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2017_LbtoD0pmunu_Kmunu_mc_background_Lb2pK-Mu.py 32.33 KiB
##########################################################
# AUTOMATICALLY GENERATED FILE IN ganga_options_generic.py
simulation = True
noPID = True
no_restrip = False
stripping_stream = 'Semileptonic'
stripping_line = 'B2XTauTauLeptonic_Lb2pK_Mu_line'
decay = '(( Lambda_b0 -> ^(D0 -> ^mu+ ^mu-) ^(Lambda(1520)0 -> ^p+ ^K-) )) || (( Lambda_b~0 -> ^(D0 -> ^mu- ^mu+) ^(Lambda(1520)~0 -> ^p~- ^K+) )) '
branches = {'mother': '(( Lambda_b0 -> (D0 -> mu+ mu-) (Lambda(1520)0 -> p+ K-) )) || (( Lambda_b~0 -> (D0 -> mu- mu+) (Lambda(1520)~0 -> p~- K+) ))', 'jpsi': '(( Lambda_b0 -> ^(D0 -> mu+ mu-) (Lambda(1520)0 -> p+ K-) )) || (( Lambda_b~0 -> ^(D0 -> mu- mu+) (Lambda(1520)~0 -> p~- K+) ))', 'd1': '(( Lambda_b0 -> (D0 -> ^mu+ mu-) (Lambda(1520)0 -> p+ K-) )) || (( Lambda_b~0 -> (D0 -> ^mu- mu+) (Lambda(1520)~0 -> p~- K+) ))', 'd2': '(( Lambda_b0 -> (D0 -> mu+ ^mu-) (Lambda(1520)0 -> p+ K-) )) || (( Lambda_b~0 -> (D0 -> mu- ^mu+) (Lambda(1520)~0 -> p~- K+) ))', 'inter': '(( Lambda_b0 -> (D0 -> mu+ mu-) ^(Lambda(1520)0 -> p+ K-) )) || (( Lambda_b~0 -> (D0 -> mu- mu+) ^(Lambda(1520)~0 -> p~- K+) ))', 'h1': '(( Lambda_b0 -> (D0 -> mu+ mu-) (Lambda(1520)0 -> ^p+ K-) )) || (( Lambda_b~0 -> (D0 -> mu- mu+) (Lambda(1520)~0 -> ^p~- K+) ))', 'h2': '(( Lambda_b0 -> (D0 -> mu+ mu-) (Lambda(1520)0 -> p+ ^K-) )) || (( Lambda_b~0 -> (D0 -> mu- mu+) (Lambda(1520)~0 -> p~- ^K+) ))'}
year = '2017'
mcdecay = 'lbtopX'
# END AUTOMATICALLY GENERATED FILE IN ganga_options_generic.py
# From here on, the file dv_options_generic.py will be used
# (Stripping will be added first for the lb2pkemu line)
###########################################################
try:
simulation = simulation
noPID = noPID
no_restrip = no_restrip
stripping_stream = stripping_stream
stripping_line = stripping_line
decay = decay
branches = branches
year = year
mcdecay = mcdecay
except NameError as error:
raise RuntimeError("""{error} - most likely due to incorrect usage; don't run this file directly.
The variables 'simulation', 'noPID', 'stripping_line', 'decay', 'branches', 'year', 'mcdecay' have to
be specified first. Correct usage is to run 'ganga_options_generic.py'""")
# don't use f-strings as not supported pre python 3.6!
print("Simulation = {0}".format(simulation))
print("noPID = {0}".format(noPID))
print("no_restrip = {0}".format(no_restrip))
print("year = {0}".format(year))
print("mcdecay descriptor = {0}".format(mcdecay))
print("stripping stream = {0}".format(stripping_stream))
print("stripping line = {0}".format(stripping_line))
print("decay = {0}".format(decay))
print("branches = {0}".format(branches))
from Gaudi.Configuration import *
from LHCbKernel.Configuration import *
from DaVinci.Configuration import *
from DecayTreeTuple.Configuration import *
from Configurables import DaVinci, DecayTreeTuple, MCDecayTreeTuple
from Configurables import TupleToolTISTOS
from Configurables import EventNodeKiller, ProcStatusCheck
from Configurables import LoKi__HDRFilter
from StrippingConf.Configuration import StrippingConf, StrippingStream
from StrippingSettings.Utils import strippingConfiguration
from StrippingArchive.Utils import buildStreams
from StrippingArchive import strippingArchive
##############################################
print("\n## Determined stripping line to be: \n ===>", stripping_line)
print("\n## config determined")
print("\n===> stream = ", stripping_stream)
print("\n===> line = ", stripping_line)
print("\n===> decay = ", decay)
print("\n===> branches = ", branches)
#################################
# ## Stream and stripping line ###
stream = stripping_stream
