setVal( constSplitVals[KKState][it] )
if parFileIn or parFileOut :
# create PDF configuration object
from P2VV.Parameterizations.FullPDFs import PdfConfiguration as PdfConfig
pdfConfig = PdfConfig()
print 120 * '='
if parFileIn :
# read parameters from file
pdfConfig.readParametersFromFile( filePath = parFileIn )
# 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()))
splitPars[-1].add(par1)
splitParsDict.pop(par1)
# 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() :
###########################################################################################################################################
## split data into signal and background ##
###########################################
# create integration sets
from ROOT import RooArgSet
intSet = RooArgSet()
normSet = RooArgSet( massPdfObs.find('mass') )
# get signal and background mass PDFs
comps = [ 'sig', 'cbkg' ]
yields = dict( sig = { }, cbkg = { } )
pdfs = dict( sig = { }, cbkg = { } )
from P2VV.Utilities.General import getSplitPar
splitCat = simMassPdf.indexCat()
for state in splitCat :
stateName = state.GetName()
yields['sig'][stateName] = getSplitPar( 'N_sigMass', stateName, massPdfPars ).getVal()
yields['cbkg'][stateName] = getSplitPar( 'N_cbkgMass', stateName, massPdfPars ).getVal()
if genMass :
pdfs['sig'][stateName] = simMassPdf.getPdf(stateName).pdfList().at(0)
pdfs['cbkg'][stateName] = simMassPdf.getPdf(stateName).pdfList().at(1)
else :
pdfs['sig'][stateName] = simMassPdf.getPdf(stateName).pdfList().at(0).createIntegral( intSet, normSet )
pdfs['cbkg'][stateName] = simMassPdf.getPdf(stateName).pdfList().at(1).createIntegral( intSet, normSet )
for comp in comps :
yields[comp]['total'] = sum( y for y in yields[comp].itervalues() )
print 'P2VV - INFO: signal and background yields:'
for comp in comps :