diff --git a/Phys/Tesla/python/Tesla/Configuration.py b/Phys/Tesla/python/Tesla/Configuration.py
index 88ff5c2c2569c92ca6720015c9269128abffe2e1..aab72c52516424522018004cde10f95f2b0cf2be 100644
--- a/Phys/Tesla/python/Tesla/Configuration.py
+++ b/Phys/Tesla/python/Tesla/Configuration.py
@@ -21,6 +21,8 @@ from Configurables import (
DecodeRawEvent,
DstConf,
EventSelector,
+ Gaudi__DataCopy as DataCopy,
+ Gaudi__DataLink as DataLink,
GaudiSequencer,
HltPackedDataDecoder,
HltRoutingBitsFilter,
@@ -68,6 +70,36 @@ from LHCbKernel.Configuration import *
from RawEventCompat.Configuration import ReverseDict as RawEventLocationsToBanks
+def _strip_root(root, locs):
+ """Return list of paths `loc` stripped of the `root` prefix.
+
+ Examples
+ --------
+
+ >>> _strip_root('/Event/Turbo', ['/Event/Turbo/Foo'])
+ 'Foo'
+ >>> _strip_root('/Event', ['/Event/Turbo/Foo'])
+ 'Turbo/Foo'
+ >>> # Path is already relative
+ >>> _strip_root('/Event', ['Turbo/Foo'])
+ 'Turbo/Foo'
+ >>> # Complains if the prefix doesn't match the root
+ >>> _strip_root('/Event/Ultra', ['/Event/Turbo/Foo'])
+ AssertionError
+ """
+ root = root.rstrip('/')
+ ret = []
+ for l in locs:
+ # Only need to modify paths that are already absolute
+ if l.startswith('/'):
+ # Strip off the root the prefixes the string
+ l = l.replace(root + '/', '')
+ assert not l.startswith('/'), \
+ 'TES path still prefixed: {0}'.format(l)
+ ret.append(l)
+ return ret
+
+
class Tesla(LHCbConfigurableUser):
__used_configurables__ = [ LHCbApp, LumiAlgsConf, RawEventJuggler, DecodeRawEvent, RawEventFormatConf, DstConf, RecombineRawEvent, PackParticlesAndVertices, TrackAssociator, ChargedPP2MC, TrackSys, TurboConf]
@@ -172,6 +204,7 @@ class Tesla(LHCbConfigurableUser):
writerName = "DstWriter"
teslaSeq = GaudiSequencer("TeslaSequence")
base = "Turbo/"
+ neutral_pp2mc_loc = "Relations/Turbo/NeutralPP2MC"
def _safeSet(self,conf,param):
@@ -211,7 +244,7 @@ class Tesla(LHCbConfigurableUser):
SequencerTimerTool().OutputLevel = WARNING
def _configureTrackTruth(self,assocpp,trackLoc) :
- assoctr = TrackAssociator("TurboAssocTr"+trackLoc)
+ assoctr = TrackAssociator("TurboAssocTr"+trackLoc.replace("/", ""))
assoctr.OutputLevel = self.getProp('OutputLevel')
assoctr.TracksInContainer = trackLoc
assocpp.TrackLocations += [ trackLoc ]
@@ -222,7 +255,7 @@ class Tesla(LHCbConfigurableUser):
assocdigits = CaloDigit2MCLinks2Table("TurboDigitAssoc")
return
- def _configureClustersAndProtosTruth(self,digits,clusters,protos) :
+ def _configureClustersAndProtosTruth(self,digits,clusters,protos,protoTabLoc):
retSeq = GaudiSequencer("NeutralTruth")
clusterTabLoc = self.base + "Relations/CaloClusters"
@@ -232,11 +265,6 @@ class Tesla(LHCbConfigurableUser):
assoccluster.Output = clusterTabLoc
assoccluster.Clusters+=clusters
- # When filtering MC, the relations table cloners will copy the tables
- # to /Event/Turbo for us. Otherwise we create them there directly
- protoTabLoc = "Relations/Turbo/NeutralPP2MC"
- if not self.getProp("FilterMC"):
- protoTabLoc = os.path.join(self.base, protoTabLoc)
assocneutral = NeutralPP2MC("TurboNeutralPP2MC")
assocneutral.InputData += protos
assocneutral.OutputLevel = self.getProp('OutputLevel')
@@ -244,7 +272,7 @@ class Tesla(LHCbConfigurableUser):
assocneutral.MCCaloTable = clusterTabLoc
retSeq.Members += [assoccluster,assocneutral]
- return protoTabLoc, retSeq
+ return retSeq
def _unpackMC(self):
DataOnDemandSvc().NodeMap['/Event/MC'] = 'DataObject'
@@ -267,10 +295,8 @@ class Tesla(LHCbConfigurableUser):
microDST algorithms, using the relations tables Tesla makes to find the
MC particles that have been associated to the reconstruction.
