def __apply_configuration__(self) :
from Configurables import ( GaudiSequencer, CombineParticles )
from PhysSelPython.Wrappers import Selection, SelectionSequence, DataOnDemand
if not self.isPropertySet("Sequencer") :
raise RuntimeError("ERROR : Sequence not set")
seq = self.getProp("Sequencer")
if self.getProp("RunSelection") :
# STD particles
from StandardParticles import StdLooseMuons
# J/psi -> mu mu
JPsiMuMuName = self.__sel_name__
JPsiMuMu = CombineParticles(JPsiMuMuName)
JPsiMuMu.DecayDescriptor = "J/psi(1S) -> mu+ mu- "
JPsiMuMu.CombinationCut = "(ADAMASS('J/psi(1S)') < 150*MeV)"
JPsiMuMu.MotherCut = "(ADMASS('J/psi(1S)') < 130*MeV) & (VFASPF(VCHI2/VDOF)<6) & (PT > 2500*MeV)"
JPsiMuMu.DaughtersCuts = {"mu+" : "(PT>1400*MeV)"\
"& (P>5*GeV)"\
"& (TRCHI2DOF<2.0)"\
"& (PPINFO(LHCb.ProtoParticle.MuonBkgLL,-10000)<-2.5)"\
"& (PPINFO(LHCb.ProtoParticle.MuonMuLL,-10000)>-10)"}
self.setOptions(JPsiMuMu)
JPsiMuMuSel = Selection( JPsiMuMuName+'Sel',
Algorithm = JPsiMuMu,
RequiredSelections = [StdLooseMuons] )
# Selection Sequence
selSeq = SelectionSequence( self.__sel_name__+'Seq', TopSelection = JPsiMuMuSel )
# Run the selection sequence.
seq.Members += [selSeq.sequence()]
# Particle Monitoring plots
if self.getProp("RunMonitors") :
from Configurables import ( ParticleMonitor )
plotter = ParticleMonitor(self.__sel_name__+"Plots")
if self.getProp("RunSelection") :
plotter.Inputs = [ 'Phys/'+self.__sel_name__+'Sel' ]
else:
musel = "(PT>1400*MeV) & (P>5*GeV) & (TRCHI2DOF<2.0) & "\
"(PPINFO(LHCb.ProtoParticle.MuonBkgLL,-10000)<-2.5) & "\
"(PPINFO(LHCb.ProtoParticle.MuonMuLL,-10000)>-10)"
_code = "( ( INTREE( ('mu+'==ID) & "+musel+" ) ) | ( INTREE( ('mu-'==ID) & "+musel+" ) ) )"
from Configurables import FilterDesktop
filter = FilterDesktop( name = self.__sel_name__+"RICHFiltered",
Code = _code,
Inputs = self.getProp("Candidates") )
plotter.Inputs = [ 'Phys/'+filter.name() ]
seq.Members += [filter]
plotter.PeakCut = "(ADMASS('J/psi(1S)')<20*MeV)" # Considering sigma = 13
plotter.SideBandCut = "(ADMASS('J/psi(1S)')>20*MeV)" # Considering sigma = 13
plotter.PlotTools = self.getProp("PlotTools")
self.setOptions(plotter)
seq.Members += [plotter]
# Make a DST ?
if self.getProp("MakeSelDST"):
# Prescale
from Configurables import DeterministicPrescaler
scaler = DeterministicPrescaler( self.__sel_name__+'PreScale',
AcceptFraction = self.getProp("DSTPreScaleFraction") )
seq.Members += [scaler]
# Write the DST
MyDSTWriter = SelDSTWriter( self.__sel_name__+"DST",
SelectionSequences = [ selSeq ],
OutputPrefix = self.__sel_name__ )
seq.Members += [MyDSTWriter.sequence()]
# MC Performance checking ?
if self.getProp("MCChecks") :
from Configurables import ParticleEffPurMoni
mcPerf = ParticleEffPurMoni(JPsiMuMuName+"MCPerf")
mcPerf.Inputs = ['Phys/'+self.__sel_name__+'Sel']
self.setOptions(mcPerf)
seq.Members += [mcPerf]
