Functions
	tla_chains (inputFlags, log=None)
	TrigTLAMonConfig (inputFlags, tdt)

Variables
	parser = argparse.ArgumentParser()
	nargs
	default
	action
	help
	type
	int
	args = parser.parse_args()
	flags = initConfigFlags()
	MaxEvents
	Files
	isMC
	HISTFileName
	triggerMenuSetup
	triggerConfig
	cfg = MainServicesCfg(flags)
	tdt = cfg.getPrimaryAndMerge(TrigDecisionToolCfg(flags))
	parentName
list	pfChains = [trig[2:] for trig in tla_chains(flags) if 'pf_ftf' in trig]
	sequenceName
	trigTLAMonitorAcc = TrigTLAMonConfig(flags,tdt)
	withDetails

Detailed Description

@file TrigTLAMonitorAlgorithm.py
@author E. Nagy
@author K. Krizka
@date 2022-06-14
@brief Example trigger python configuration for the Run III AthenaMonitoring package, based on the example by C Burton and P Onyisi

Function Documentation

◆ tla_chains()

python.TrigTLAMonitorAlgorithm.tla_chains	(		inputFlags,
			log = None )

Read in the TLA trigger chain names as submitted to the MonGroups

Definition at line 12 of file TrigTLAMonitorAlgorithm.py.

def tla_chains(inputFlags,log=None):
    '''
    Read in the TLA trigger chain names as submitted to the MonGroups 
    '''
    tla_triglist = []
    # Trigger list from monitoring groups: signatures = TLAMon to be agreed w/ MonGroups management
    from TrigConfigSvc.TriggerConfigAccess import getHLTMonitoringAccess
    moniAccess=getHLTMonitoringAccess(inputFlags)
    TLAChainsE=moniAccess.monitoredChains(signatures="tlaMon",monLevels=["t0"])
    if log is not None:
        log.info (" ==> tla_chainlist t0: %s", TLAChainsE)
    for chain in TLAChainsE:
        chain = "E_"+chain
        tla_triglist.append(chain)
    TLAChainsS=moniAccess.monitoredChains(signatures="tlaMon",monLevels=["shifter"])
    if log is not None:
        log.info (" ==> tla_chainlist shifter:  %s", TLAChainsS)
    for chain in TLAChainsS:
        chain = "S_"+chain
        tla_triglist.append(chain)
    if log is not None:
        log.info (" ==> tla_triglist:  %s", tla_triglist)
    return tla_triglist
 
 

◆ TrigTLAMonConfig()

python.TrigTLAMonitorAlgorithm.TrigTLAMonConfig	(		inputFlags,
			tdt )

Function to configures some algorithms in the monitoring system.

Definition at line 37 of file TrigTLAMonitorAlgorithm.py.

def TrigTLAMonConfig(inputFlags, tdt):
    '''Function to configures some algorithms in the monitoring system.'''
 
    from AthenaCommon.Logging import logging
    log = logging.getLogger( 'TrigTLAMonitorAlgorithm.py' )
 
    
 
    # The following class will make a sequence, configure algorithms, and link
    # them to GenericMonitoringTools
    from AthenaMonitoring import AthMonitorCfgHelper
    helper = AthMonitorCfgHelper(inputFlags,'TrigTLAAthMonitorCfg')
 
    
 
    from AthenaConfiguration.ComponentFactory import CompFactory
    trigTLAMonAlg = helper.addAlgorithm(CompFactory.TrigTLAMonitorAlgorithm,'TrigTLAMonAlg')
 
    
    trigTLAMonAlg.TriggerChain = ''
    trigTLAMonAlg.TriggerDecisionTool = tdt
 
    
    tla_triglist=tla_chains(inputFlags,log=None)
 
    # Add a generic monitoring tool (a "group" in old language). The returned 
    # object here is the standard GenericMonitoringTool.
    TLAMonGroup = helper.addGroup(trigTLAMonAlg,'TrigTLAMonitor','HLT/TLAMon/')
 
    
    from TrigTLAMonitoring.TrigTLAMonitorHistograms import (
        histdefs_eventinfo, histdefs_particle, histdefs_tracks, histdefs_dR, histdefs_jetcalibscales, histdefs_jetvariables
    )
    # Configure histograms
    #NB! The histograms defined here must match the ones in the cxx file exactly
    histdefs_global=[]
    histdefs_global+=histdefs_eventinfo('eventInfo')
    histdefs=[]
    histdefs+=histdefs_particle('jet'  ,'jet')
    histdefs+=histdefs_particle('pfjet','particle-flow jet')
    histdefs+=histdefs_particle('ph'   ,'photon')
    histdefs+=histdefs_particle('muon' ,'muon')
    histdefs+=histdefs_tracks  ('trk'  ,'track')
    histdefs+=histdefs_dR      ('jet0'  ,'jet1'  , 'leading jet'   ,'subleading jet'   )
    histdefs+=histdefs_dR      ('pfjet0','pfjet1', 'leading pf jet','subleading pf jet')
    histdefs+=histdefs_dR      ('jet0'  ,'ph0'   , 'leading jet'   ,'leading photon'   )
    histdefs+=histdefs_dR      ('pfjet0','ph0'   , 'leading pf jet','leading photon'   )
    histdefs+=histdefs_jetcalibscales('jet'  ,'jet')
    histdefs+=histdefs_jetcalibscales('pfjet','particle-flow jet', True)
    histdefs+=histdefs_jetvariables('jet', 'jet')
    histdefs+=histdefs_jetvariables('pfjet', 'particle-flow jet', True)
 
    
    AllChains = []
    for chain in tla_triglist :
        AllChains.append(chain[2:])
 
        for histdef in histdefs:
            HistName = histdef['name'] + '_' + chain[2:]
 
            xlabel=histdef.get('xlabel',histdef['name'  ])
            if 'xunit' in histdef:
                xlabel+=f' [{histdef["xunit"]}'
            ylabel=histdef.get('ylabel',histdef['ylabel'])
 
            if chain[0:1] == "E" :
                TLAMonGroup.defineHistogram(HistName, title=f'Distribution of {histdef["name"]};{xlabel};{ylabel}',
                                            path='Expert/' +chain[2:],xbins=histdef['xbins'],xmin=histdef['xmin'],xmax=histdef['xmax'])
            if chain[0:1] == "S" :
                TLAMonGroup.defineHistogram(HistName, title=f'Distribution of {histdef["name"]};{xlabel};{ylabel}',
                                            path='Shifter/'+chain[2:],xbins=histdef['xbins'],xmin=histdef['xmin'],xmax=histdef['xmax'])
 
    # global histograms added here
    for histdef in histdefs_global:
        HistName = histdef['name']
        xlabel=histdef.get('xlabel',histdef['name'  ])
        if 'xunit' in histdef:
            xlabel+=f' [{histdef["xunit"]}'
        ylabel=histdef.get('ylabel',histdef['ylabel'])
        TLAMonGroup.defineHistogram(HistName, title=f'Distribution of {histdef["name"]};{xlabel};{ylabel}',
                                        path='Expert/EventInfo',xbins=histdef['xbins'],xmin=histdef['xmin'],xmax=histdef['xmax'])
 
    log.info (" ==> In TrigTLAMonitorAlgorithm.py: AllChains list:  %s", AllChains)
    trigTLAMonAlg.AllChains = AllChains
 
    
    return helper.result()
 
 