def normalizeMoments( momentsFileOrig, momentsFileNorm, normMoment = 'Re_ang_A0_A0', printMoms = True ):
# moment containers
funcNames = [ ]
moments = { }
correlations = { }
# read moments
print 'input moments:'
from P2VV.Utilities.DataMoments import readMoments, printMoments
readMoments( momentsFileOrig, BasisFuncNames = funcNames, Moments = moments, Correlations = correlations, ProcessAll = True )
if printMoms: printMoments( BasisFuncNames = funcNames, Moments = moments, Correlations = correlations )
# calculate moments with new normalization
from math import sqrt
valNorm = moments[normMoment][0]
errNorm = moments[normMoment][1]
momsNew = { }
corrsNew = { }
# moments value and error
for name in funcNames :
valNew = moments[name][0] / valNorm
err = moments[name][1]
corrNorm = correlations[name][normMoment]
varNew = ( err**2 + valNew**2 * errNorm**2 - 2. * valNew * err * errNorm * corrNorm ) / valNorm**2
momsNew[name] = ( valNew, sqrt(varNew), ( sqrt( valNew**2 / varNew ) ) if varNew != 0. else 0. if valNew == 0. else float('inf') )
corrsNew[name] = { }
# moments correlations
for name0 in funcNames :
for name1 in funcNames :
valsNew = ( momsNew[name0][0], momsNew[name1][0] )
errsNew = ( momsNew[name0][1], momsNew[name1][1] )
errs = ( moments[name0][1], moments[name1][1] )
corr01 = correlations[name0][name1]
corr0Norm = correlations[name0][normMoment]
corr1Norm = correlations[name1][normMoment]
corr01New = ( errs[0] * errs[1] * corr01 + valsNew[0] * valsNew[1] * errNorm**2\
- valsNew[1] * errs[0] * errNorm * corr0Norm - valsNew[0] * errs[1] * errNorm * corr1Norm ) / valNorm**2
if abs( errsNew[0] ) > 1.e-10 and abs( errsNew[1] ) > 1.e-10 :
corr01New /= errsNew[0] * errsNew[1]
elif abs( corr01New ) < 1.e-10 and name0 == normMoment and name1 == normMoment :
corr01New = 1.
elif abs( corr01New ) < 1.e-10 and ( name0 == normMoment or name1 == normMoment ) :
corr01New = 0.
else :
corr01New = -999.
corrsNew[name0][name1] = corr01New
corrsNew[name1][name0] = corr01New
print 'output moments:'
from P2VV.Utilities.DataMoments import writeMoments
writeMoments( momentsFileNorm, BasisFuncNames = funcNames, Moments = momsNew, Correlations = corrsNew )
if printMoms: printMoments( BasisFuncNames = funcNames, Moments = momsNew, Correlations = corrsNew )
def read( self, filePath = 'moments', **kwargs ) :
readMoments( filePath, BasisFuncNames = self._basisFuncNames, Moments = self._coefficients, Correlations = self._correlations,
**kwargs )
self._covMatrixSize = len(self._correlations)
def combineMoments( momentsFilesIn, momentsFileOut, prefix = '', printMoms = True):
funcNames = [ 'Re_ang_A0_A0', 'Re_ang_Apar_Apar', 'Re_ang_Aperp_Aperp'
, 'Im_ang_Apar_Aperp', 'Re_ang_A0_Apar', 'Im_ang_A0_Aperp'
, 'Re_ang_AS_AS', 'Re_ang_Apar_AS', 'Im_ang_Aperp_AS', 'Re_ang_A0_AS' ]
if prefix:
funcNamesWPF = []
for name in funcNames: funcNamesWPF += [prefix + '_' + name]
funcNames = funcNamesWPF
# moment containers
moments = [ ]
correlations = [ ]
# read moments
from P2VV.Utilities.DataMoments import readMoments, printMoments
for momsFile in momentsFilesIn :
moments.append( { } )
correlations.append( { } )
readMoments( momsFile, BasisFuncNames = funcNames, Moments = moments[-1], Correlations = correlations[-1] )
if printMoms: printMoments( BasisFuncNames = funcNames, Moments = moments[-1], Correlations = correlations[-1] )
# combine moments
from ROOT import TMatrixD
combNames = [ name for name in funcNames if moments[0][name][1] > 0. ]
momVec = TMatrixD( len(combNames), 1 )
covMat = TMatrixD( len(combNames), len(combNames) )
for moms, corrs in zip( moments, correlations ) :
mom = TMatrixD( len(combNames), 1 )