# Ntuple ?
if self.getProp("MakeNTuple") :
from Configurables import ( DecayTreeTuple,
TupleToolDecay,
LoKi__Hybrid__FilterCriterion,
LoKi__Hybrid__TupleTool,
TupleToolMCBackgroundInfo,
BackgroundCategory,
TupleToolTrigger,
TupleToolMCTruth,
MCTupleToolKinematic,
MCTupleToolHierarchy,
TupleToolVtxIsoln,
TupleToolP2VV
)
JPsiMuMuTree = DecayTreeTuple( JPsiMuMuName + 'Tuple')
JPsiMuMuTree.Inputs = [ 'Phys/'+JPsiMuMuName]
JPsiMuMuTree.Decay = 'J/psi(1S) -> ^mu+ ^mu- '
# set some names for ntuple branchs
MyBranch_jpsi = "jpsi"
MyBranch_mup = "mup"
MyBranch_mum = "mum"
# label the branches for the particle tools
JPsiMuMuTree.Branches = {
MyBranch_jpsi : "J/psi(1S) : J/psi(1S) -> mu+ mu- ",
MyBranch_mup : "J/psi(1S) -> ^mu+ mu- ",
MyBranch_mum : "J/psi(1S) -> mu+ ^mu- ",
}
JPsiMuMuTree.ToolList = [
"TupleToolEventInfo"
, "TupleToolGeneration"
, "TupleToolMCTruth"
, "TupleToolMCBackgroundInfo"
, "MCTupleToolKinematic"
, "TupleToolPrimaries"
, "TupleToolVtxIsoln"
, "TupleToolTrackInfo"
, "TupleToolPid"
, "TupleToolGeometry"
, "TupleToolKinematic"
, "TupleToolPropertime"
, "TupleToolPid"
, "TupleToolPrimaries"
, "TupleToolTrigger"
]
JPsiMuMuTree.addTool(BackgroundCategory())
JPsiMuMuTree.BackgroundCategory.SoftPhotonCut = 2000
JPsiMuMuTree.OutputLevel = INFO
JPsiMuMuTree.addTool(TupleToolTrigger())
JPsiMuMuTree.TupleToolTrigger.VerboseL0 = True
JPsiMuMuTree.addTool(TupleToolMCTruth())
JPsiMuMuTree.TupleToolMCTruth.addTool(MCTupleToolKinematic())
JPsiMuMuTree.TupleToolMCTruth.addTool(MCTupleToolHierarchy())
JPsiMuMuTree.TupleToolMCTruth.ToolList = [
"MCTupleToolKinematic" ,
"MCTupleToolHierarchy"
]
JPsiMuMuTree.TupleToolMCTruth.MCTupleToolKinematic.StoreKineticInfo = True
JPsiMuMuTree.TupleToolMCTruth.MCTupleToolKinematic.StoreVertexInfo = True
JPsiMuMuTree.TupleToolMCTruth.MCTupleToolKinematic.StorePropertimeInfo = False
JPsiMuMuTree.addTool(TupleToolVtxIsoln( OutputLevel = 6 ))
JPsiMuMuTree.TupleToolVtxIsoln.IP = 2.0
JPsiMuMuTree.TupleToolVtxIsoln.InputParticles = [ "Phys/StdLooseMuons"]
seq.Members += [JPsiMuMuTree]
JPsiMuMuTree.NTupleLUN = "JPSIMUMU"
from Configurables import NTupleSvc
NTupleSvc().Output = ["JPSIMUMU DATAFILE='JpsiMuMu_Presel.root' TYP='ROOT' OPT='NEW'"]
sstream = StrippingStream("TestStream")
sstream.appendLines(B2XMuMuLines)
sstream.OutputLevel = 2
sc.appendStream(sstream)
#---------------------------
# Run fixing XmumuLine
#---------------------------
from Configurables import PromptNeutrinoTupleTool
stripping_line = 'B2XMuMu_Line'
stream = 'AllStreams'
tuple = DecayTreeTuple('PromptNeutrinoTupleTool')
tuple.OutputLevel = INFO
tuple.Inputs = ['/Event/{0}/Phys/{1}/Particles'.format(stream, stripping_line)]
tuple.Decay = "[B+ -> ^( J/psi(1S) -> ^mu- ^mu+ ) ^pi+]CC"
tuple.Branches = {
"B": "[B+ -> ( J/psi(1S) -> mu- mu+ ) pi+ ]CC",
"Jpsi": "[B+ -> ^(J/psi(1S) -> mu- mu+) pi+]CC",
"mu_prim": "[B+ -> (J/psi(1S) -> mu- ^mu+) pi+]CC",
"mu_sec": "[B+ -> (J/psi(1S) -> ^mu- mu+) pi+]CC",
"pi": "[B+ -> (J/psi(1S) -> mu- mu+) ^pi+]CC",
}
tuple.ToolList = [
"TupleToolKinematic",
"TupleToolPid",
"TupleToolGeometry",
def decay_tree_tuple(name, decay, mothers, intermediate, daughters, inputs,
mc):
"""Return a configured DecayTreeTuple instance.