line = stripping_line
print("\n## Determined stripping line to be: \n ===>", stripping_line)
###########################
# ## Restripping process ###
# In the case that we are dealing with simulation, we may need to restrip due to the fact
# that the stripping version for the simulation is different (older) than that of the
# stripping line
# In the case that we remove the PID requirements, this changes the restripping process
# since we edit the config file to remove these requirements
if simulation == True:
if no_restrip == False:
event_node_killer = EventNodeKiller('StripKiller')
event_node_killer.Nodes = ['/Event/AllStreams', '/Event/Strip']
####################
if noPID == False: # conventional restrip
if year == '2016':
strip = 'stripping28r2p2'
elif year == '2017':
strip = 'stripping29r2p3'
elif year == '2018':
strip = 'stripping34r0p3'
streams = buildStreams(stripping=strippingConfiguration(strip),
archive=strippingArchive(strip))
custom_stream = StrippingStream('AllStreams')
custom_line = 'Stripping'+line
for stream in streams:
for sline in stream.lines:
if sline.name() == custom_line:
custom_stream.appendLines([sline])
#####################
else: # remove PID requirements and restrip
# in this case we need to edit the config to remove PID requirements
# different stripping versions for different years
if year == '2016':
from StrippingArchive.Stripping28r2p2.StrippingRD.StrippingB2XTauTauLeptonic import B2XTauTauLeptonicConf as builder
from StrippingArchive.Stripping28r2p2.StrippingRD.StrippingB2XTauTauLeptonic import default_config as config
elif year == '2017':
from StrippingArchive.Stripping29r2p3.StrippingRD.StrippingB2XTauTauLeptonic import B2XTauTauLeptonicConf as builder
from StrippingArchive.Stripping29r2p3.StrippingRD.StrippingB2XTauTauLeptonic import default_config as config
elif year == '2018':
from StrippingArchive.Stripping34r0p3.StrippingRD.StrippingB2XTauTauLeptonic import B2XTauTauLeptonicConf as builder
from StrippingArchive.Stripping34r0p3.StrippingRD.StrippingB2XTauTauLeptonic import default_config as config
# print the unedited config file
print("OLD CONFIG below")
print(config['CONFIG'])
print("OLD CONFIG above")
# edit the config
config1 = config['CONFIG']
config1['MuonPID'] = -1001
config1['ElectronPID'] = -1001
config1['UseNoPIDsHadrons'] = True
# then print the edited config file
print("NEW CONFIG below")
print(config1)
print("NEW CONFIG above")
lb = builder('B2XTauTauLeptonic', config1)
custom_stream = StrippingStream('MyStream')
# Now we have the stream and the line and can add the lines to the stream
target_line = 'Stripping' + line
for sline in lb.lines():
if sline.name() == target_line:
custom_stream.appendLines([sline])
#######################
filterBadEvents = ProcStatusCheck()
sc = StrippingConf(Streams=[custom_stream],
MaxCandidates=10000,
AcceptBadEvents=False,
BadEventSelection=filterBadEvents)
### Fill tuple with DecayTreeTuple ###
dtt = DecayTreeTuple('DecayTreeTuple')
dtt.Inputs = ['/Event/Phys/{0}/Particles'.format(line)]
else: # no restrip
### Fill tuple with DecayTreeTuple ###
dtt = DecayTreeTuple('DecayTreeTuple')
dtt.Inputs = ['/Event/{0}/Phys/{1}/Particles'.format(stream,line)]
else: # data rather than simulation
### Fill tuple with DecayTreeTuple ###
dtt = DecayTreeTuple('DecayTreeTuple')
dtt.Inputs = ['/Event/{0}/Phys/{1}/Particles'.format(stream,line)]
########################################
# ## Define decay and create branches ###
dtt.Decay = decay
dtt.addBranches(branches)
######################
# ## Add tupletools ###
# # Generic tupletools ##
dtt.ToolList = [] #reset toollist to add verbose to geometry/kinematic
SubMassTool = dtt.addTupleTool('TupleToolSubMass')