"""
- if not self.getProp('FilterMC'):
- return
-
- output_prefix = self.base.replace('/', '')
+ output_prefix = self.base.rstrip('/')
+ output_level = self.getProp('OutputLevel')
# Algorithm to clone the existing relations tables and the MC particles
# and vertices these tables point to from their original location to
@@ -281,6 +307,7 @@ class Tesla(LHCbConfigurableUser):
# Don't use the assumed copy of the input ProtoParticle objects, as
# Tesla doesn't need to copy them (they're already under /Event/Turbo)
copy_pp2mcp.UseOriginalFrom = True
+ copy_pp2mcp.OutputLevel = output_level
# Algorithm to clone all MC particles and vertices that are associated
# to the simulated signal process (using LHCb::MCParticle::fromSignal)
@@ -288,6 +315,7 @@ class Tesla(LHCbConfigurableUser):
copy_signal_mcp.OutputPrefix = output_prefix
# Don't copy the associated reconstruction, as Tesla already saves it
copy_signal_mcp.SaveAssociatedRecoInfo = False
+ copy_signal_mcp.OutputLevel = output_level
algorithms = [copy_pp2mcp, copy_signal_mcp]
seq = GaudiSequencer('TurboMCFiltering', Members=algorithms)
@@ -494,7 +522,10 @@ class Tesla(LHCbConfigurableUser):
# Configure
self._configureDigitsTruth()
- protoneutral, retSeq = self._configureClustersAndProtosTruth(outputDigiLoc,neutralClustersTot,neutralProtosTot)
+ protoneutral = self.neutral_pp2mc_loc
+ if not self.getProp('FilterMC'):
+ protoneutral = os.path.join(tesROOT, protoneutral)
+ retSeq = self._configureClustersAndProtosTruth(outputDigiLoc,neutralClustersTot,neutralProtosTot,protoneutral)
NeutralProtoSeq.Members+=[retSeq]
# Add standard Turbo locations if not packing
@@ -591,6 +622,113 @@ class Tesla(LHCbConfigurableUser):
# Add the output sequence
TeslaReportAlgoSeq.Members += [TeslaOutputStreamsSequence]
+ def _configureTruthMatching(self, name, packing):
+ output_level = self.getProp('OutputLevel')
+
+ # Locations of the objects we want to truth-match
+ track_locs = [packing.outputs['Hlt2LongTracks'],
+ packing.outputs['Hlt2DownstreamTracks']]
+ proto_locs = [packing.outputs['Hlt2LongProtos'],
+ packing.outputs['Hlt2DownstreamProtos']]
+ cluster_locs = [packing.outputs['Hlt2CaloClusters']]
+ neutral_locs = [packing.outputs['Hlt2NeutralProtos']]
+
+ assocpp = ChargedPP2MC("TurboProtoAssocPP")
+ # Configure Track -> MCParticle relations table maker
+ trackTruthSeq = GaudiSequencer('TurboTrackTruthSequencer')
+ trackTruthSeq.Members = [self._configureTrackTruth(assocpp, loc)
+ for loc in track_locs]
+
+ # Configure ProtoParticle -> MCParticle relations table maker
+ assocpp.OutputLevel = output_level
+ assocpp.VetoEmpty = True
+ assocpp.InputData += _strip_root('/Event', proto_locs)
+
+ assocDigits = CaloDigit2MCLinks2Table("TurboDigitAssoc")
+ # The digits relations table maker will try to find the linker table
+ # for digits at `Raw/{det}/Digits` at `Link/Raw/{det}/Digits`. Our
+ # digits are at `Turbo/Raw/{det}/Digits`, but we can't remake a linker
+ # table at `Link/Turbo/Raw/{det}/Digits because the information needed
+ # to make one is lost after Boole.
