def configure_for_line(self, decaydesc, inputloc, linename, version,
simulation,
toolList = ["TupleToolPropertime",
"TupleToolKinematic",
"TupleToolGeometry",
"TupleToolEventInfo",
"TupleToolPrimaries",
"TupleToolPid",
"TupleToolANNPID",
"TupleToolTrackInfo",
"TupleToolRecoStats",],
mcToolList = ['TupleToolMCTruth',
'TupleToolMCBackgroundInfo',
'MCTupleToolPrompt'],
L0List = [],
HLT1List = [],
HLT2List = [],
strippingList = []) :
self.Decay = decaydesc.to_string(carets = True)
self.Inputs = [inputloc]
isTrigger = is_trigger(version)
if isTrigger :
self.WriteP2PVRelations = False
# Not sure if this is necessary since RootInTES will be set for turbo data.
#self.InputPrimaryVertices = '/Event/Turbo/Primary'
if not linename in HLT2List :
HLT2List.append(linename)
else :
if not linename in strippingList :
strippingList.append(linename)
self.addBranches(decaydesc.branches())
headBranch = getattr(self, decaydesc.get_alias())
self.configure_tools(toolList = toolList,
mcToolList = (mcToolList if simulation else []),
L0List = L0List,
HLT1List = HLT1List,
HLT2List = HLT2List,
strippingList = strippingList,
headBranch = headBranch,
isTrigger = isTrigger)
if simulation :
lokituple = headBranch.addTupleTool('LoKi::Hybrid::TupleTool')
lokituple.Preambulo = ['from LoKiPhysMC.decorators import *',
'from LoKiPhysMC.functions import mcMatch']
if isTrigger :
# Need this for 2015
#relations = TeslaTruthUtils.getRelLoc(inputloc.split('/')[-2] + '/')
# This for 2015 ...
relations = TeslaTruthUtils.getRelLoc('')
mcmatch = 'switch(mcMatch({0!r}, {1!r}), 1, 0)'.format(decaydesc.to_string(carets = False,
arrow = '==>'),
relations)
else :
mcmatch = 'switch(mcMatch({0!r}), 1, 0)'.format(decaydesc.to_string(carets = False,
arrow = '==>'))
lokituple.Variables = {'mcMatch' : mcmatch}
def configure_for_line(self, decaydesc, inputloc, linename, version,
simulation,
toolList = ["TupleToolPropertime",
"TupleToolKinematic",
"TupleToolGeometry",
"TupleToolEventInfo",
"TupleToolPrimaries",
"TupleToolPid",
"TupleToolANNPID",
"TupleToolTrackInfo",
"TupleToolRecoStats",],
mcToolList = ['TupleToolMCTruth',
'TupleToolMCBackgroundInfo',
'MCTupleToolPrompt'],
L0List = [],
HLT1List = [],
HLT2List = [],
strippingList = []) :
self.Decay = decaydesc.to_string(carets = True)
self.Inputs = [inputloc]
isTrigger = is_trigger(version)
if isTrigger :
