def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','miniTree')
inputTreeName = kwargs.pop('inputTreeName','MiniTree')
inputLumiName = kwargs.pop('inputTreeName','LumiTree')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
if hasProgress:
self.pbar = kwargs.pop('progressbar',ProgressBar(widgets=['{0}: '.format(outputTreeName),' ',SimpleProgress(),' events ',Percentage(),' ',Bar(),' ',ETA()]))
# input files
self.fileNames = []
if isinstance(inputFileNames, basestring): # inputFiles is a file name
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
# input tchain
self.tchain = ROOT.TChain('{0}/{1}'.format(inputTreeDirectory,inputTreeName))
tchainLumi = ROOT.TChain('{0}/{1}'.format(inputTreeDirectory,inputLumiName))
for fName in self.fileNames:
if fName.startswith('/store'): fName = 'root://cmsxrootd.hep.wisc.edu//{0}'.format(fName)
self.tchain.Add(fName)
tchainLumi.Add(fName)
# get the lumi info
self.numLumis = tchainLumi.GetEntries()
self.numEvents = 0
self.summedWeights = 0
for entry in xrange(self.numLumis):
tchainLumi.GetEntry(entry)
self.numEvents += tchainLumi.nevents
self.summedWeights += tchainLumi.summedWeights
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
# other input files
self.pileupWeights = PileupWeights()
self.leptonScales = LeptonScales()
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
# pileup
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[0], 'pileupWeight', 'F')
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[1], 'pileupWeightUp', 'F')
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[2], 'pileupWeightDown', 'F')
def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','')
inputTreeName = kwargs.pop('inputTreeName','Events')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
self.shift = kwargs.pop('shift','')
self.events = []
self.outputTreeName = outputTreeName
# preselection
if not hasattr(self,'preselection'): self.preselection = '1'
# input files
self.fileNames = []
if os.path.isfile('PSet.py'): # grab input files from crab pset
import PSet
self.fileNames = list(PSet.process.source.fileNames)
elif isinstance(inputFileNames, basestring): # inputFiles is a file name
if inputFileNames.startswith('/store'): # xrootd access
self.fileNames += [inputFileNames]
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
if not self.fileNames:
logging.error('No files found')
raise ValueError
# test for hdfs
#self.hasHDFS = os.path.exists('/hdfs/store/user')
self.hasHDFS = False
# input tchain
self.treename = inputTreeName
self.totalEntries = 0
self.numLumis = 0
self.numEvents = 0
self.summedWeights = 0
self.summedWeightsLHEScale = [0]*9
logging.info('Getting Lumi information')
#self.skims = {}
#self.tfiles = []
for f,fName in enumerate(self.fileNames):
if fName.startswith('/store/user'):
fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
elif fName.startswith('/store'):
fName = '{0}/{1}'.format('root://cmsxrootd.fnal.gov/',fName)
tfile = ROOT.TFile.Open(fName)
tree = tfile.Get(self.treename)
self.totalEntries += tree.GetEntries()
if not hasattr(self,'version'):
tree.GetEntry(1)
if hasattr(tree,'provenance'):
ver = tree.provenance[0].split('_')
self.version = ''.join([ver[1],ver[2],'X'])
else:
self.version = getCMSSWVersion()
lumitree = tfile.Get('LuminosityBlocks')
for entry in lumitree:
self.numLumis += 1
runtree = tfile.Get('Runs')
for entry in runtree:
if hasattr(runtree,'genEventCount'):
self.numEvents += runtree.genEventCount
self.summedWeights += runtree.genEventSumw
for i in range(9):
if len(runtree.LHEScaleSumw)>i: self.summedWeightsLHEScale[i] += runtree.LHEScaleSumw[i]
#self.tfiles += [tfile]
tfile.Close('R')
logging.info('Analysis is running with version {0}'.format(self.version))
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
if not len(self.fileNames): raise Exception
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
# pileup
self.tree.add(lambda cands: self.event.nOtherPV()+1, 'numVertices', 'I')
self.tree.add(lambda cands: self.event.fixedGridRhoFastjetAll(), 'rho', 'F')
# gen
self.tree.add(lambda cands: 0 if self.event.isData() else self.event.Pileup_nPU(), 'numTrueVertices', 'I')
self.tree.add(lambda cands: self.event.isData(), 'isData', 'I')
self.tree.add(lambda cands: 0 if self.event.isData() else self.event.genWeight(), 'genWeight', 'F')
# scale shifts
weightMap = {
0: {'muR':1.0, 'muF':1.0},
1: {'muR':1.0, 'muF':2.0},
2: {'muR':1.0, 'muF':0.5},
