def __call__(self, data):
pdf_pars = self.__pdf.getParameters(data.get())
if not self.__parameters:
self.__parameters = pdf_pars
self.__parameters = [p for p in pdf_pars] + [self.__status]
else:
for p in self.__parameters:
pdf_par = pdf_pars.find(p.GetName())
if not pdf_par:
continue
pdf_par.setVal(p.getVal())
pdf_par.setError(p.getError())
success = False
status = 4
for i in range(3):
self.__result = self.__pdf.fitTo(data, **self.__fit_opts)
status = self.__result.status()
if status == 0:
success = True
break
if status < 4:
self.__status.setIndex(self.__result.status())
else:
self.__status.setIndex(4)
if success:
from P2VV.Utilities.SWeights import SData
self.__sData = SData(Pdf=self.__pdf, Data=data, Name="MassSPlot")
data = self.__sData.data(self.__comp)
if self.__correct_weights:
from P2VV.Utilities.DataHandling import correctWeights
data = correctWeights(data, splitCatNames=None, ImportIntoWS=False)
return data
else:
return None
minosPars += [ 'Gamma', 'dGamma', 'dM', 'AparPhase', 'AperpPhase' ]
if args.model in [ 'phi', 'lamb_phi' ] :
minosPars += [ 'phiCP', 'A0Mag2', 'AperpMag2' ]
if args.model == 'lamb_phi' :
minosPars += [ 'lambdaCP' ]
elif args.model == 'polarDep' :
minosPars += [ 'phiCPAv', 'phiCPRel_Apar', 'phiCPRel_AperpApar', 'phiCPRel_AS'
, 'CCPAv', 'CCPRel_Apar', 'CCPRel_Aperp', 'CCPAv_AS', 'avA02', 'avAperp2' ]
minosPars = [ pdfPars.find(par) for par in minosPars ]
if minosPars :
print 'Bs2JpsiphiMCFit: running Minos for parameters', ', '.join( '"%s"' % par.GetName() for par in minosPars )
# fit data
if dataSet.isWeighted() :
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( dataSet, [ ] )
else :
fitData = dataSet
fitResult = pdf.fitTo( fitData, SumW2Error = False, Save = True, NumCPU = args.numCPU, Optimize = 2, Timer = True, Minimizer = 'Minuit2'
, Strategy = 1, Offset = True, Hesse = runHesse, Minos = minosPars )
if pdfConfig['lambdaCPParam'] == 'observables_CPVDecay' :
from P2VV.Imports import parNames, parValuesCPVDecay as parValues
elif args.model == 'phi' :
from P2VV.Imports import parNames, parValuesFixLamb as parValues
else :
from P2VV.Imports import parNames, parValues
print 120 * '-'
print 'parameter values:'
fitResult.PrintSpecial( text = True, LaTeX = True, normal = True, ParNames = parNames, ParValues = parValues )
print 120 * '-'
minosPars += [ 'Gamma', '{0}dGamma{0}'.format(blindAdd), 'dM', 'AparPhase', 'AperpPhase' ]
if args.model in [ 'phi', 'lamb_phi' ] :
minosPars += [ '{0}phiCP{0}'.format(blindAdd), 'A0Mag2', 'AperpMag2' ]
if args.model == 'lamb_phi' :
minosPars += [ 'lambdaCP' ]
elif args.model == 'polarDep' :
minosPars += [ '{0}phiCPAv{0}'.format(blindAdd), '{0}phiCPRel_Apar{0}'.format(blindAdd)
, '{0}phiCPRel_AperpApar{0}'.format(blindAdd), '{0}phiCPRel_AS{0}'.format(blindAdd)
, 'CCPAv', 'CCPRel_Apar', 'CCPRel_Aperp', 'CCPAv_AS', 'avA02', 'avAperp2' ]
minosPars = [ pdfPars.find(par) for par in minosPars ]
if minosPars :
print 'Bs2JpsiKK3fbFit: running Minos for parameters', ', '.join( '"%s"' % par.GetName() for par in minosPars )
# fit data
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( dataSet, [ 'runPeriod', 'KKMassCat' ] )
fitResult = pdf.fitTo( fitData, SumW2Error = False, Save = True, NumCPU = args.numCPU, Optimize = 2, Timer = True, Minimizer = 'Minuit2'
, Strategy = 1, Offset = True, Hesse = runHesse, Minos = minosPars )
if pdfConfig['lambdaCPParam'] == 'observables_CPVDecay' :
from P2VV.Imports import parNames, parValuesCPVDecay as parValues
elif args.model == 'phi' :
from P2VV.Imports import parNames, parValuesFixLamb as parValues
else :
from P2VV.Imports import parNames, parValues
print 120 * '-'
print 'parameter values:'
fitResult.PrintSpecial( text = True, LaTeX = True, normal = True, ParNames = parNames, ParValues = parValues )
print 120 * '-'
print 'correlation matrix:'
fitResult.correlationMatrix().Print()
pdf = pdfBuild.pdf()
if not 'Optimize' in fitOpts or fitOpts['Optimize'] < 2 :
# unset cache-and-track
for par in pdfBuild['taggingParams'].parameters() : par.setAttribute( 'CacheAndTrack', False )
if parFileIn :
# read parameters from file
pdfConfig.readParametersFromFile( filePath = parFileIn )
pdfConfig.setParametersInPdf(pdf)