#
# will create Sum_{p=2,max) C(N,p) new entries in the nTuple called [head]_M[ij...]
# Particle daughters are sorted by PID at each branch of the tree (cc-independant)
#
#**** Substitution property
#
# usage : TupleTool.Substitution += ["pi+ => K+"] TupleTool.Substitution += ["K+ => pi+"]
# produce alternative mass with substituted PID pi<->K (cc is assumed)
#
#-change only one pion (K) at once in case of several pion (K) in the decay tree (producing separate output par pion (K) )
#
#**** DoubleSubstitution property
#
# usage : TupleTool.DoubleSubstitution += ["K+/pi- => pi+/K-"] TupleTool.DoubleSubstitution += ["K+/K-" => pi+/pi-"]
# change all [K+pi-]cc ([K+K-]cc) pairs to (pi+K-)cc ([pi+pi-]cc)
# change only one pair at once in case of several pairs in the decay tree (producing separate output per pair)
#
# "/" separator is not mandatory : K+pi- syntax is allowed (just a bit slower to parse)
GeometryTool = dtt.addTupleTool('TupleToolGeometry') #Fill geometry related information for DecayTreeTuple
GeometryTool.Verbose=True
# head_MINIP : minimum impact parameter on any PV
# head_MINIPCHI2 : minimum chi2 IP on all PVs
# head_ENDVERTEX_[X|Y|Z] : decay vertex position for composite particles
# head_ENDVERTEX_[X|Y|Z]ERR : decay vertex position error estimate for composite particles
# head_ENDVERTEX_CHI2 : decay vertex chi2
# head_ENDVERTEX_NDOF : decay vertex nDoF
# head_OWNPV_[X|Y|Z] : related primary vertex position
# head_OWNPV_[X|Y|Z]ERR : related primary vertex position error estimate for composite particles
# head_OWNPV_CHI2 : related primary vertex chi2
# head_OWNPV_NDOF : related primary vertex nDoF
# head_IP_OWNPV : impact parameter with respect to the PhysDesktop::relatedVertex() considered particle
# head_IPCHI2_OWNPV : impact parameter chi2 with respect to the relatedVertex() considered particle
# head_FD_OWNPV : flight distance of composite particle wrt. the relatedVertex() considered particle
# head_FDCHI2_OWNPV : flight distance significance in units of chi2 wrt. the relatedVertex() considered particle
# head_DIRA_OWNPV : direction angle wrt. the PhysDesktop::relatedVertex() considered particle
# Verbose being true gives:
# head_TOPPV_[X|Y|Z] : PhysDesktop::relatedVertex() of the top of decay chain position
# head_TOPPV_[X|Y|Z]ERR : PhysDesktop::relatedVertex() of the top of decay chain position error estimate
# head_TOPPV_CHI2 : PhysDesktop::relatedVertex() of the top of decay chain chi2
# head_TOPPV_NDOF : PhysDesktop::relatedVertex() of the top of decay chain nDoF
# head_IP_TOPPV : impact parameter with respect to the PhysDesktop::relatedVertex() of the top of decay chain
# head_IPCHI2_TOPPV : impact parameter chi2 with respect to the relatedVertex() of the top of decay chain
# head_FD_TOPPV : flight distance of composite particle wrt. the relatedVertex() of the top of decay chain
# head_FDCHI2_TOPPV : flight distance significance in units of chi2 wrt. the PhysDesktop::relatedVertex() of the top of decay chain
# head_DIRA_TOPPV : direction angle wrt. the relatedVertex() of the top of decay chain
# head_ORIVX_[X|Y|Z] : ancestor's related primary vertex position (when applicable)
# head_ORIVX_[X|Y|Z]ERR : ancestor's related primary vertex position error estimate (when applicable)
# head_ORIVX_CHI2 : ancestor's related primary vertex chi2 (when applicable)
# head_ORIVX_NDOF : ancestor's related primary vertex nDoF (when applicable)
# head_IP_ORIVX : impact parameter with respect to the ancestor's vertex (when applicable)
# head_IPCHI2_ORIVX : impact parameter chi2 with respect to the ancestor's vertex (when applicable)
# head_FD_ORIVX : flight distance of composite particle wrt. the ancestor's vertex (when applicable)
# head_FDCHI2_ORIVX : flight distance significance in units of chi2 wrt. ancestor's vertex (when applicable)
# head_DIRA_ORIVX : direction angle wrt. ancestor's vertex (when applicable)
KinematicTool = dtt.addTupleTool('TupleToolKinematic') #Fill kinematic information for DecayTreeTuple