self.WriteP2PVRelations = False
# Not sure if this is necessary since RootInTES will be set for turbo data.
#self.InputPrimaryVertices = '/Event/Turbo/Primary'
if not linename in HLT2List :
HLT2List.append(linename)
else :
if not linename in strippingList :
strippingList.append(linename)
self.addBranches(decaydesc.branches())
headBranch = getattr(self, decaydesc.get_alias())
self.configure_tools(toolList = toolList,
mcToolList = mcToolList if simulation else [],
L0List = L0List,
HLT1List = HLT1List,
HLT2List = HLT2List,
strippingList = strippingList,
headBranch = headBranch,
isTrigger = isTrigger)
if simulation :
lokituple = headBranch.addTupleTool('LoKi::Hybrid::TupleTool')
lokituple.Preambulo = ['from LoKiPhysMC.decorators import *',
'from LoKiPhysMC.functions import mcMatch']
if isTrigger :
relations = TeslaTruthUtils.getRelLoc('')
mcmatch = 'switch(mcMatch({0!r}, {1!r}), 1, 0)'.format(decaydesc.to_string(carets = False,
arrow = '==>'),
relations)
else :
mcmatch = 'switch(mcMatch({0!r}), 1, 0)'.format(decaydesc.to_string(carets = False,
arrow = '==>'))
lokituple.Variables = {'mcMatch' : mcmatch}
def execute(simulation=True,
turbo=True,
decay_descriptor="J/psi(1S) -> mu- mu+"):
# Configure all the unpacking, algorithms, tags and input files
appConf = ApplicationMgr()
appConf.ExtSvc+= ['ToolSvc', 'DataOnDemandSvc', LoKiSvc()]
ConfigTarFileAccessSvc().File = 'config.tar'
dv = DaVinci()
dv.DataType = "2012"
lhcbApp = LHCbApp()
lhcbApp.Simulation = simulation
CondDB().Upgrade = False
dtt = DecayTreeTuple("Early2015")
if turbo:
tesla_prefix = "Hlt2DiMuonJPsi"
dtt.Inputs = ["/Event/"+tesla_prefix+"/Particles"]
dtt.InputPrimaryVertices = "/Event/"+tesla_prefix+"/Primary"
dtt.WriteP2PVRelations = False
else:
LHCbApp().DDDBtag = "dddb-20140729"
polarity = "u"
LHCbApp().CondDBtag = "sim-20140730-vc-m%s100"%polarity
muons = AutomaticData(Location="Phys/StdAllLooseMuons/Particles")
jpsi = CombineParticles('MyJPsi')
jpsi.DecayDescriptors = [decay_descriptor]
jpsi.CombinationCut = "(AM < 7100.0 *GeV)"
jpsi.DaughtersCuts = {"": "ALL", "mu+": "ALL", "mu-": "ALL"}
jpsi.MotherCut = "(VFASPF(VCHI2/VDOF) < 999999.0)"
code = """
('J/psi(1S)' == ID) &
in_range(2.990*GeV, M, 3.210*GeV) &
DECTREE('%s') &
CHILDCUT(1, HASMUON & ISMUON) &
CHILDCUT(2, HASMUON & ISMUON) &
(MINTREE('mu+' == ABSID, PT) > 700*MeV) &
(MAXTREE(ISBASIC & HASTRACK, TRCHI2DOF) < 5) &
(MINTREE(ISBASIC & HASTRACK, CLONEDIST) > 5000) &
(VFASPF(VPCHI2) > 0.5/100) &
(abs(BPV(VZ)) < 0.5*meter) &
(BPV(vrho2) < (10*mm)**2)
"""%(decay_descriptor)
# similar to the HLT2 line
code = """
(ADMASS('J/psi(1S)')< 120*MeV) &
DECTREE('%s') &
(PT>0*MeV) &
(MAXTREE('mu-'==ABSID,TRCHI2DOF) < 4) &