3: {'muR':2.0, 'muF':1.0},
4: {'muR':2.0, 'muF':2.0},
5: {'muR':2.0, 'muF':0.5},
6: {'muR':0.5, 'muF':1.0},
7: {'muR':0.5, 'muF':2.0},
8: {'muR':0.5, 'muF':0.5},
}
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[0] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>0 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[0]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[1] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>1 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[1]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[2] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>2 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[2]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[3] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>3 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[3]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[4] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>4 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[4]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[5] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>5 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[5]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[6] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>6 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[6]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[7] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>7 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[7]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[8] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>8 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[8]), 'F')
class AnalysisBase(object):
'''
Analysis Tree
'''
def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','')
inputTreeName = kwargs.pop('inputTreeName','Events')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
self.shift = kwargs.pop('shift','')
self.events = []
self.outputTreeName = outputTreeName
# preselection
if not hasattr(self,'preselection'): self.preselection = '1'
# input files
self.fileNames = []
if os.path.isfile('PSet.py'): # grab input files from crab pset
import PSet
self.fileNames = list(PSet.process.source.fileNames)
elif isinstance(inputFileNames, basestring): # inputFiles is a file name
if inputFileNames.startswith('/store'): # xrootd access
self.fileNames += [inputFileNames]
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
if not self.fileNames:
logging.error('No files found')
raise ValueError
# test for hdfs
#self.hasHDFS = os.path.exists('/hdfs/store/user')
self.hasHDFS = False
# input tchain
self.treename = inputTreeName
self.totalEntries = 0
self.numLumis = 0
self.numEvents = 0
self.summedWeights = 0
self.summedWeightsLHEScale = [0]*9
logging.info('Getting Lumi information')
#self.skims = {}
#self.tfiles = []
for f,fName in enumerate(self.fileNames):
if fName.startswith('/store/user'):
fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
elif fName.startswith('/store'):
fName = '{0}/{1}'.format('root://cmsxrootd.fnal.gov/',fName)
tfile = ROOT.TFile.Open(fName)
tree = tfile.Get(self.treename)
self.totalEntries += tree.GetEntries()
if not hasattr(self,'version'):
tree.GetEntry(1)
if hasattr(tree,'provenance'):
ver = tree.provenance[0].split('_')
self.version = ''.join([ver[1],ver[2],'X'])
else:
self.version = getCMSSWVersion()
lumitree = tfile.Get('LuminosityBlocks')
for entry in lumitree:
self.numLumis += 1
runtree = tfile.Get('Runs')
for entry in runtree:
if hasattr(runtree,'genEventCount'):
self.numEvents += runtree.genEventCount
self.summedWeights += runtree.genEventSumw
for i in range(9):
if len(runtree.LHEScaleSumw)>i: self.summedWeightsLHEScale[i] += runtree.LHEScaleSumw[i]
#self.tfiles += [tfile]
tfile.Close('R')
logging.info('Analysis is running with version {0}'.format(self.version))
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
if not len(self.fileNames): raise Exception
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
# pileup
self.tree.add(lambda cands: self.event.nOtherPV()+1, 'numVertices', 'I')
self.tree.add(lambda cands: self.event.fixedGridRhoFastjetAll(), 'rho', 'F')
# gen
self.tree.add(lambda cands: 0 if self.event.isData() else self.event.Pileup_nPU(), 'numTrueVertices', 'I')
self.tree.add(lambda cands: self.event.isData(), 'isData', 'I')
self.tree.add(lambda cands: 0 if self.event.isData() else self.event.genWeight(), 'genWeight', 'F')