KinematicTool.Verbose=True
# head_P : momentum's amplitude
# head_PT : transverse momentum
# head_P[E|X|Y|Z] : four vector momentum
# head_MM : measured mass (or assigned mass in case of 'basic' particle
# head_M : mass calculated from momentum four-vector
# head_MMERR : error on the measured mass (only for non-basic parts)
# Verbose being true gives:
# head_REFP[X|Y|Z]: one point the particle momentum extrapolation goes through
# head_PreFitMass: Mass of 4-vectors of daughters, not yet extrapolated to the head decay vertex (only for composites).
# This is the quantity used in ADAMASS or AM in CombineParticles.CombinationCut
# prefix_AtVtx_P[X|Y|Z]: momentum information of basic particles at origin vertex position
TrackInfoTool = dtt.addTupleTool('TupleToolTrackInfo') #Fill track information for DecayTreeTuple
TrackInfoTool.Verbose=True
# X_TRACK_CHI2NDOF : track chi2/ndof
# X_TRACK_TYPE : track type
# X_TRACK_PCHI2 : track Chi2 probability
# X_TRACK_GhostProb : Ghost probability (run NeuralNetTmva to fill it)
# X_TRACK_CloneDist : Only available for 2009 data
# Verbose being true gives:
# X_TRACK_CHI2 : track chi2
# X_TRACK_NDOF : track ndof
# X_TRACK_VeloCHI2NDOF : Track fit velo chi2/nDoF
# X_TRACK_TCHI2NDOF : Track fit T chi2/nDoF
# X_TRACK_VELO_UTID : hopefully unique double constructed from multiplying all Velo hit IDs
# X_TRACK_TT_UTID : hopefully unique double constructed from multiplying all TT hit IDs
# X_TRACK_IT_UTID : hopefully unique double constructed from multiplying all IT hit IDs
# X_TRACK_OT_UTID : hopefully unique double constructed from multiplying all OT hit IDs
# X_TRACK_VP_UTID : hopefully unique double constructed from multiplying all VP hit IDs
# X_TRACK_UT_UTID : hopefully unique double constructed from multiplying all UT hit IDs
# X_TRACK_FT_UTID : hopefully unique double constructed from multiplying all FT hit IDs
# X_TRACK_nVeloHits : Number of Velo hits on the track
# X_TRACK_nVeloRHits : Number of Velo R hits on the track
# X_TRACK_nVeloPhiHits : Number of Velo phi hits on the track
# X_TRACK_nVeloPileUpHits : Number of Velo pile-up hits on the track
# X_TRACK_nTTHits : Number of TT hits on the track
# X_TRACK_nITHits : Number of IT hits on the track
# X_TRACK_nOTHits : Number of OT hits on the track
# X_TRACK_nVPHits : Number of VP hits on the track
# X_TRACK_nUTHits : Number of UT hits on the track
# X_TRACK_nFTHits : Number of FT hits on the track
# X_TRACK_FirstMeasurementX: x position of state at 'FirstMeasurement'
# X_TRACK_FirstMeasurementY: y position of state at 'FirstMeasurement'
# X_TRACK_FirstMeasurementZ: z position of state at 'FirstMeasurement'
# X_TRACK_History: Algorithm which the track was made with
# X_TRACK_qOverp : q/p of state at 'FirstMeasurement'
# X_TRACK_Tx : x slope of state at 'FirstMeasurement'
# X_TRACK_Ty : y slope of state at 'FirstMeasurement'
EventInfoTool = dtt.addTupleTool('TupleToolEventInfo') #Event and Run number for DecayTreeTuple
EventInfoTool.Verbose=True
# runNumber: well, the run number
# eventNumber:
# BCID and BC type
# Odin and Hlt TCKs
# GPS time
# If the property Mu is given it will fill the Mu of the run. A working dictionary can be
# found at https://twiki.cern.ch/twiki/bin/view/LHCb/NuMuPileUp
# if Verbose is on, also gps time in year,month,day,hour,min,second Note that months are
# numbered [0-11]. That's a convention. Sorry.
PropertimeTool = dtt.addTupleTool('TupleToolPropertime') #Fills the propertime for DecayTreeTuple
# PropertimeTool.Verbose=True
# head_TAU
# head_TAUERR
# head_TAUCHI2
RecoStatsTool = dtt.addTupleTool('TupleToolRecoStats') #Fills Reco stats, from RecSummary.
# RecoStatsTool.Verbose=True
PidTool = dtt.addTupleTool('TupleToolPid') #DLL and PID information to be stored in a Tuple
# PidTool.Verbose=True
# head_ID : particleID().pid();
# For the long lived particles (isBasicParticle()).
# head_PIDe : LHCb::ProtoParticle::CombDLLe
# head_PIDmu : LHCb::ProtoParticle::CombDLLmu
# head_PIDK : LHCb::ProtoParticle::CombDLLk
# head_PIDp : LHCb::ProtoParticle::CombDLLp
ANNPIDTool = dtt.addTupleTool('TupleToolANNPID') #ProbNN values for "Electron", "Muon", "Pion", "Kaon", "Proton", "Ghost"
# ANNPIDTool.Verbose=True
AnglesTool = dtt.addTupleTool('TupleToolAngles') #Fill MC Particle with decay angle in mother frame
# AnglesTool.Verbose=True
# head_CosTheta : angle in mother's frame
# if WRTMother is false, will calculate angle in frame of top of tree
PrimariesTool = dtt.addTupleTool('TupleToolPrimaries') #Primary vertices properties for DecayTreeTuple
# PrimariesTool.Verbose=True
# coordinates PVX, PVY, PVZ
# errors PVXERR, PVYERR, PVZERR
# vertex chi2 PVCHI
# vertex ndf PVNDOF
# Nb of tracks used to do the vertex PVNTRACKS
## Isolation variables ##
# cone isolation #
ConeIsoTool = dtt.addTupleTool('TupleToolConeIsolation')