A DecayTreeTuple is configured with the given decay descriptor.
The mothers dictionary is used to give exclusive tools to vertices, and it
should be, as daughters, a dictionary of tuple branch names to branch
descriptors.
A typical method call might look like
decay_tree_tuple(
'TupleDstToD0pi_D0ToKpi',
'[D*(2010)+ -> K- pi+]CC',
{
'Dst': '[D*(2010) -> (D0 -> K- pi+) pi+]CC',
'D0': '[D*(2010) -> ^(D0 -> K- pi+) pi+]CC'
},
{
'D0_K': '[D*(2010) -> (D0 -> ^K- pi+) pi+]CC',
'D0_pi': '[D*(2010) -> (D0 -> K- ^pi+) pi+]CC',
'Dst_pi': '[D*(2010) -> (D0 -> K- pi+) ^pi+]CC'
},
'Phys/StrippingLineName/Particles'
)
Keyword arguments:
name -- TDirectory the DecayTreeTuple TTree will be saved in
decay -- Decay descriptor
mothers -- Branch descriptors to be added to the tuple as mothers;
decaying particles
daughters -- Branch descriptors to be added to the tuple as daughters;
final state particles
inputs -- str of list of str, as the value of DecayTreeTuple.Inputs
mc -- Extra MC information is included if True
"""
# Define tuple tools to add
tools = [
"TupleToolPropertime",
'TupleToolEventInfo',
]
# Extra variables, added using LoKi hybrid tuple tools
basic_loki_vars = {
'ETA': 'ETA',
'PHI': 'PHI',
'PT': 'PT',
'ID': 'ID',
'P': 'P',
'Loki_BPVIPCHI2': 'BPVIPCHI2()',
'Loki_MIPCHI2DV': 'MIPCHI2DV(PRIMARY)',
}
intermediate_loki_vars = {
'Loki_AM34': 'LoKi.Particles.PFunA(AM34)',
'Loki_AM4': 'LoKi.Particles.PFunA(AM4)',
'Loki_BPVDIRA': "BPVDIRA",
'Loki_acosBPVDIRA': "acos(BPVDIRA)",
}
daughter_loki_vars = {
'PIDK': 'PIDK',
'PIDe': 'PIDe',
'PIDmu': 'PIDmu',
'PIDp': 'PIDp',
'Loki_TRACKCHI2NDOF': 'TRCHI2DOF',
'Loki_TRACKGHOSTPROB': 'TRGHOSTPROB',
}
mother_loki_vars = {
'M': 'M',
'Loki_BPVVDCHI2': 'BPVVDCHI2',
'Loki_BPVIPCHI2': 'BPVIPCHI2()',
'Loki_DOCAMAX': 'DOCAMAX',
'Loki_AMAXDOCA': "LoKi.Particles.PFunA(AMAXDOCA(''))",
'Loki_AMINDOCA': "LoKi.Particles.PFunA(AMINDOCA(''))",
'Loki_DOCACHI2MAX': 'DOCACHI2MAX',
'Loki_VCHI2NDOF': 'VFASPF(VCHI2/VDOF)',
'Loki_VX': 'VFASPF(VX)',
'Loki_VY': 'VFASPF(VY)',
'Loki_VZ': 'VFASPF(VZ)',
'Loki_SUMPT': 'SUMTREE(PT, ISBASIC)',
'Loki_BPVLTIME': "BPVLTIME()",
}
# Template DecayTreeTuple
t = DecayTreeTuple(name)
# Providing str will throw an exception, so wrap it in a list
try:
t.Inputs = inputs
except ValueError:
t.Inputs = [inputs]
t.Decay = decay
# Merge the mother and daughter dictionaries
t.addBranches(
dict(mothers.items() + intermediate.items() + daughters.items()))
# Tools for all branches
t.ToolList = tools
# Verbose reconstruction information
t.addTupleTool('TupleToolANNPID').ANNPIDTunes = ["MC15TuneV1"]
# t.addTupleTool('TupleToolRecoStats')
# MC truth information
if mc:
if has_turbo_inputs(t):
print 'Adding MC truth information for Turbo'
from TeslaTools import TeslaTruthUtils
relations = TeslaTruthUtils.getRelLoc("")
print 'relations = {}'.format(relations)
toollist = ['MCTupleToolPrompt']
rels = [relations]
MCTruth = TupleToolMCTruth()
#MCTruth.OutputLevel = 1
MCTruth = t.addTupleTool('TupleToolMCTruth')
MCTruth.ToolList = toollist
MCTruth.addTool(DaVinciSmartAssociator)
MCTruth.DaVinciSmartAssociator.RedoNeutral = False
MCTruth.DaVinciSmartAssociator.addTool(P2MCPFromProtoP)
MCTruth.DaVinciSmartAssociator.P2MCPFromProtoP.Locations = rels