(MINTREE('mu-'==ABSID,PT)> 0*MeV) &
(VFASPF(VCHI2PDOF)< 25)
"""%(decay_descriptor)
filter_jpsi = FilterDesktop("MyFilterJPsi",
Code=code,
Preambulo=["vrho2 = VX**2 + VY**2"],
ReFitPVs=True,
#IgnoreP2PVFromInputLocations=True,
#WriteP2PVRelations=True
)
jpsi_sel = Selection("SelMyJPsi", Algorithm=jpsi, RequiredSelections=[muons])
filter_jpsi_sel = Selection("SelFilterMyJPsi",
Algorithm=filter_jpsi,
RequiredSelections=[jpsi_sel])
jpsi_seq = SelectionSequence("SeqMyJPsi", TopSelection=filter_jpsi_sel)
dtt.Inputs = [jpsi_seq.outputLocation()]
# Overwriting default list of TupleTools
dtt.ToolList = ["TupleToolKinematic",
"TupleToolPid",
"TupleToolEventInfo",
"TupleToolMCBackgroundInfo",
"TupleToolMCTruth",
#"MCTupleToolHierarchy",
#"MCTupleToolPID",
"TupleToolGeometry",
"TupleToolTISTOS",
# with turbo this crashes
#"TupleToolTrackInfo",
"TupleToolTrigger",
]
tlist = ["L0HadronDecision", "L0MuonDecision",
"L0DiMuonDecision", "L0ElectronDecision",
"L0PhotonDecision",
"Hlt1DiMuonHighMassDecision", "Hlt1DiMuonLowMassDecision",
"Hlt1TrackMuonDecision", "Hlt1TrackAllL0Decision",
"Hlt2DiMuonJPsiDecision", "Hlt2SingleMuonDecision",
]
dtt.addTool(TupleToolTrigger, name="TupleToolTrigger")
dtt.addTool(TupleToolTISTOS, name="TupleToolTISTOS")
# Get trigger info
dtt.TupleToolTrigger.Verbose = True
dtt.TupleToolTrigger.TriggerList = tlist
dtt.TupleToolTISTOS.Verbose = True
dtt.TupleToolTISTOS.TriggerList = tlist
from Configurables import TupleToolMCTruth, MCTupleToolHierarchy
dtt.addTool(TupleToolMCBackgroundInfo,
name="TupleToolMCBackgroundInfo")
dtt.TupleToolMCBackgroundInfo.Verbose = True
dtt.addTool(MCTupleToolHierarchy,
name="MCTupleToolHierarchy")
dtt.MCTupleToolHierarchy.Verbose = True
dtt.addTool(TupleToolMCTruth,
name="TupleToolMCTruth")
dtt.TupleToolMCTruth.Verbose = True
if turbo:
assoc_seq = TeslaTruthUtils.associateSequence(tesla_prefix, False)
ChargedPP2MC(tesla_prefix+"ProtoAssocPP").OutputLevel = 1
assoc_seq.Members.insert(0, PatLHCbID2MCParticle())
from Configurables import MuonCoord2MCParticleLink
muon_coords = MuonCoord2MCParticleLink("TeslaMuonCoordLinker")
assoc_seq.Members.insert(1, muon_coords)
TrackAssociator("TeslaAssocTr").DecideUsingMuons = True
relations = TeslaTruthUtils.getRelLoc(tesla_prefix)
else:
relations = "Relations/Rec/ProtoP/Charged"
TeslaTruthUtils.makeTruth(dtt,
relations,
["MCTupleToolKinematic",
"MCTupleToolHierarchy",
"MCTupleToolPID",
]
)
dtt.Decay = mark(2, mark(3, decay_descriptor)) #"J/psi(1S) -> ^mu- ^mu+"
dtt.addBranches({"X": "^(%s)"%(decay_descriptor),
"muplus": mark(3, decay_descriptor),#"J/psi(1S) -> mu- ^mu+",
"muminus": mark(2, decay_descriptor),#"J/psi(1S) -> ^mu- mu+",
})
x_preamble = ["DZ = VFASPF(VZ) - BPV(VZ)",
]