# choose cones to have a deltaR of 0.5, 0.7, 0.9 radians
ConeIsoTool.MinConeSize = 0.6
ConeIsoTool.MaxConeSize = 0.6
# ConeIsoTool.SizeStep = 0.2
# Fill asymmetry, delta, and component variables
# ConeIsoTool.FillAsymmetry = True
# ConeIsoTool.FillDeltas = True
# ConeIsoTool.FillComponents = True
# head_cc: charged cone
# head_nc: neutral cone
# head_XX_mult : number of objects inside the cone
# head_XX_sPT : scalar-summed pT of the objects inside the cone
# head_XX_vPT : vector-summed pT of the objects inside the cone
# head_XX_P : x, y and z components of the cone momentum
# head_XX_asy_P : momentum asymmetry between the head and the cone defined as (head_P - head_XX_P) / (head_P + head_XX_P)
# head_XX_asy_P : x, y, z and transverse components of the momentum asymmetry
# head_XX_deltaEta : difference in eta between the head and the cone
# head_XX_deltaPhi : difference in phi between the head and the cone
# head_XX_IT : transverse isolation of the head in the cone, defined as head_PT / (head_P + head_XX_P)_T
# head_IT : transverse isolation of the head in the charged and neutral cones, defined as head_PT / (head_P + head_cc_P + head_nc_P)_T
# head_cc_maxPt_Q : charge of the max-pT object in the charged cone
# head_XX_maxPt_P : x, y, z (and e) components of the max-pT object momentum in the cone
# head_MasshPi0: invariant mass of the seed-Pi0 combinations
# head_Pi0_DeltaR: DeltaR between the seed and the pi0 directions
# head_Pi0_E, head_Pi0_PX, head_Pi0_PY, head_Pi0_PZ: four momentum of the pi0
# head_Pi0_M: invariant mass of the pi0
# head_Pi0Ph1_CL, head_Pi0Ph2_CL: confidence levels of the (photon) pi0 daughters
# track isolation #
TrackIsoTool = dtt.addTupleTool('TupleToolTrackIsolation')
# choose cones to have a deltaR of 0.5, 0.7, 0.9 radians
TrackIsoTool.MinConeAngle = 0.6
TrackIsoTool.MaxConeAngle = 0.6
# TrackIsoTool.StepSize = 0.2
# fill asymmetry and DeltaAngles variables
TrackIsoTool.FillAsymmetry = True
# TrackIsoTool.FillDeltaAngles = True
# Open up a cone around head, exclude all tracks that are in the decay descriptor
# (i.e. that belong to the decay you are looking for), build the variables with
# the remaining tracks.
# head_cmult : Number of tracks inside cone.
# head_cp : Summed p inside cone
# head_cpt : Summed pt inside cone
# head_cpx : Summed px inside cone
# head_cpy : Summed py inside cone
# head_cpz : Summed pz inside cone
# If Verbose, or other flags are set:
# Asymmetry variables
# head_pasy : (head_P - head_cp)/(head_P + head_cp)
# head_ptasy : (head_PT - head_cpt)/(head_PT + head_cpt)
# head_pxasy : (head_Px - head_cpx)/(head_Px + head_cpx)
# head_pyasy : (head_Py - head_cpy)/(head_Py + head_cpy)
# head_pzasy : (head_Pz - head_cpz)/(head_Pz + head_cpz) Delta angle variables
# head_DeltaEta : Difference in eta between summed tracks and head
# head_DeltaPhi : Difference in phi between summed tracks and head
# MinConeAngle: Set the minimal deltaR of the cone (default = 0.5), in radians
# MaxConeAngle: Set the maximum deltaR of the cone (default = 1.0), in radians
# StepSize: Set the step of deltaR between two iterations (default = 0.1), in radians
# TrackType: Set the type of tracks which are considered inside the cone (default = 3)
# FillAsymmetry: Flag to fill the asymmetry variables (default = false)
# FillDeltaAngles: Flag to fill the delta angle variables (default = false)
# vertex isolation #
VtxIsoTool = dtt.addTupleTool('TupleToolVtxIsoln')
# head_NOPARTWITHINDCHI2WDW : no. of non-signal particles that when added to vertex give delta chi2 < specified window
# head_NOPARTWITHINCHI2WDW : no. of non-signal particles that when added to vertex give chi2 < specified window
# head_SMALLESTCHI2: chi2 of smallest chi2 combination with any of the input Particles
# head_SMALLESTDELTACHI2: delta chi2 of smallest delta chi2 combination with any of the input Particles
#### updates:
# (head)_NumVtxWithinChi2WindowOneTrack: number of particles that generate a vertex within a chi2 window
# (head)_SmallestDeltaChi2OneTrack: smallest delta chi2 when adding one track
# (head)_SmallestDeltaChi2MassOneTrack: mass of the candidate with the smallest delta chi2
# (head)_SmallestDeltaChi2TwoTracks: smallest delta chi2 when adding one track to the combination
# that has the smallest delta chi2 when adding one track
# (head)_SmallestDeltaChi2MassTwoTracks: mass of the candidate with the smallest delta chi2 when adding
# one track to the combination that has the smallest delta chi2 when adding one track
## Hybrid tupletool ##
all_hybrid = dtt.addTupleTool('LoKi::Hybrid::TupleTool/LoKi_All')
all_hybrid.Variables = {
'ETA' : "ETA", #pseudorapidity
'PHI' : "PHI", #asimuthal angle
'MINIPCHI2' : "MIPCHI2DV(PRIMARY)",
#The special version of LoKi::Particles::MinImpParChi2 functor which gets all the primary
#vertices from desktop.