# scale shifts
weightMap = {
0: {'muR':1.0, 'muF':1.0},
1: {'muR':1.0, 'muF':2.0},
2: {'muR':1.0, 'muF':0.5},
3: {'muR':2.0, 'muF':1.0},
4: {'muR':2.0, 'muF':2.0},
5: {'muR':2.0, 'muF':0.5},
6: {'muR':0.5, 'muF':1.0},
7: {'muR':0.5, 'muF':2.0},
8: {'muR':0.5, 'muF':0.5},
}
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[0] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>0 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[0]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[1] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>1 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[1]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[2] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>2 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[2]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[3] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>3 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[3]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[4] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>4 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[4]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[5] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>5 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[5]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[6] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>6 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[6]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[7] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>7 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[7]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.LHEScaleWeight()[8] if hasattr(self.event,'LHEScaleWeight') and len(self.event.LHEScaleWeight())>8 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[8]), 'F')
def __exit__(self, type, value, traceback):
self.finish()
def __del__(self):
self.finish()
def finish(self):
print ''
logging.info('Finishing')
logging.info('Writing {0} events'.format(self.eventsStored))
self.outfile.cd()
cutflowHist = ROOT.TH1D('summedWeights','summedWeights',1,0,1)
cutflowHist.SetBinContent(1,self.summedWeights)
self.outfile.Write()
self.outfile.Close()
def flush(self):
sys.stdout.flush()
sys.stderr.flush()
def get_event(self):
return '{run}:{lumi}:{event}'.format(run=self.event.run(),lumi=self.event.lumi(),event=self.event.event())
#############################
### primary analysis loop ###
#############################
def analyze(self):
'''
The primary analyzer loop.
'''
logging.info('Beginning Analysis')
start = time.time()
total = 0
for f, fName in enumerate(self.fileNames):
if fName.startswith('/store/user'):
fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
elif fName.startswith('/store'):
fName = '{0}/{1}'.format('root://cmsxrootd.fnal.gov/',fName)
logging.info('Processing file {0} of {1}: {2}'.format(f+1, len(self.fileNames), fName))
tfile = ROOT.TFile.Open(fName,'READ')
tree = tfile.Get(self.treename)
for row in tree:
total += 1
if total==2: start = time.time() # just ignore first event for timing
if total % 1000 == 1:
cur = time.time()
elapsed = cur-start
remaining = float(elapsed)/total * float(self.totalEntries) - float(elapsed)
mins, secs = divmod(int(remaining),60)
hours, mins = divmod(mins,60)
logging.info('{}: Processing event {}/{} ({} selected) - {}:{:02d}:{:02d} remaining'.format(self.outputTreeName,total,self.totalEntries,self.eventsStored,hours,mins,secs))
self.flush()
self.setupEvent(tree)
self.perRowAction()
tfile.Close('R')
def setupEvent(self,tree):
'''Setup the event objects'''
# load objects
self.event = Event(tree)
if self.event.isData(): self.shift = ''
if not self.event.isData(): self.gen = [GenParticle(tree,entry=i) for i in range(tree.nGenPart)]
self.electrons = [Electron(tree,entry=i,shift=self.shift) for i in range(tree.nElectron)]
self.muons = [Muon(tree,entry=i,shift=self.shift) for i in range(tree.nMuon)]
self.taus = [Tau(tree,entry=i,shift=self.shift) for i in range(tree.nTau)]
self.photons = [Photon(tree,entry=i,shift=self.shift) for i in range(tree.nPhoton)]
self.jets = [Jet(tree,entry=i,shift=self.shift) for i in range(tree.nJet)]
self.pfmet = Met(tree,shift=self.shift)
def perRowAction(self):
'''Per row action, can be overridden'''
goodToCheck = self.cutTree.evaluate(self.event)
if not goodToCheck: return
# select candidates
cands = self.selectCandidates()