x_vars = {"ETA": "ETA",
"Y": "Y",
"PHI": "PHI",
"VPCHI2": "VFASPF(VPCHI2)",
"DELTAZ": "DZ",
# DZ * M / PZ / c with c in units of mm/s
# XXX should this be the PDG mass or measured mass?
#"TZ": "DZ*M / PZ / 299792458000.0", #seconds
"TZ": "DZ*3096.916 / PZ/299792458000.0*(10**12)", #ps
"minpt": "MINTREE('mu+' == ABSID, PT)",
"minclonedist": "MINTREE(ISBASIC & HASTRACK, CLONEDIST)",
"maxtrchi2dof": "MAXTREE(ISBASIC & HASTRACK, TRCHI2DOF)",
}
muon_vars = {"ETA": "ETA",
"Y": "Y",
"PHI": "PHI",
"CHARGE": "Q",
"CLONEDIST": "CLONEDIST",
"TRCHI2DOF": "TRCHI2DOF",
}
loki_X = dtt.X.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_X")
loki_X.Variables = x_vars
loki_X.Preambulo = x_preamble
loki_mup = dtt.muplus.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_MuPlus")
loki_mup.Variables = muon_vars
#dtt.muplus.addTupleTool("TupleToolGeometry")
loki_mum = dtt.muminus.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_MuMinus")
loki_mum.Variables = muon_vars
#dtt.muminus.addTupleTool("TupleToolGeometry")
dv.TupleFile = "DVNtuples.root"
if turbo:
dv.UserAlgorithms = [assoc_seq, dtt]
else:
assocpp = ChargedPP2MC("TimsChargedPP2MC")
assocpp.OutputLevel = 1
dv.UserAlgorithms = [jpsi_seq.sequence(), assocpp, dtt]
def configure_tools(self, toolList = ["TupleToolPropertime",
"TupleToolKinematic",
"TupleToolGeometry",
"TupleToolEventInfo",
"TupleToolPrimaries",
"TupleToolPid",
"TupleToolANNPID",
"TupleToolTrackInfo",
"TupleToolRecoStats",],
mcToolList = ['TupleToolMCTruth',
'TupleToolMCBackgroundInfo',
'MCTupleToolPrompt'],
L0List = [],
HLT1List = [],
HLT2List = [],
strippingList = [],
headBranch = None,
isTrigger = False) :
for trigList in L0List, HLT1List, HLT2List, strippingList :
for i, trig in enumerate(trigList) :
if trig[-8:] != 'Decision' :
trigList[i] += 'Decision'
for tool in toolList :
self.addTupleTool(tool)
if mcToolList :
ttmc = self.addTupleTool('TupleToolMCTruth')
for tool in mcToolList :
if tool == 'TupleToolMCTruth' :
continue
if tool.find('MCTupleTool') == 0 :
ttmc.addTupleTool(tool)
else :
self.addTupleTool(tool)
if isTrigger :
# Is this right? Or should I pass it the list of sub-tools of TupleToolMCTruth?
relations = TeslaTruthUtils.getRelLoc('')
TeslaTruthUtils.makeTruth(self,
[relations],
mcToolList)
if strippingList :
ttstrip = self.addTupleTool('TupleToolStripping')
ttstrip.TriggerList = strippingList
ttstrip.VerboseStripping = True
# This doesn't currently work. There doesn't seem to be an easy way
# to TISTOS stripping lines currently, which is infuriating. Surely everyone
# needs to do this for MC studies? It might be possible to do it using
# TESTisTos in a Bender algorithm, or INTES functor.
#ttstriptistos = headBranch.addTupleTool('TupleToolTISTOS/tistos_stripping')
#ttstriptistos.TriggerTisTosName = 'TESTisTos'
#ttstriptistos.TriggerList = [os.path.join(rootInTES, inputLocation)]
if L0List or HLT1List or HLT2List :
if headBranch == None :
headBranch = self
ttrig = headBranch.addTupleTool('TupleToolTISTOS')