'MINIP' : "MIPDV(PRIMARY)",
#The special version of LoKi::Particles::MinImpPar functor which gets all the primary
#vertices from desktop.
'IPCHI2_OWNPV' : "BPVIPCHI2()",
#The special "context-dependent" version of LoKi::Particles::ImpParChi2 functor which gets
#the related primary vertex from IPhysDesktop tool
'IP_OWNPV' : "BPVIP()",
#The special "context-dependent" version of LoKi::Particles::ImpPar functor which gets the
#related primary vertex from IPhysDesktop tool.
'DIRA_OWNPV' : "BPVDIRA",
'ghost' : "TRGHP", #simple evaluator of "ghost probability"
'TrackCHI2DOF' : 'TRCHI2DOF',
'FD_CHI2' : "BPVVDCHI2",
#BPV = Adaptor to "best-primary-vertex", VDCHI2 = Evaluator of the chi2 of GEOMETRY distance
#between the particle "endVertex" and "the vertex".
'VCHI2DOF' : 'VFASPF(VCHI2/VDOF)',
# #Decay tree fitter functions:
# 'DTF_CHI2NDOF' : "DTF_CHI2NDOF( True )",
# #Simple evaluator of $\chi^2$ per degree of freedom for the decay tree fit.
# 'DTF_VCHI2NDOF' : "DTF_FUN ( VFASPF(VCHI2/VDOF) , True )",
# #VCHI2 = evaluator of the Chi2 of the vertex / VDOF = evaluator of the number of degrees
# #of freedom for the vertex
# 'DTF_MASS_JpsiConstr' : "DTF_FUN ( M , True , 'J/psi(1S)' )" ,
# 'DTF_MASS' : "DTF_FUN ( M , True )" ,
# 'DTF_CTAU"' : "DTF_CTAU( 0, True )",
# #Evaluate $c\tau$ for the dauthter particle in the decay tree.
# 'DTF_CTAUS' : "DTF_CTAUSIGNIFICANCE( 0, True )"
# #Evaluate $ \frac{c\tau}{\sigma \left( c\tau\right) } $ for the dauthter particle
# #in the decay tree.
}
lb_hybrid = dtt.mother.addTupleTool('LoKi::Hybrid::TupleTool/LoKi_Lb')
lb_hybrid.Variables = {
'DOCAjpsiinter' : "DOCA(1,2)",
'DOCAmotherjpsi' : "DOCA(0,1)",
'DOCAmotherinter' : "DOCA(0,2)",
'DOCAjpsiinterCHI2' : "DOCACHI2(1,2)",
'DOCAmotherjpsiCHI2' : "DOCACHI2(0,1)",
'DOCAmotherinterCHI2' : "DOCACHI2(0,2)"
}
jpsi_hybrid = dtt.jpsi.addTupleTool('LoKi::Hybrid::TupleTool/LoKi_jpsi')
jpsi_hybrid.Variables = {
'DOCAd1d2' : "DOCA(1,2)",
'DOCAjpsid1' : "DOCA(0,1)",
'DOCAjpsid2' : "DOCA(0,2)",
'DOCAd1d2CHI2' : "DOCACHI2(1,2)",
'DOCAjpsid1CHI2' : "DOCACHI2(0,1)",
'DOCAjpsid2CHI2' : "DOCACHI2(0,2)"
}
inter_hybrid = dtt.inter.addTupleTool('LoKi::Hybrid::TupleTool/LoKi_inter')
inter_hybrid.Variables = {
#note that the end vertex of the intermediate hadron is also the end vertex of the lb
'DOCAh1h2' : "DOCA(1,2)",
'DOCAmotherh1' : "DOCA(0,1)",
'DOCAmotherh2' : "DOCA(0,2)",
'DOCAh1h2CHI2' : "DOCACHI2(1,2)",
'DOCAmotherh1CHI2' : "DOCACHI2(0,1)",
'DOCAmotherh2CHI2' : "DOCACHI2(0,2)"
}
################
### Triggers ###
# Add trigger list #
L0Triggers = ['L0MuonDecision','L0DiMuonDecision','L0HadronDecision']
Hlt1Triggers = [# muon lines
'Hlt1TrackMuonDecision','Hlt1SingleMuonNoIPDecision','Hlt1SingleMuonHighPTDecision',
# dimuon lines
'Hlt1DiMuonHighMassDecision','Hlt1DiMuonLowMassDecision',
# MVA lines
'Hlt1TrackMVADecision','Hlt1TrackMVALooseDecision','Hlt1TrackMuonMVADecision',
'Hlt1TwoTrackMVALooseDecision','Hlt1TwoTrackMVADecision'
]
Hlt2Triggers = [# topo lines
'Hlt2Topo2BodyDecision','Hlt2Topo3BodyDecision','Hlt2Topo4BodyDecision',
'Hlt2TopoMu2BodyDecision','Hlt2TopoMu3BodyDecision','Hlt2TopoMu4BodyDecision',
'Hlt2TopoMuMu2BodyDecision','Hlt2TopoMuMu3BodyDecision','Hlt2TopoMuMu4BodyDecision',
# muon lines
'Hlt2SingleMuonDecision','Hlt2SingleMuonHighPTDecision','Hlt2SingleMuonLowPTDecision',