cands['event'] = self.event
# store event?
goodToStore = self.cutTree.checkCands(cands)
if not goodToStore: return
self.tree.fill(cands)
self.eventsStored += 1
def selectCandidates(self):
'''
Select candidates
format should be:
candidates = {
"objectName" : ("collectionName", position),
...
}
'''
logging.warning("You must override selectCandidates.")
return {}
#################
### utilities ###
#################
def getCands(self,coll,func):
cands = []
for cand in coll:
if func(cand): cands += [cand]
return cands
def cleanCands(self,src,other,dr):
cleaned = []
for s in src:
keep = True
for o in other:
if deltaR(s.eta(),s.phi(),o.eta(),o.phi())<dr:
keep = False
break
if keep:
cleaned += [s]
return cleaned
def getCollectionString(self,cand):
if isinstance(cand,Electron): return 'e'
elif isinstance(cand,Muon): return 'm'
elif isinstance(cand,Tau): return 't'
elif isinstance(cand,Photon): return 'g'
elif isinstance(cand,Jet): return 'j'
else: return 'a'
def checkTrigger(self,*datasets,**triggerNames):
'''Check trigger using trigger map'''
isData = self.event.isData()>0.5
# reject triggers if they are in another dataset
# looks for the dataset name in the filename
# for MC it accepts any
reject = True if isData else False
for dataset in datasets:
# if we match to the dataset, start accepting triggers
if dataset in self.fileNames[0] and isData: reject = False
for trigger in triggerNames[dataset]:
var = 'HLT_{0}'.format(trigger)
passTrigger = getattr(self.event,var)()
if passTrigger>0.5:
# it passed the trigger
# in data: reject if it corresponds to a higher dataset
return False if reject else True
# dont check the rest of data
if dataset in self.fileNames[0] and isData: break
return False
def metFilter(self):
if not self.event.isData(): return True
return self.event.Flag_METFilters()
# legacy, keep in case we revert
filterList = [
'HBHENoiseFilter',
'HBHENoiseIsoFilter',
'globalTightHalo2016Filter',
'EcalDeadCellTriggerPrimitiveFilter',
'goodVertices',
'eeBadScFilter',
'noBadMuons',
'BadChargedCandidateFilter',
]
notFilterList = [
# Dont use, "noBadMuons" contains this
#'duplicateMuons',
#'badMuons',
]
for f in filterList:
if getattr(self.event,'Flag_{}'.format(f))()==0:
logging.info('Rejecting event {0}:{1}:{2} for {3}={4}'.format(self.event.run(), self.event.lumi(), self.event.event(), f, getattr(self.event,f)()))
self.report_failure('fails {}'.format(f))
return False
for f in notFilterList:
if getattr(self.event,'Flag_{}'.format(f))()>0:
logging.info('Rejecting event {0}:{1}:{2} for {3}={4}'.format(self.event.run(), self.event.lumi(), self.event.event(), f, getattr(self.event,f)()))
self.report_failure('fails {}'.format(f))
return False
return True
def report_failure(self,message):
if self.events:
event = self.get_event()
if event in self.events:
print event, message
##########################
### add object to tree ###
##########################
def addTriggers(self):
pass
def addCandVar(self,label,varLabel,var,rootType,permissive=False):
'''Add a variable for a cand'''
if permissive:
self.tree.add(lambda cands: getattr(cands[label],var)() if cands[label].has(var) else 0., '{0}_{1}'.format(label,varLabel), rootType)
else:
self.tree.add(lambda cands: getattr(cands[label],var)(), '{0}_{1}'.format(label,varLabel), rootType)
def addFlavorDependentCandVar(self,label,varLabel,varMap,rootType,default=0):
'''Add a variable for a cand based on flavor'''
self.tree.add(lambda cands: getattr(cands[label],varMap[cands[label].collName])() if cands[label].collName in varMap else default, '{0}_{1}'.format(label,varLabel), rootType)
def addMet(self,label):
'''Add Met variables'''
self.addCandVar(label,'pt','pt','F')
self.addCandVar(label,'phi','phi','F')
#self.addCandVar(label,'cov00','covXX','F')