# TupleToolTISTOS can't do stripping this way either.
ttrig.TriggerList = L0List + HLT1List + HLT2List
ttrig.Verbose = True
ttrig.VerboseL0 = True
ttrig.VerboseHlt1 = True
ttrig.VerboseHlt2 = True
#tlist = ["L0HadronDecision","L0MuonDecision","L0DiMuonDecision","L0ElectronDecision","L0PhotonDecision","Hlt1DiMuonHighMassDecision","Hlt1DiMuonLowMassDecision","Hlt1TrackMuonDecision","Hlt1TrackAllL0Decision","Hlt2DiMuonJPsi","Hlt2IncPhiDecision","Hlt2Topo4BodySimpleDecision","Hlt2Topo3BodySimpleDecision","Hlt2Topo3BodyBBDTDecision","Hlt2Topo2BodySimpleDecision","Hlt2Topo2BodyBBDTDecision","Hlt2Topo4BodyBBDTDecision","Hlt2TopoMu4BodyBBDTDecision","Hlt2IncPhiSidebandsDecision","Hlt2B2HHDecision","Hlt2DiPhiDecision"]
tlist = ["Hlt2DiMuonJPsi"]
tuple.Decay = "J/psi(1S) -> ^mu+ ^mu-"
#tuple.Decay = "[D*(2010)+ -> ^(K*(892)0 -> ^K+ ^pi-) ^pi+]CC"
tuple.addTool(TupleToolTrigger, name="TupleToolTrigger")
tuple.addTool(TupleToolTISTOS, name="TupleToolTISTOS")
# Get trigger info
tuple.TupleToolTrigger.Verbose = True
tuple.TupleToolTrigger.TriggerList = tlist
tuple.TupleToolTISTOS.Verbose = True
tuple.TupleToolTISTOS.TriggerList = tlist
from TeslaTools import TeslaTruthUtils
seq = TeslaTruthUtils.associateSequence("Tesla", False)
relations = TeslaTruthUtils.getRelLoc("Tesla")
TeslaTruthUtils.makeTruth(
tuple, relations,
["MCTupleToolKinematic", "MCTupleToolHierarchy", "MCTupleToolPID"])
tuple2 = MCDecayTreeTuple("MCTeslaTuple")
tuple2.Inputs = ['/Event/Tesla/Particles']
tuple2.Decay = tuple.Decay
from Configurables import DataOnDemandSvc, L0SelReportsMaker, L0DecReportsMaker
DataOnDemandSvc().AlgMap["HltLikeL0/DecReports"] = L0DecReportsMaker()
DataOnDemandSvc().AlgMap["HltLikeL0/SelReports"] = L0SelReportsMaker()
from Configurables import L0Conf
L0Conf().FullL0MuonDecoding = True
L0Conf().EnableL0DecodingOnDemand = True
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
def configure_tools(self, toolList = ["TupleToolPropertime",
"TupleToolKinematic",
"TupleToolGeometry",
"TupleToolEventInfo",
"TupleToolPrimaries",
"TupleToolPid",
"TupleToolANNPID",
"TupleToolTrackInfo",
"TupleToolRecoStats",],
mcToolList = ['TupleToolMCTruth',
'TupleToolMCBackgroundInfo',
'MCTupleToolPrompt'],
L0List = [],
HLT1List = [],
HLT2List = [],
strippingList = [],
headBranch = None,
isTrigger = False) :
for trigList in L0List, HLT1List, HLT2List, strippingList :
for i, trig in enumerate(trigList) :
if trig[-8:] != 'Decision' :
trigList[i] += 'Decision'
for tool in toolList :
self.addTupleTool(tool)
if mcToolList :
ttmc = self.addTupleTool('TupleToolMCTruth')
for tool in mcToolList :
if tool == 'TupleToolMCTruth' :
continue
if tool.find('MCTupleTool') == 0 :
ttmc.addTupleTool(tool)
else :
self.addTupleTool(tool)
if isTrigger and mcToolList :
# Is this right? Or should I pass it the list of sub-tools of TupleToolMCTruth?
hlt2line = self.Inputs[0].split('/')[-2]
# Need this for 2015
#relations = TeslaTruthUtils.getRelLoc(hlt2line + '/')
# This for 2016 ...
relations = TeslaTruthUtils.getRelLoc('')
TeslaTruthUtils.makeTruth(self,
[relations],
ttmc.ToolList)
if strippingList :
ttstrip = self.addTupleTool('TupleToolStripping')