cov = TMatrixD( len(combNames), len(combNames) )
for it1, name1 in enumerate(combNames) :
mom[it1][0] = moms[name1][0]
for it2, name2 in enumerate(combNames) :
cov[it1][it2] = moms[name1][1] * moms[name2][1] * corrs[name1][name2]
cov.Invert()
momVec += cov * mom
covMat += cov
covMat.Invert()
momVec = covMat * momVec
momsNew = { }
corrsNew = { }
for name in funcNames :
if moments[0][name][1] > 0. : continue
momsNew[name] = moments[0][name]
corrsNew[name] = correlations[0][name]
from math import sqrt
for it1, name1 in enumerate(combNames) :
val = momVec[it1][0]
err = sqrt( covMat[it1][it1] )
momsNew[name1] = ( val, err, abs( val / err ) )
corrsNew[name1] = { }
for name in funcNames :
if moments[0][name][1] > 0. : continue
corrsNew[name1][name] = correlations[0][name1][name]
for it2, name2 in enumerate(combNames) :
corrsNew[name1][name2] = covMat[it1][it2] / err / sqrt( covMat[it2][it2] )
# write combined moments to file
from P2VV.Utilities.DataMoments import writeMoments
writeMoments( momentsFileOut, BasisFuncNames = funcNames, Moments = momsNew, Correlations = corrsNew )
if printMoms: printMoments( BasisFuncNames = funcNames, Moments = momsNew, Correlations = corrsNew )
funcNames = [ 'Re_ang_A0_A0', 'Re_ang_Apar_Apar', 'Re_ang_Aperp_Aperp'
, 'Im_ang_Apar_Aperp', 'Re_ang_A0_Apar', 'Im_ang_A0_Aperp'
, 'Re_ang_AS_AS', 'Re_ang_Apar_AS', 'Im_ang_Aperp_AS', 'Re_ang_A0_AS' ]
latex = True
# moment containers
moments1 = { }
moments2 = { }
correlations1 = { }
correlations2 = { }
# read moments
print 'input moments 1:'
from P2VV.Utilities.DataMoments import readMoments, printMoments
readMoments( momentsFile1, BasisFuncNames = funcNames, Moments = moments1, Correlations = correlations1 )
printMoments( BasisFuncNames = funcNames, Moments = moments1, Correlations = correlations1 )
print 'input moments 2:'
from P2VV.Utilities.DataMoments import readMoments, printMoments
readMoments( momentsFile2, BasisFuncNames = funcNames, Moments = moments2, Correlations = correlations2 )
printMoments( BasisFuncNames = funcNames, Moments = moments2, Correlations = correlations2 )
from ROOT import TMatrixD
diffInd = 0
diffNames = [ name for name in funcNames if moments1[name][1] != 0. ]
diffs = TMatrixD( len(diffNames), 1 )
diffCovs = TMatrixD( len(diffNames), len(diffNames) )
from math import sqrt
print 'differences:'
# script parameters
momentsFileOrig = 'Sim08_hel_UB_UT_trueTime_BkgCat050_KK30_Phys'
momentsFileNorm = 'Sim08_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_norm'
normMoment = 'Re_ang_A0_A0'
# moment containers
funcNames = [ ]
moments = { }
correlations = { }
# read moments
print 'input moments:'
from P2VV.Utilities.DataMoments import readMoments, printMoments
readMoments( momentsFileOrig, BasisFuncNames = funcNames, Moments = moments, Correlations = correlations, ProcessAll = True )
printMoments( BasisFuncNames = funcNames, Moments = moments, Correlations = correlations )
# calculate moments with new normalization
from math import sqrt
valNorm = moments[normMoment][0]
errNorm = moments[normMoment][1]
momsNew = { }
corrsNew = { }
# moments value and error
for name in funcNames :
valNew = moments[name][0] / valNorm
err = moments[name][1]
corrNorm = correlations[name][normMoment]
varNew = ( err**2 + valNew**2 * errNorm**2 - 2. * valNew * err * errNorm * corrNorm ) / valNorm**2
momsNew[name] = ( valNew, sqrt(varNew), ( sqrt( valNew**2 / varNew ) ) if varNew != 0. else 0. if valNew == 0. else float('inf') )
corrsNew[name] = { }
'Sim08_{0}_{1}_Phys_norm_{2}'.format(MCProd,outputEffMomentsBaselineName,iterNumb),
normMoment = PhysicsReweight.getParNamePrefix() + '_Re_ang_A0_A0',