# data set with weights corrected for background dilution: for phi_s fit only!
if corrSFitErr == 'sumWeight'\
or ( type(corrSFitErr) != str and hasattr( corrSFitErr, '__iter__' ) and hasattr( corrSFitErr, '__getitem__' ) ) :
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( sigData, 'KKMassCat' if pdfConfig['paramKKMass'] == 'simultaneous' else ''
, CorrectionFactors = None if corrSFitErr == 'sumWeight' else corrSFitErr )
else :
fitData = sigData
# get observables and parameters in PDF
pdfObs = pdf.getObservables(fitData)
pdfPars = pdf.getParameters(fitData)
###########################################################################################################################################
## fit data ##
##############
# float/fix values of some parameters
for CEvenOdds in pdfBuild['taggingParams']['CEvenOdds'] :
from P2VV.Parameterizations.FullPDFs import Bs2Jpsiphi_PdfBuilder as PdfBuilder
pdfBuild = PdfBuilder( **pdfConfig )
pdf = pdfBuild.pdf()
if not 'Optimize' in fitOpts or fitOpts['Optimize'] < 2 :
# unset cache-and-track
for par in pdfBuild['taggingParams'].parameters() : par.setAttribute( 'CacheAndTrack', False )
if parFileIn :
# read parameters from file
pdfConfig.readParametersFromFile( filePath = parFileIn )
pdfConfig.setParametersInPdf(pdf)
# data set with weights corrected for background dilution: for phi_s fit only!
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( dataSet, 'KKMassCat' if pdfConfig['paramKKMass'] == 'simultaneous' else '' )
# get observables and parameters in PDF
pdfObs = pdf.getObservables(fitData)
pdfPars = pdf.getParameters(fitData)
###########################################################################################################################################
## fit data ##
##############
# fix values of some parameters
for CEvenOdds in pdfBuild['taggingParams']['CEvenOdds'] :
if not pdfConfig['SSTagging'] :
CEvenOdds.setConstant('avgCEven.*')
CEvenOdds.setConstant( 'avgCOdd.*', True )
from P2VV.Utilities.DataHandling import addTransversityAngles
addTransversityAngles( fitData, 'trcospsi', 'trcostheta', 'trphi'
, angles[0].GetName(), angles[1].GetName(), angles[2].GetName() )
# write data to file
from P2VV.Utilities.DataHandling import writeData
writeData( dataSetFile, dataSetName, fitData )
elif pdfConfig['sFit'] :
defData = pdfBuild['sigSWeightData']
sigData = pdfBuild['sigSWeightData']
bkgData = pdfBuild['bkgSWeightData']
if corrSFitErr == 'sumWeight'\
or ( type(corrSFitErr) != str and hasattr( corrSFitErr, '__iter__' ) and hasattr( corrSFitErr, '__getitem__' ) ) :
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( pdfBuild['sigSWeightData'], 'KKMassCat' if pdfConfig['parameterizeKKMass'] == 'simultaneous' else ''
, CorrectionFactors = None if corrSFitErr == 'sumWeight' else corrSFitErr )
else :
fitData = pdfBuild['sigSWeightData']
else :
defData = pdfBuild['data']
fitData = pdfBuild['data']
sigData = pdfBuild['sigSWeightData']
bkgData = pdfBuild['bkgSWeightData']
# get observables and parameters in PDF
pdfObs = pdf.getObservables(fitData)
pdfPars = pdf.getParameters(fitData)
# print parameters
bkgYield.setVal( bkgYield.getVal() * nEvBin / nEv )
bkgYield.setError( sqrt( bkgYield.getVal() ) )
bkgYield.setMin(0.)
bkgYield.setMax(nEvBin)
# determine mass parameters in each sub-sample with a fit
sim_mass_result = sWeight_mass_pdf.fitTo(data, **fitOpts)
sweight_pdf = sWeight_mass_pdf
else:
sweight_pdf = mass_pdf
from P2VV.Utilities.SWeights import SData
from P2VV.Utilities.DataHandling import correctWeights
sdata = SData( Pdf = sweight_pdf, Data = data, Name = 'mass_sdata')
sig_sdata = correctWeights(sdata.data('signal'), splitCatNames = [excl_biased.GetName()],
ImportIntoWS = False)
bkg_sdata = correctWeights(sdata.data('background'), splitCatNames = [excl_biased.GetName()],
ImportIntoWS = False)
from array import array
weights = array('d')
from ROOT import TFile
f = TFile.Open(input_file, "read")
tree = f.Get("DecayTree")
from ROOT import gDirectory
tree.Draw(">>elist", cut, "entrylist")
output = "temp.root"
output_file = TFile(output, "recreate")
from P2VV.Parameterizations.FullPDFs import Bs2Jpsiphi_PdfBuilder as PdfBuilder
pdfBuild = PdfBuilder( **pdfConfig )
pdf = pdfBuild.pdf()
if not 'Optimize' in fitOpts or fitOpts['Optimize'] < 2 :
# unset cache-and-track
for par in pdfBuild['taggingParams'].parameters() : par.setAttribute( 'CacheAndTrack', False )
if parFileIn :
# read parameters from file
pdfConfig.readParametersFromFile( filePath = parFileIn )
pdfConfig.setParametersInPdf(pdf)
# data set with weights corrected for background dilution: for phi_s fit only!
from P2VV.Utilities.DataHandling import correctWeights
fitData = correctWeights( dataSet, corrSFitErrCats )
# get observables and parameters in PDF
pdfObs = pdf.getObservables(fitData)
pdfPars = pdf.getParameters(fitData)
# get test parameters
testPars = [ pdfPars.find(name) for name in testParNames ]
###########################################################################################################################################
## get NLL values ##
####################
# fix values of some parameters
for CEvenOdds in pdfBuild['taggingParams']['CEvenOdds'] :