#self.addCandVar(label,'cov01','covXY','F')
#self.addCandVar(label,'cov10','covXY','F')
#self.addCandVar(label,'cov11','covYY','F')
def addCandidate(self,label):
'''Add variables relevant for all objects'''
self.addCandVar(label,'pt','pt','F')
self.addCandVar(label,'eta','eta','F')
self.tree.add(lambda cands: abs(getattr(cands[label],'eta')()), '{}_abseta'.format(label), 'F')
self.addCandVar(label,'phi','phi','F')
self.addCandVar(label,'mass','mass','F')
def addJet(self,label):
'''Add variables relevant for jets'''
self.addCandidate(label)
self.addCandVar(label,'CSVv2','btagCSVV2','F')
self.addCandVar(label,'hadronFlavour','hadronFlavour','I')
def addLepton(self,label):
'''Add variables relevant for leptons'''
self.addCandidate(label)
self.addCandVar(label,'charge','charge','I')
self.addCandVar(label,'dz','dz','F')
self.addCandVar(label,'dxy','dxy','F')
def addDetailedMuon(self,label):
'''Add detailed variables'''
pass
def addDetailedTau(self,label):
'''Add detailed variables'''
pass
def addPhoton(self,label):
'''Add variables relevant for photons'''
self.addCandidate(label)
self.addCandVar(label,'r9','r9','F')
def genDeltaR(self,cand):
'''Get the gen level deltaR'''
if cand.genMatch()==0: return 0.
eta = cand.eta()
genEta = cand.genEta()
phi = cand.phi()
genPhi = cand.genPhi()
return deltaR(eta,phi,genEta,genPhi)
def genJetDeltaR(self,cand):
'''Get the gen level deltaR'''
if cand.genJetMatch()==0: return 0.
eta = cand.eta()
genEta = cand.genJetEta()
phi = cand.phi()
genPhi = cand.genJetPhi()
return deltaR(eta,phi,genEta,genPhi)
def addDiCandidate(self,label):
'''Add variables relevant for a two object candidate'''
self.addCandVar(label,'mass','M','F')
self.addCandVar(label,'M2','M2','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
self.addCandVar(label,'deltaR','deltaR','F')
self.addCandVar(label,'deltaEta','deltaEta','F')
self.addCandVar(label,'deltaPhi','deltaPhi','F')
def addDiJet(self,label):
'''Add variables relevant for a dijet candidate'''
self.addDiCandidate(label)
def addDiLepton(self,label):
'''Add variables relevant for a dilepton candidate'''
self.addDiCandidate(label)
def addLeptonMet(self,label):
'''Add variables related to a lepton + met'''
self.addCandVar(label,'mt','Mt','F')
self.addCandVar(label,'mt2','Mt2','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
self.addCandVar(label,'deltaPhi','deltaPhi','F')
def addComposite(self,label):
'''Add variables related to multi object variables'''
self.addCandVar(label,'mass','M','F')
self.addCandVar(label,'M2','M2','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
def addCompositeMet(self,label):
'''Add variables related to multi object variables'''
self.addCandVar(label,'mt','Mt','F')
self.addCandVar(label,'mt2','Mt2','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','miniTree')
inputTreeName = kwargs.pop('inputTreeName','MiniTree')
inputLumiName = kwargs.pop('inputTreeName','LumiTree')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
self.shift = kwargs.pop('shift','')
self.outputTreeName = outputTreeName
if hasProgress:
self.pbar = kwargs.pop('progressbar',ProgressBar(widgets=['{0}: '.format(outputTreeName),' ',SimpleProgress(),' events ',Percentage(),' ',Bar(),' ',ETA()]))
# preselection
if not hasattr(self,'preselection'): self.preselection = '1'
# input files
self.fileNames = []
if os.path.isfile('PSet.py'): # grab input files from crab pset
import PSet
self.fileNames = list(PSet.process.source.fileNames)
elif isinstance(inputFileNames, basestring): # inputFiles is a file name
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
# test for hdfs
#self.hasHDFS = os.path.exists('/hdfs/store/user')
self.hasHDFS = False
# input tchain
self.treename = '{0}/{1}'.format(inputTreeDirectory,inputTreeName)