ttstrip.TriggerList = strippingList
ttstrip.VerboseStripping = True
# This doesn't currently work. There doesn't seem to be an easy way
# to TISTOS stripping lines currently, which is infuriating. Surely everyone
# needs to do this for MC studies? It might be possible to do it using
# TESTisTos in a Bender algorithm, or INTES functor.
#ttstriptistos = headBranch.addTupleTool('TupleToolTISTOS/tistos_stripping')
#ttstriptistos.TriggerTisTosName = 'TESTisTos'
#ttstriptistos.TriggerList = [os.path.join(rootInTES, inputLocation)]
if L0List or HLT1List or HLT2List :
if headBranch == None :
headBranch = self
ttrig = headBranch.addTupleTool('TupleToolTISTOS')
# TupleToolTISTOS can't do stripping this way either.
ttrig.TriggerList = L0List + HLT1List + HLT2List
ttrig.Verbose = True
ttrig.VerboseL0 = True
ttrig.VerboseHlt1 = True
ttrig.VerboseHlt2 = True
#tlist = ["L0HadronDecision","L0MuonDecision","L0DiMuonDecision","L0ElectronDecision","L0PhotonDecision","Hlt1DiMuonHighMassDecision","Hlt1DiMuonLowMassDecision","Hlt1TrackMuonDecision","Hlt1TrackAllL0Decision","Hlt2DiMuonJPsi","Hlt2IncPhiDecision","Hlt2Topo4BodySimpleDecision","Hlt2Topo3BodySimpleDecision","Hlt2Topo3BodyBBDTDecision","Hlt2Topo2BodySimpleDecision","Hlt2Topo2BodyBBDTDecision","Hlt2Topo4BodyBBDTDecision","Hlt2TopoMu4BodyBBDTDecision","Hlt2IncPhiSidebandsDecision","Hlt2B2HHDecision","Hlt2DiPhiDecision"]
tlist = ["Hlt2DiMuonJPsi"]
tuple.Decay = "J/psi(1S) -> ^mu+ ^mu-"
#tuple.Decay = "[D*(2010)+ -> ^(K*(892)0 -> ^K+ ^pi-) ^pi+]CC"
tuple.addTool(TupleToolTrigger, name="TupleToolTrigger")
tuple.addTool(TupleToolTISTOS, name="TupleToolTISTOS")
# Get trigger info
tuple.TupleToolTrigger.Verbose = True
tuple.TupleToolTrigger.TriggerList = tlist
tuple.TupleToolTISTOS.Verbose = True
tuple.TupleToolTISTOS.TriggerList = tlist
from TeslaTools import TeslaTruthUtils
seq = TeslaTruthUtils.associateSequence("Tesla",False)
relations = TeslaTruthUtils.getRelLoc("Tesla")
TeslaTruthUtils.makeTruth(tuple, relations, [ "MCTupleToolKinematic" , "MCTupleToolHierarchy" , "MCTupleToolPID" ])
tuple2 = MCDecayTreeTuple("MCTeslaTuple")
tuple2.Inputs = ['/Event/Tesla/Particles']
tuple2.Decay = tuple.Decay
from Configurables import DataOnDemandSvc, L0SelReportsMaker, L0DecReportsMaker
DataOnDemandSvc().AlgMap["HltLikeL0/DecReports"] = L0DecReportsMaker()
DataOnDemandSvc().AlgMap["HltLikeL0/SelReports"] = L0SelReportsMaker()
from Configurables import L0Conf
L0Conf().FullL0MuonDecoding = True
L0Conf().EnableL0DecodingOnDemand = True
L0Conf().EnsureKnownTCK=False
def execute(simulation=True,
turbo=True,
decay_descriptor="J/psi(1S) -> mu- mu+"):
# Configure all the unpacking, algorithms, tags and input files
appConf = ApplicationMgr()