'Hlt2SingleMuonRareDecision','Hlt2SingleMuonVHighPTDecision',
# dimuon lines
'Hlt2DiMuonDecision','Hlt2DiMuonJPsiDecision','Hlt2DiMuonDetachedDecision',
'Hlt2DiMuonDetachedHeavyDecision','Hlt2DiMuonDetachedJPsiDecision',
'Hlt2DiMuonDetachedPsi2SDecision','Hlt2DiMuonSoftDecision'
]
# Electrons in Sel
if '_E_' in stripping_line or '_MuE_' in stripping_line or '_EPi_' in stripping_line:
L0Triggers += ["L0ElectronDecision","L0ElectronHiDecision","L0PhotonDecision","L0PhotonHiDecision"]
Hlt1Triggers += ["Hlt1SingleElectronNoIPDecision"]
Hlt2Triggers += ["Hlt2TopoE2BodyDecision","Hlt2TopoE3BodyDecision","Hlt2TopoE4BodyDecision",
"Hlt2TopoEE2BodyDecision","Hlt2TopoEE3BodyDecision","Hlt2TopoEE4BodyDecision",
"Hlt2TopoMuE2BodyDecision","Hlt2TopoMuE3BodyDecision","Hlt2TopoMuE4BodyDecision"
]
AllTriggers = L0Triggers + Hlt1Triggers + Hlt2Triggers
MuonTriggers = [# L0
'L0MuonDecision',
# Hlt1
'Hlt1TrackMuonDecision','Hlt1SingleMuonNoIPDecision','Hlt1SingleMuonHighPTDecision',
'Hlt1TrackMVADecision','Hlt1TrackMVALooseDecision','Hlt1TrackMuonMVADecision',
# Hlt2
'Hlt2SingleMuonDecision','Hlt2SingleMuonHighPTDecision',
'Hlt2SingleMuonLowPTDecision','Hlt2SingleMuonRareDecision','Hlt2SingleMuonVHighPTDecision'
]
HadronTriggers = [# L0
'L0HadronDecision',
# Hlt1
'Hlt1TrackMVADecision','Hlt1TrackMVALooseDecision'
]
ElectronTriggers = [# L0
"L0ElectronDecision","L0ElectronHiDecision","L0PhotonDecision","L0PhotonHiDecision",
# Hlt1
"Hlt1SingleElectronNoIPDecision","Hlt1TrackMVADecision"]
# TupleToolTISTOS #
# It saves the trigger TIS/TOS decisions for each particle for each Hlt Selection
dtt.mother.ToolList += [ "TupleToolTISTOS" ]
dtt.mother.addTool( TupleToolTISTOS, name = "TupleToolTISTOS" )
dtt.mother.TupleToolTISTOS.Verbose = True
dtt.mother.TupleToolTISTOS.TriggerList = AllTriggers
dtt.d2.ToolList += [ "TupleToolTISTOS" ]
dtt.d2.addTool( TupleToolTISTOS, name = "TupleToolTISTOS" )
dtt.d2.TupleToolTISTOS.Verbose = True
dtt.d2.TupleToolTISTOS.TriggerList = HadronTriggers
dtt.d1.ToolList += [ "TupleToolTISTOS" ]
dtt.d1.addTool( TupleToolTISTOS, name = "TupleToolTISTOS" )
dtt.d1.TupleToolTISTOS.Verbose = True
dtt.d1.TupleToolTISTOS.TriggerList = HadronTriggers
dtt.h1.ToolList += [ "TupleToolTISTOS" ]
dtt.h1.addTool( TupleToolTISTOS, name = "TupleToolTISTOS" )
dtt.h1.TupleToolTISTOS.Verbose = True
if '_Mu_' in stripping_line or '_MuE_' in stripping_line or '_MuPi_' in stripping_line:
dtt.h1.TupleToolTISTOS.TriggerList = MuonTriggers
elif '_EPi_' in stripping_line:
dtt.h1.TupleToolTISTOS.TriggerList = ElectronTriggers
elif '_PiPi_' in stripping_line:
dtt.h1.TupleToolTISTOS.TriggerList = HadronTriggers
# else: # TODO remove
# print('LOCAL: ERROR WITH h1 TRIGGER ASSIGNMENT')
dtt.h2.ToolList += [ "TupleToolTISTOS" ]
dtt.h2.addTool( TupleToolTISTOS, name = "TupleToolTISTOS" )
dtt.h2.TupleToolTISTOS.Verbose = True
if '_E_' in stripping_line or '_MuE_' in stripping_line:
dtt.h2.TupleToolTISTOS.TriggerList = ElectronTriggers
elif '_EPi_' in stripping_line or '_PiPi_' in stripping_line:
dtt.h2.TupleToolTISTOS.TriggerList = HadronTriggers
## MC truth value tupletools ##
if simulation == True:
MCTruthTool = dtt.addTupleTool('TupleToolMCTruth') #Fill MC truth info if a link is present