printMoms = delIntermediateMoms
)
if delIntermediateMoms: os.remove('Sim08_{0}_{1}_Phys_{2}'.format(MCProd,outputEffMomentsBaselineName,iterNumb) )
# combine 2011, 2012 acceptances
if combineEffMoments:
angAcc2011 = 'Sim08_2011_%s_Phys_norm_%s'%(outputEffMomentsBaselineName,iterNumb)
angAcc2012 = 'Sim08_2012_%s_Phys_norm_%s'%(outputEffMomentsBaselineName,iterNumb)
combAccName = 'Sim08_20112012_{0}_Phys_norm_{1}'.format(outputEffMomentsBaselineName,iterNumb)
combineMoments( angAcc2011, angAcc2012, combAccName, Prefix = 'mc', delete=False )
# convert effyciency weights to efficiency moments
moments, correlations = {}, {}
readMoments( combAccName, BasisFuncNames = [], Moments = moments, Correlations = correlations, ProcessAll = True )
convertEffWeightsToMoments( moments, OutputFilePath = combAccName.replace('Phys','weights').replace('_norm',''),
WeightNamesPrefix = PhysicsReweight.getParNamePrefix(),
# PrintMoments = False
)
# plot data after each reweighting step
if makePlots:
from P2VV.Utilities.MCReweighting import plotingScenarios, weightNamesDataKeysMap
plot = True
plotScenarioKey = options.rewSteps.replace('_','') if not mkkBmom2DRew else 'TwoD' + options.rewSteps.replace('_','')
try: case = plotingScenarios[plotScenarioKey]
except KeyError: plot = False
if plot:
for dataSetKeys in case:
dataSets = {}
momentsFilesIn = [ 'Sim08_2011_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_norm', 'Sim08_2012_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_norm' ]
momentsFileOut = 'Sim08_20112012_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_norm'
funcNames = [ 'Re_ang_A0_A0', 'Re_ang_Apar_Apar', 'Re_ang_Aperp_Aperp'
, 'Im_ang_Apar_Aperp', 'Re_ang_A0_Apar', 'Im_ang_A0_Aperp'
, 'Re_ang_AS_AS', 'Re_ang_Apar_AS', 'Im_ang_Aperp_AS', 'Re_ang_A0_AS' ]
# moment containers
moments = [ ]
correlations = [ ]
# read moments
from P2VV.Utilities.DataMoments import readMoments, printMoments
for momsFile in momentsFilesIn :
moments.append( { } )
correlations.append( { } )
readMoments( momsFile, BasisFuncNames = funcNames, Moments = moments[-1], Correlations = correlations[-1] )
printMoments( BasisFuncNames = funcNames, Moments = moments[-1], Correlations = correlations[-1] )
# combine moments
from ROOT import TMatrixD
combNames = [ name for name in funcNames if moments[0][name][1] > 0. ]
momVec = TMatrixD( len(combNames), 1 )
covMat = TMatrixD( len(combNames), len(combNames) )
for moms, corrs in zip( moments, correlations ) :
mom = TMatrixD( len(combNames), 1 )
cov = TMatrixD( len(combNames), len(combNames) )
for it1, name1 in enumerate(combNames) :
mom[it1][0] = moms[name1][0]
for it2, name2 in enumerate(combNames) :
cov[it1][it2] = moms[name1][1] * moms[name2][1] * corrs[name1][name2]
cov.Invert()
# script parameters
weightsFile = 'Sim08_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_norm'
momentsFile = 'Sim08_hel_UB_UT_trueTime_BkgCat050_KK30_Phys_moms_norm'
funcNames = [ 'Re_ang_A0_A0', 'Re_ang_Apar_Apar', 'Re_ang_Aperp_Aperp'
, 'Im_ang_Apar_Aperp', 'Re_ang_A0_Apar', 'Im_ang_A0_Aperp'
, 'Re_ang_AS_AS', 'Re_ang_Apar_AS', 'Im_ang_Aperp_AS', 'Re_ang_A0_AS' ]
# read weights
from P2VV.Utilities.DataMoments import readMoments, printMoments
weights = { }
weightCorrs = { }
readMoments( weightsFile, BasisFuncNames = funcNames, Moments = weights, Correlations = weightCorrs )
printMoments( BasisFuncNames = funcNames, Moments = weights, Correlations = weightCorrs )
# convert weights to moments
from P2VV.Utilities.DataMoments import convertEffWeightsToMoments
convertEffWeightsToMoments( Weights = weights, OutputFilePath = momentsFile )