appConf.ExtSvc += ['ToolSvc', 'DataOnDemandSvc', LoKiSvc()]
ConfigTarFileAccessSvc().File = 'config.tar'
dv = DaVinci()
dv.DataType = "2012"
lhcbApp = LHCbApp()
lhcbApp.Simulation = simulation
CondDB().Upgrade = False
dtt = DecayTreeTuple("Early2015")
if turbo:
tesla_prefix = "Hlt2DiMuonJPsi"
dtt.Inputs = ["/Event/" + tesla_prefix + "/Particles"]
dtt.InputPrimaryVertices = "/Event/" + tesla_prefix + "/Primary"
dtt.WriteP2PVRelations = False
else:
LHCbApp().DDDBtag = "dddb-20140729"
polarity = "u"
LHCbApp().CondDBtag = "sim-20140730-vc-m%s100" % polarity
muons = AutomaticData(Location="Phys/StdAllLooseMuons/Particles")
jpsi = CombineParticles('MyJPsi')
jpsi.DecayDescriptors = [decay_descriptor]
jpsi.CombinationCut = "(AM < 7100.0 *GeV)"
jpsi.DaughtersCuts = {"": "ALL", "mu+": "ALL", "mu-": "ALL"}
jpsi.MotherCut = "(VFASPF(VCHI2/VDOF) < 999999.0)"
code = """
('J/psi(1S)' == ID) &
in_range(2.990*GeV, M, 3.210*GeV) &
DECTREE('%s') &
CHILDCUT(1, HASMUON & ISMUON) &
CHILDCUT(2, HASMUON & ISMUON) &
(MINTREE('mu+' == ABSID, PT) > 700*MeV) &
(MAXTREE(ISBASIC & HASTRACK, TRCHI2DOF) < 5) &
(MINTREE(ISBASIC & HASTRACK, CLONEDIST) > 5000) &
(VFASPF(VPCHI2) > 0.5/100) &
(abs(BPV(VZ)) < 0.5*meter) &
(BPV(vrho2) < (10*mm)**2)
""" % (decay_descriptor)
# similar to the HLT2 line
code = """
(ADMASS('J/psi(1S)')< 120*MeV) &
DECTREE('%s') &
(PT>0*MeV) &
(MAXTREE('mu-'==ABSID,TRCHI2DOF) < 4) &
(MINTREE('mu-'==ABSID,PT)> 0*MeV) &
(VFASPF(VCHI2PDOF)< 25)
""" % (decay_descriptor)
filter_jpsi = FilterDesktop(
"MyFilterJPsi",
Code=code,
Preambulo=["vrho2 = VX**2 + VY**2"],
ReFitPVs=True,
#IgnoreP2PVFromInputLocations=True,
#WriteP2PVRelations=True
)
jpsi_sel = Selection("SelMyJPsi",
Algorithm=jpsi,
RequiredSelections=[muons])
filter_jpsi_sel = Selection("SelFilterMyJPsi",
Algorithm=filter_jpsi,
RequiredSelections=[jpsi_sel])
jpsi_seq = SelectionSequence("SeqMyJPsi", TopSelection=filter_jpsi_sel)
dtt.Inputs = [jpsi_seq.outputLocation()]
# Overwriting default list of TupleTools
dtt.ToolList = [
"TupleToolKinematic",
"TupleToolPid",
"TupleToolEventInfo",
"TupleToolMCBackgroundInfo",
"TupleToolMCTruth",
#"MCTupleToolHierarchy",
#"MCTupleToolPID",
"TupleToolGeometry",
"TupleToolTISTOS",
# with turbo this crashes
#"TupleToolTrackInfo",
"TupleToolTrigger",
]
tlist = [
"L0HadronDecision",
"L0MuonDecision",
"L0DiMuonDecision",
"L0ElectronDecision",
"L0PhotonDecision",
"Hlt1DiMuonHighMassDecision",
"Hlt1DiMuonLowMassDecision",
"Hlt1TrackMuonDecision",
"Hlt1TrackAllL0Decision",
"Hlt2DiMuonJPsiDecision",
"Hlt2SingleMuonDecision",
]
dtt.addTool(TupleToolTrigger, name="TupleToolTrigger")
dtt.addTool(TupleToolTISTOS, name="TupleToolTISTOS")