luminame = '{0}/{1}'.format(inputTreeDirectory,inputLumiName)
#tchainLumi = ROOT.TChain(luminame)
self.totalEntries = 0
self.numLumis = 0
self.numEvents = 0
self.summedWeights = 0
logging.info('Getting Lumi information')
#self.skims = {}
for f,fName in enumerate(self.fileNames):
if fName.startswith('/store'): fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
tfile = ROOT.TFile.Open(fName)
tree = tfile.Get(self.treename)
#skimName = 'skim{0}'.format(f)
#tree.Draw('>>{0}'.format(skimName),self.preselection,'entrylist')
#skimlist = ROOT.gDirectory.Get(skimName)
#listEvents = skimlist.GetN()
#self.skims[f] = skimlist
#self.totalEntries += listEvents
self.totalEntries += tree.GetEntries()
if not hasattr(self,'version'):
tree.GetEntry(1)
if hasattr(tree,'provenance'):
ver = tree.provenance[0].split('_')
self.version = ''.join([ver[1],ver[2],'X'])
else:
self.version = getCMSSWVersion()
lumitree = tfile.Get(luminame)
for entry in lumitree:
self.numLumis += 1
self.numEvents += lumitree.nevents
self.summedWeights += lumitree.summedWeights
tfile.Close('R')
#tchainLumi.Add(fName)
# get the lumi info
#self.numLumis = tchainLumi.GetEntries()
#self.numEvents = 0
#self.summedWeights = 0
#for entry in xrange(self.numLumis):
# tchainLumi.GetEntry(entry)
# self.numEvents += tchainLumi.nevents
# self.summedWeights += tchainLumi.summedWeights
logging.info('Analysis is running with version {0}'.format(self.version))
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
if not len(self.fileNames): raise Exception
# other input files
self.pileupWeights = PileupWeights(self.version)
self.fakeRates = FakeRates(self.version)
self.leptonScales = LeptonScales(self.version)
self.triggerScales = TriggerScales(self.version)
self.triggerPrescales = TriggerPrescales(self.version)
self.zptGenWeight = ZptGenWeight(self.version)
self.zzGenWeight = ZZGenWeight(self.version)
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
dysamples = [
'DY1JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY2JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY3JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY4JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DYJetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
]
qqzzsamples = [
'ZZTo4L_13TeV_powheg_pythia8',
'ZZTo4L_13TeV-amcatnloFXFX-pythia8',
]
# pileup
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[0], 'pileupWeight', 'F')
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[1], 'pileupWeightUp', 'F')
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[2], 'pileupWeightDown', 'F')
self.tree.add(lambda cands: self.event.vertices_count(), 'numVertices', 'I')
self.tree.add(lambda cands: self.event.rho(), 'rho', 'F')
# gen
self.tree.add(lambda cands: self.event.nTrueVertices(), 'numTrueVertices', 'I')
self.tree.add(lambda cands: self.event.NUP(), 'NUP', 'I')
self.tree.add(lambda cands: self.event.isData(), 'isData', 'I')
self.tree.add(lambda cands: self.event.genWeight(), 'genWeight', 'F')
if any([x in fName for x in dysamples]):
self.tree.add(lambda cands: self.zptGenWeight.weight(self.gen), 'zPtWeight', 'F')
if any([x in fName for x in qqzzsamples]):
self.tree.add(lambda cands: self.zzGenWeight.weight(self.gen), 'qqZZkfactor', 'F')
self.tree.add(lambda cands: self.event.numGenJets(), 'numGenJets', 'I')
self.tree.add(lambda cands: self.event.genHT(), 'genHT', 'I')
# scale shifts
weightMap = {
0: {'muR':1.0, 'muF':1.0},
1: {'muR':1.0, 'muF':2.0},
2: {'muR':1.0, 'muF':0.5},
3: {'muR':2.0, 'muF':1.0},
4: {'muR':2.0, 'muF':2.0},
5: {'muR':2.0, 'muF':0.5},
6: {'muR':0.5, 'muF':1.0},
7: {'muR':0.5, 'muF':2.0},
8: {'muR':0.5, 'muF':0.5},
}