MCTruth.addTool(MCMatchObjP2MCRelator)
MCTruth.MCMatchObjP2MCRelator.RelTableLocations = rels
MCTruth.DaVinciSmartAssociator.addTool(BackgroundCategory)
MCTruth.DaVinciSmartAssociator.BackgroundCategory.addTool(
P2MCPFromProtoP)
MCTruth.DaVinciSmartAssociator.BackgroundCategory.vetoNeutralRedo = True
MCTruth.DaVinciSmartAssociator.BackgroundCategory.P2MCPFromProtoP.Locations = rels
bkgcat = t.addTupleTool('TupleToolMCBackgroundInfo')
bkgcat.addTool(BackgroundCategory)
bkgcat.OutputLevel = 10
bkgcat.BackgroundCategory.vetoNeutralRedo = True
bkgcat.BackgroundCategory.addTool(P2MCPFromProtoP)
bkgcat.BackgroundCategory.P2MCPFromProtoP.Locations = rels
t.OutputLevel = 10
else:
print 'Adding MC truth information'
t.addTupleTool('TupleToolMCTruth')
t.addTupleTool('TupleToolMCBackgroundInfo')
# Extra information from LoKi
hybrid_tt = t.addTupleTool('LoKi::Hybrid::TupleTool/basicLoKiTT')
hybrid_tt.Variables = basic_loki_vars
hybrid_tt.Preambulo = ['from LoKiTracks.decorators import TrIDC']
# Add mother-specific varaibles to each mother branch
for mother in mothers:
branch = getattr(t, mother)
branch.addTupleTool('LoKi::Hybrid::TupleTool/{0}LoKiTT'.format(
mother)).Variables = mother_loki_vars
# For some unknown reason this doesn't work with Turbo candidates, so
# the information for them has to be added to every branch
DictTuple = branch.addTupleTool(LoKi__Hybrid__Dict2Tuple,
name="DTFTuple")
DictTuple.addTool(DTFDict, name="DTF")
DictTuple.Source = "LoKi::Hybrid::DTFDict/DTF"
DictTuple.NumVar = 6 * (len(mothers) + len(intermediate) +
len(daughters))
# configure the DecayTreeFitter in the usual way
DictTuple.DTF.constrainToOriginVertex = True
DictTuple.DTF.daughtersToConstrain = ['D0']
DictTuple.DTF.addTool(LoKi__Hybrid__DictOfFunctors, name="dict")
DictTuple.DTF.Source = "LoKi::Hybrid::DictOfFunctors/dict"
DictTuple.DTF.dict.Variables = {
"DTFDict_{}_PT".format(mother): "PT",
"DTFDict_{}_ETA".format(mother): "ETA",
"DTFDict_{}_PHI".format(mother): "PHI",
"DTFDict_{}_P".format(mother): "P",
"DTFDict_{}_M".format(mother): "M",
}
for part, decay in intermediate.items() + daughters.items():
DictTuple.DTF.dict.Variables["DTFDict_{}_PT".format(
part)] = "CHILD(PT,'{}')".format(decay)
DictTuple.DTF.dict.Variables["DTFDict_{}_ETA".format(
part)] = "CHILD(ETA,'{}')".format(decay)
DictTuple.DTF.dict.Variables["DTFDict_{}_PHI".format(
part)] = "CHILD(PHI,'{}')".format(decay)
DictTuple.DTF.dict.Variables["DTFDict_{}_P".format(
part)] = "CHILD(P,'{}')".format(decay)
DictTuple.DTF.dict.Variables["DTFDict_{}_M".format(
part)] = "CHILD(M,'{}')".format(decay)
# Add intermediate-specific varaibles to each mother branch
mom_int = mother_loki_vars.copy()
mom_int.update(intermediate_loki_vars)
for mother in intermediate:
branch = getattr(t, mother)
branch.addTupleTool('LoKi::Hybrid::TupleTool/{0}LoKiTT'.format(
mother)).Variables = mom_int
# For some unknown reason this doesn't work with Turbo candidates, so
# the information for them has to be added to every branch
for daughter in daughters:
branch = getattr(t, daughter)
branch.addTupleTool('LoKi::Hybrid::TupleTool/{0}LoKiTT'.format(
daughter)).Variables = daughter_loki_vars
return t