# Get trigger info
dtt.TupleToolTrigger.Verbose = True
dtt.TupleToolTrigger.TriggerList = tlist
dtt.TupleToolTISTOS.Verbose = True
dtt.TupleToolTISTOS.TriggerList = tlist
from Configurables import TupleToolMCTruth, MCTupleToolHierarchy
dtt.addTool(TupleToolMCBackgroundInfo, name="TupleToolMCBackgroundInfo")
dtt.TupleToolMCBackgroundInfo.Verbose = True
dtt.addTool(MCTupleToolHierarchy, name="MCTupleToolHierarchy")
dtt.MCTupleToolHierarchy.Verbose = True
dtt.addTool(TupleToolMCTruth, name="TupleToolMCTruth")
dtt.TupleToolMCTruth.Verbose = True
if turbo:
assoc_seq = TeslaTruthUtils.associateSequence(tesla_prefix, False)
ChargedPP2MC(tesla_prefix + "ProtoAssocPP").OutputLevel = 1
assoc_seq.Members.insert(0, PatLHCbID2MCParticle())
from Configurables import MuonCoord2MCParticleLink
muon_coords = MuonCoord2MCParticleLink("TeslaMuonCoordLinker")
assoc_seq.Members.insert(1, muon_coords)
TrackAssociator("TeslaAssocTr").DecideUsingMuons = True
relations = TeslaTruthUtils.getRelLoc(tesla_prefix)
else:
relations = "Relations/Rec/ProtoP/Charged"
TeslaTruthUtils.makeTruth(dtt, relations, [
"MCTupleToolKinematic",
"MCTupleToolHierarchy",
"MCTupleToolPID",
])
dtt.Decay = mark(2, mark(3, decay_descriptor)) #"J/psi(1S) -> ^mu- ^mu+"
dtt.addBranches({
"X": "^(%s)" % (decay_descriptor),
"muplus": mark(3, decay_descriptor), #"J/psi(1S) -> mu- ^mu+",
"muminus": mark(2, decay_descriptor), #"J/psi(1S) -> ^mu- mu+",
})
x_preamble = [
"DZ = VFASPF(VZ) - BPV(VZ)",
]
x_vars = {
"ETA": "ETA",
"Y": "Y",
"PHI": "PHI",
"VPCHI2": "VFASPF(VPCHI2)",
"DELTAZ": "DZ",
# DZ * M / PZ / c with c in units of mm/s
# XXX should this be the PDG mass or measured mass?
#"TZ": "DZ*M / PZ / 299792458000.0", #seconds
"TZ": "DZ*3096.916 / PZ/299792458000.0*(10**12)", #ps
"minpt": "MINTREE('mu+' == ABSID, PT)",
"minclonedist": "MINTREE(ISBASIC & HASTRACK, CLONEDIST)",
"maxtrchi2dof": "MAXTREE(ISBASIC & HASTRACK, TRCHI2DOF)",
}
muon_vars = {
"ETA": "ETA",
"Y": "Y",
"PHI": "PHI",
"CHARGE": "Q",
"CLONEDIST": "CLONEDIST",
"TRCHI2DOF": "TRCHI2DOF",
}
loki_X = dtt.X.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_X")
loki_X.Variables = x_vars
loki_X.Preambulo = x_preamble
loki_mup = dtt.muplus.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_MuPlus")
loki_mup.Variables = muon_vars
#dtt.muplus.addTupleTool("TupleToolGeometry")
loki_mum = dtt.muminus.addTupleTool("LoKi::Hybrid::TupleTool/LoKi_MuMinus")
loki_mum.Variables = muon_vars
#dtt.muminus.addTupleTool("TupleToolGeometry")
dv.TupleFile = "DVNtuples.root"
if turbo:
dv.UserAlgorithms = [assoc_seq, dtt]
else:
assocpp = ChargedPP2MC("TimsChargedPP2MC")
assocpp.OutputLevel = 1
dv.UserAlgorithms = [jpsi_seq.sequence(), assocpp, dtt]