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[0] if len(self.event.genWeights())>0 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[0]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[1] if len(self.event.genWeights())>1 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[1]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[2] if len(self.event.genWeights())>2 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[2]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[3] if len(self.event.genWeights())>3 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[3]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[4] if len(self.event.genWeights())>4 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[4]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[5] if len(self.event.genWeights())>5 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[5]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[6] if len(self.event.genWeights())>6 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[6]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[7] if len(self.event.genWeights())>7 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[7]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[8] if len(self.event.genWeights())>8 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[8]), 'F')
class AnalysisBase(object):
'''
Analysis Tree
'''
def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','miniTree')
inputTreeName = kwargs.pop('inputTreeName','MiniTree')
inputLumiName = kwargs.pop('inputTreeName','LumiTree')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
self.shift = kwargs.pop('shift','')
self.outputTreeName = outputTreeName
if hasProgress:
self.pbar = kwargs.pop('progressbar',ProgressBar(widgets=['{0}: '.format(outputTreeName),' ',SimpleProgress(),' events ',Percentage(),' ',Bar(),' ',ETA()]))
# preselection
if not hasattr(self,'preselection'): self.preselection = '1'
# input files
self.fileNames = []
if os.path.isfile('PSet.py'): # grab input files from crab pset
import PSet
self.fileNames = list(PSet.process.source.fileNames)
elif isinstance(inputFileNames, basestring): # inputFiles is a file name
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
# test for hdfs
#self.hasHDFS = os.path.exists('/hdfs/store/user')
self.hasHDFS = False
# input tchain
self.treename = '{0}/{1}'.format(inputTreeDirectory,inputTreeName)
luminame = '{0}/{1}'.format(inputTreeDirectory,inputLumiName)
#tchainLumi = ROOT.TChain(luminame)
self.totalEntries = 0
self.numLumis = 0
self.numEvents = 0
self.summedWeights = 0
logging.info('Getting Lumi information')
#self.skims = {}
for f,fName in enumerate(self.fileNames):
if fName.startswith('/store'): fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
tfile = ROOT.TFile.Open(fName)
tree = tfile.Get(self.treename)
#skimName = 'skim{0}'.format(f)
#tree.Draw('>>{0}'.format(skimName),self.preselection,'entrylist')
#skimlist = ROOT.gDirectory.Get(skimName)
#listEvents = skimlist.GetN()
#self.skims[f] = skimlist
#self.totalEntries += listEvents
self.totalEntries += tree.GetEntries()
if not hasattr(self,'version'):
tree.GetEntry(1)
if hasattr(tree,'provenance'):
ver = tree.provenance[0].split('_')
self.version = ''.join([ver[1],ver[2],'X'])
else:
self.version = getCMSSWVersion()
lumitree = tfile.Get(luminame)
for entry in lumitree:
self.numLumis += 1
self.numEvents += lumitree.nevents
self.summedWeights += lumitree.summedWeights
tfile.Close('R')
#tchainLumi.Add(fName)
# get the lumi info
#self.numLumis = tchainLumi.GetEntries()
#self.numEvents = 0
#self.summedWeights = 0
#for entry in xrange(self.numLumis):
# tchainLumi.GetEntry(entry)
# self.numEvents += tchainLumi.nevents
# self.summedWeights += tchainLumi.summedWeights
logging.info('Analysis is running with version {0}'.format(self.version))
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
