"pi+:lep",
"abs(d0)<0.08 and abs(z0)<0.3 and muonID>0.9 and pidDeltaLogLikelihoodValueExpert(13,211,ALL)>28.9"
)
fillParticleList("pi+:highP",
"abs(d0)<5 and abs(z0)<10 and useCMSFrame(p)>2.2")
#event selection
cutAndCopyList(
'B-:evtslt', 'B-:good',
'nTracks>4 and ROE_mbc(cleanMask)>5.1 and ROE_deltae(cleanMask)>-2.4 and ROE_deltae(cleanMask)<0.8 and daughter(0,chiProb)>0.001 and abs(daughter(0,d0))<0.08 and abs(daughter(0,z0))<0.3 and useCMSFrame(p)>2.2 and useCMSFrame(p)<3.1 and daughter(0,nCDCHits)>0 and daughter(0,kaonID)<0.04 and daughter(0,electronID)<0.1 and thrustOm<0.99 and daughter(0,pidDeltaLogLikelihoodValueExpert(13,211,ALL))>28.9 and NhighP<2 and nROEKLMClusters<6 and ROE_eextra(cleanMask)<4.4 and missP(cleanMask,0)>2.3'
)
#
from flavorTagger import *
use_central_database("analysis_AAT-parameters_release-01-02-03")
flavorTagger(particleLists=['B-:evtslt'])
#-------------------------------------------------NTuple maker---------------------------------------------
toolsmu = ['EventMetaData', '^B- -> ^mu-']
toolsmu += ['MCTruth', '^B- -> ^mu-']
toolsmu += ['Kinematics', '^B- -> ^mu-']
toolsmu += ['MCKinematics', '^B- -> ^mu-']
toolsmu += ['DeltaEMbc', 'B- -> mu-']
toolsmu += [
'CustomFloats[useCMSFrame(E):useCMSFrame(px):useCMSFrame(py):useCMSFrame(pz):useCMSFrame(p)]',
'^B- -> mu-'
]
toolsmu += ['CustomFloats[useCMSFrame(mcE):useCMSFrame(mcP)]', '^B- -> ^mu-']
toolsmu += ['CustomFloats[d0]', 'B- -> ^mu-']
toolsmu += ['CustomFloats[z0]', 'B- -> ^mu-']
toolsmu += ['CustomFloats[muonID]', 'B- -> ^mu-']
[E>0.060 and abs(clusterTiming) < 20 and clusterReg==2] or \
[E>0.056 and abs(clusterTiming) < 44 and clusterReg==3]'
cleanMask = ('cleanMask', 'abs(d0) < 10.0 and abs(z0) < 20.0', eclCut)
# append both masks to ROE
appendROEMasks('B0:signal', [oldMask, cleanMask])
# choose one mask which is applied
buildContinuumSuppression('B0:signal', 'cleanMask')
matchMCTruth('B0:signal')
TagV('B0:signal', 'breco')
flavorTagger(particleLists='B0:signal', weightFiles='B2JpsiKs_muBGx1')
matchMCTruth('pi+:all')
#matchMCTruth('K_10:all')
matchMCTruth('gamma:loose')
#rankByHighest()
toolsB0_meson = ['Kinematics', '^B0 -> ^K_S0 ^pi+ ^pi- ^gamma']
toolsB0_meson += ['CustomFloats[cosTheta:isSignal:isContinuumEvent]', '^B0']
#toolsB0_meson += ['MCKinematics','^B0 -> ^K_10 gamma']
toolsB0_meson += ['MCTruth', '^B0 -> ^K_S0 ^pi+ ^pi- ^gamma']
toolsB0_meson += ['MCHierarchy', '^B0 -> ^K_S0 ^pi+ ^pi- gamma']
toolsB0_meson += ['Vertex', '^B0 -> ^K_S0 pi+ pi- gamma']
toolsB0_meson += ['MCVertex', '^B0 -> ^K_S0 pi+ pi- gamma']
#toolsB0_meson += ['PDGCode','^B0']
toolsB0_meson += ['InvMass', '^B0 -> ^K_S0 pi+ pi- gamma']
toolsB0_meson += ['DeltaEMbc', '^B0']
reconstructDecay('phi:all -> pi0:veryLooseFit pi+:all pi-:all','0.95< M < 1.07')
vertexKFit('phi:all', 0.0)
matchMCTruth('phi:all')
reconstructDecay('B0:ch3 -> phi:all K_S0:mdst','Mbc > 5.2 and abs(deltaE) < 0.2')
vertexRave('B0:ch3', 0.0, 'B0:ch3 -> [phi -> ^pi+ ^pi- pi0] ^K_S0', 'iptube')
matchMCTruth('B0:ch3')
# get the rest of the event:
buildRestOfEvent('B0:ch3')
# flavor tagging
flavorTagger(
mode='Expert',
particleList='B0:ch3',
combinerMethods=['TMVA-FBDT', 'FANN-MLP'],
workingDirectory="./JpsiMuMu_ftTrain/BGx1",
belleOrBelle2='Belle2')
# get tag vertex ('breco' is the type of MC association)
TagV('B0:ch3', 'breco')
# get continuum suppression (needed for flavor tagging)
buildContinuumSuppression('B0:ch3')
if action == 'expert':
# Variables for training.
trainVars = [
'R2',