+ # Instead, exploit the fact that the digits under `Turbo/` are a subset
+ # of the originals, and just symlink the original linker table to the
+ # location expected for the Turbo digits
+ assocDigits.RespectInputDigitLocation = False
+ digit_locs = _strip_root('/Event', assocDigits.getDefaultProperty('Inputs'))
+ turbo_digit_locs = [os.path.join(self.base, l) for l in digit_locs]
+ linkingSeq = GaudiSequencer('TurboLinkTableLinkers')
+ for digit_loc in digit_locs:
+ link_loc = os.path.join('Link', digit_loc)
+ turbo_link_loc = os.path.join('Link', self.base, digit_loc)
+ name = '{0}Linker'.format(link_loc.replace('/', ''))
+ dl = DataLink(name, What=link_loc, Target=turbo_link_loc)
+ linkingSeq.Members.append(dl)
+ # DataLinks don't create the ancestor TES structure, so do it
+ # manually
+ path = ''
+ for node in turbo_link_loc.split(os.path.sep)[:-1]:
+ path = os.path.join(path, node)
+ DataOnDemandSvc().NodeMap[path] = 'DataObject'
+
+ # Configure CaloDigit -> MCParticle relations table maker
+ assocDigits.OutputLevel = output_level
+ # Can use a magic string here as this table is only temporary
+ assocDigits.Output = "Relations/CaloDigits"
+ assocDigits.Inputs = turbo_digit_locs
+
+ # Configure CaloCluster -> MCParticle and neutral ProtoParticle ->
+ # MCParticle relations table makers
+ neutral_rels_loc = self.neutral_pp2mc_loc
+ assocClustersNeutrals = self._configureClustersAndProtosTruth(
+ assocDigits.Output,
+ cluster_locs,
+ neutral_locs,
+ neutral_rels_loc
+ )
+
+ chargedProtoSeq = GaudiSequencer("ChargedTruthSequencer")
+ chargedProtoSeq.Members = [trackTruthSeq, assocpp]
+ neutralProtoSeq = GaudiSequencer("NeutralTruthSequencer")
+ neutralProtoSeq.Members = [linkingSeq, assocDigits, assocClustersNeutrals]
+ truthSeq = GaudiSequencer("TurboTruthSequencer")
+ truthSeq.Members = [chargedProtoSeq, neutralProtoSeq]
+
+ # We have now created the relations tables under /Event/Relations,
+ # and want them under /Event/Turbo/Relations. We have two strategies:
+ # 1. Use the CopyProtoParticle2MCRelations algorithm, which will copy
+ # the tables *and* the MC particles they reference to under
+ # /Event/Turbo, updating the copied tables to point to the copied MC
+ # particles; or
+ # 2. Use Gaudi::DataCopy to copy the tables verbatim, so that they
+ # still refer to MC objects in /Event/MC.
+ # The first case we call 'filtering', as in principle the original MC
+ # objects can now be deleted because we then only depend on those in
+ # /Event/Turbo/MC. The second case we choose to do when not filtering
+ # so that the paths to the final relations tables are the same as those
+ # in the first case.