# head_TRUEID : true pid
MCTruthTool.ToolList = [
"MCTupleToolKinematic",
# head_TRUEP[E|X|Y|Z] : true four vector momentum
# head_TRUEPT : true transverse momentum, PT
# head_TRUEORIGINVERTEX_[X|Y|Z] : position of the true origin vertex.
# head_TRUEENDVERTEX_[X|Y|Z] : position of the true end vertex (the first one)
# head_TRUEISSTABLE : MCAssociate has no daughters.
# head_TRUETAU : true propertime
"MCTupleToolHierarchy",
# head_MC_MOTHER_ID : true mc mother ID
# head_MC_MOTHER_KEY : true mc mother key
# head_MC_GD_MOTHER_ID : grand mother ID
# head_MC_GD_MOTHER_KEY : grand mother key
# head_MC_GD_GD_MOTHER_ID : grand grand mother ID
# head_MC_GD_GD_MOTHER_KEY : grand grand mother key
]
## Hybrid tupletool ##
hybrid_mc_dtt = dtt.addTupleTool('LoKi::Hybrid::MCTupleTool/LoKi_All_MC')
hybrid_mc_dtt.Variables = {
'MCETA' : "MCETA", #pseudorapidity
'MCPHI' : "MCPHI", #asimuthal angle
}
MCBackgroundInfoTool = dtt.addTupleTool('TupleToolMCBackgroundInfo') #Fill the info from IBackgroundCategory.
# head_BKGCAT : category
# add mcdecaytreetuple
# mcdtt decay descriptor
mcdecay_strings = {
'lbtopkll': "[Lambda_b0 ==> ^p+ ^K- ^l+ ^l-]CC",
'lbtopkllpi0': "[Lambda_b0 ==> ^p+ ^K- ^l+ ^l- ^pi0]CC",
'lbtopkjpsi': '[Lambda_b0 ==> ^p+ ^K- ^J/psi(1S)]CC',
'lbtopX': "([Lambda_b0]cc --> [p+]cc ... )", # only mother branch
'xibtopX': "([Xi_b0]cc --> [p+]cc ... )", # only mother branch
'bstokX': "([B_s0]cc --> [K+]cc ... )", # only mother branch
'b0tokX': "([B0]cc --> [K+]cc ... )", # only mother branch
'b0toDX': "([B0]cc --> [D-]cc ... )", # only mother branch
'b0toD0X': "([B0]cc --> [D0]cc ... )", # only mother branch
'bstoDsX': "([B_s0]cc --> [D_s-]cc ... )", # only mother branch
'btoD0X': "([B+]cc --> [D0]cc ... )", # only mother branch
'lbtolcX': "([Lambda_b0]cc --> [Lambda_c+]cc ... )", # only mother branch
'b0toDsX': "([B0]cc --> [D_s-]cc ... )", # only mother branch
'b0topX': "([B0]cc --> [p+]cc ... )", # only mother branch
}
print("\n## Matching mcdecay identifier to correct string: \n===> ", mcdecay)
mcdecay = mcdecay_strings[mcdecay]
print("===> matched: ", mcdecay)
def Make_MCTuple(decay):
MCTuple = MCDecayTreeTuple("MCDecayTreeTuple")
MCTuple.Decay = decay
MCTuple.setDescriptorTemplate( decay )
MCTuple.ToolList = [
"MCTupleToolKinematic"
, "MCTupleToolHierarchy"
, "MCTupleToolAngles"
, "MCTupleToolPID"
, "TupleToolEventInfo"
, "TupleToolRecoStats"
]
## Hybrid tupletool ##
hybrid_mc_mcdtt = MCTuple.addTupleTool('LoKi::Hybrid::MCTupleTool/LoKi_All_MC')
hybrid_mc_mcdtt.Variables = {
'MCETA' : "MCETA", #pseudorapidity
'MCPHI' : "MCPHI", #asimuthal angle
}
return MCTuple
MCTuple = Make_MCTuple(mcdecay)
#########################
# ## Configure DaVinci ###
from Configurables import GaudiSequencer
MySequencer = GaudiSequencer('Sequence')
if simulation == True:
MySequencer.Members = [event_node_killer, sc.sequence(), dtt, MCTuple]
# MySequencer.Members = [event_node_killer, sc.sequence(),dtt]
else:
MySequencer.Members = [dtt]
DaVinci().UserAlgorithms += [MySequencer]
DaVinci().EvtMax = -1
DaVinci().PrintFreq = 1000