+ relationsLocations = [os.path.join('Relations', path)
+ for path in assocpp.InputData]
+ relationsLocations.append(neutral_rels_loc)
+ if self.getProp('FilterMC'):
+ filterMCSeq = self._filterMCParticlesSequence(relationsLocations)
+ truthSeq.Members += [filterMCSeq]
+ else:
+ base = self.base.rstrip('/')
+ truthSeq.Members.append(
+ GaudiSequencer('CopyRelationsTables', Members=[
+ DataCopy('Copy{0}'.format(loc.replace('/', '')),
+ What=loc,
+ Target=os.path.join(base, loc),
+ NeverFail=False,
+ OutputLevel=output_level)
+ for loc in relationsLocations
+ if self.base in loc
+ ], IgnoreFilterPassed=True)
+ )
+
+ return truthSeq
+
+
def _configureOutputStream(self, stream, lines_dict):
'''
The lines dictionary should have the following form:
@@ -830,7 +968,7 @@ class Tesla(LHCbConfigurableUser):
)]
# Kill any links the output file might have had to the input file
- if online:
+ if online and not simulation:
address_killer = [AddressKillerAlg()]
else:
address_killer = []
@@ -869,6 +1007,9 @@ class Tesla(LHCbConfigurableUser):
pack = self.getProp('Pack')
write_fsr = self.getProp('WriteFSR')
simulation = self.getProp('Simulation')
+ filter_mc = self.getProp('FilterMC')
+ if filter_mc:
+ assert simulation, 'Expected Simulation = True as FilterMC = True'
stream_seq = GaudiSequencer(namer('TeslaStreamSequence'))
@@ -901,6 +1042,10 @@ class Tesla(LHCbConfigurableUser):
]
))
+ if simulation:
+ self._unpackMC()
+ stream_seq.Members.append(self._configureTruthMatching(name, packing))
+
# No need to clone if the output prefix is empty (everything stays
# under /Event/Turbo)
if output_prefix:
@@ -1007,6 +1152,26 @@ class Tesla(LHCbConfigurableUser):
)
packers.append(psandvs_packer)
+ # Pack the filtered MC particles and vertices
+ if filter_mc:
+ mcp_packer = PackMCParticle(
+ 'TurboPackMCParticle',
+ AlwaysCreateOutput=True,
+ DeleteInput=False,
+ RootInTES=turbo_base
+ )
+ mcv_packer = PackMCVertex(
+ 'TurboPackMCVertex',
+ AlwaysCreateOutput=True,
+ DeleteInput=False,
+ RootInTES=turbo_base
+ )
+
+ packers.append(mcp_packer)
+ packers.append(mcv_packer)
+
+ optional_output_locations += [os.path.join(turbo_base, 'pSim#*')]
+
for packer in packers:
packer.OutputLevel = min(self.getProp('OutputLevel'),
self.getProp('PackerOutputLevel'))
@@ -1023,6 +1188,12 @@ class Tesla(LHCbConfigurableUser):
os.path.join(turbo_base, 'pRec#*'),
os.path.join(turbo_base, 'Hlt2/pRec#*')
]
+
+ # Need to save the *unpacked* relations tables when we aren't
+ # streaming because we don't run PackParticlesAndVertices in that
+ # case
+ if simulation and not output_prefix:
+ optional_output_locations += [os.path.join(turbo_base, 'Relations#*')]
else:
# Save everything under the stream prefix
optional_output_locations += [
@@ -1038,7 +1209,7 @@ class Tesla(LHCbConfigurableUser):
else:
fname = self.getProp('outputFile')
- if online:
+ if online and not simulation:
writer = OutputStream(namer(self.writerName))
writer.AcceptAlgs += ['LumiSeq', 'PhysFilter']
# In online mode we perform the raw event juggling (otherwise
@@ -1048,8 +1219,10 @@ class Tesla(LHCbConfigurableUser):
# In offline mode, e.g. after Brunel, propagate everything from the
# input file to the output
writer = InputCopyStream(namer(self.writerName))
+
writer.ItemList = required_output_locations
writer.OptItemList = optional_output_locations
+
# Keep the 2016 behaviour by not writing out anything if the
# sel reports are missing
writer.RequireAlgs = [self._selReportsCheck(), stream_seq]
@@ -1145,9 +1318,10 @@ class Tesla(LHCbConfigurableUser):
ApplicationMgr().AppName="Tesla, utilising DaVinci"
#
- if self.getProp('Mode') is "Online":
+ if self.getProp('Mode') == "Online":
self.setProp('WriteFSR',True)
- self._configureLumi()
+ if not self.getProp('Simulation'):
+ self._configureLumi()
else:
DecodeRawEvent().DataOnDemand=True
RecombineRawEvent(Version=self.getProp('SplitRawEventInput'))
@@ -1158,6 +1332,10 @@ class Tesla(LHCbConfigurableUser):
# /Event/Turbo, else it will be packed
TurboConf().setProp("RootInTES", "/Event")
+ # The MC logic requires the DataOnDemandSvc to be enabled
+ if self.getProp('Simulation'):
+ self._configureDataOnDemand()
+
if self.getProp('DataType') == '2017' and not self.getProp('CandidatesFromSelReports'):
# Unpack the DstData raw bank
TurboConf().setProp("RunPackedDataDecoder", True)