if not len(self.fileNames): raise Exception
# other input files
self.pileupWeights = PileupWeights(self.version)
self.fakeRates = FakeRates(self.version)
self.leptonScales = LeptonScales(self.version)
self.triggerScales = TriggerScales(self.version)
self.triggerPrescales = TriggerPrescales(self.version)
self.zptGenWeight = ZptGenWeight(self.version)
self.zzGenWeight = ZZGenWeight(self.version)
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
dysamples = [
'DY1JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY2JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY3JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DY4JetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
'DYJetsToLL_M-50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8',
]
qqzzsamples = [
'ZZTo4L_13TeV_powheg_pythia8',
'ZZTo4L_13TeV-amcatnloFXFX-pythia8',
]
# pileup
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[0], 'pileupWeight', 'F')
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[1], 'pileupWeightUp', 'F')
self.tree.add(lambda cands: self.pileupWeights.weight(self.event)[2], 'pileupWeightDown', 'F')
self.tree.add(lambda cands: self.event.vertices_count(), 'numVertices', 'I')
self.tree.add(lambda cands: self.event.rho(), 'rho', 'F')
# gen
self.tree.add(lambda cands: self.event.nTrueVertices(), 'numTrueVertices', 'I')
self.tree.add(lambda cands: self.event.NUP(), 'NUP', 'I')
self.tree.add(lambda cands: self.event.isData(), 'isData', 'I')
self.tree.add(lambda cands: self.event.genWeight(), 'genWeight', 'F')
if any([x in fName for x in dysamples]):
self.tree.add(lambda cands: self.zptGenWeight.weight(self.gen), 'zPtWeight', 'F')
if any([x in fName for x in qqzzsamples]):
self.tree.add(lambda cands: self.zzGenWeight.weight(self.gen), 'qqZZkfactor', 'F')
self.tree.add(lambda cands: self.event.numGenJets(), 'numGenJets', 'I')
self.tree.add(lambda cands: self.event.genHT(), 'genHT', 'I')
# scale shifts
weightMap = {
0: {'muR':1.0, 'muF':1.0},
1: {'muR':1.0, 'muF':2.0},
2: {'muR':1.0, 'muF':0.5},
3: {'muR':2.0, 'muF':1.0},
4: {'muR':2.0, 'muF':2.0},
5: {'muR':2.0, 'muF':0.5},
6: {'muR':0.5, 'muF':1.0},
7: {'muR':0.5, 'muF':2.0},
8: {'muR':0.5, 'muF':0.5},
}
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[0] if len(self.event.genWeights())>0 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[0]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[1] if len(self.event.genWeights())>1 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[1]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[2] if len(self.event.genWeights())>2 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[2]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[3] if len(self.event.genWeights())>3 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[3]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[4] if len(self.event.genWeights())>4 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[4]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[5] if len(self.event.genWeights())>5 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[5]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[6] if len(self.event.genWeights())>6 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[6]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[7] if len(self.event.genWeights())>7 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[7]), 'F')
self.tree.add(lambda cands: 0. if self.event.isData() else self.event.genWeights()[8] if len(self.event.genWeights())>8 else 0., 'genWeight_muR{muR:3.1f}_muF{muF:3.1f}'.format(**weightMap[8]), 'F')
def __exit__(self, type, value, traceback):
self.finish()
def __del__(self):
self.finish()
def finish(self):
print ''
logging.info('Finishing')
logging.info('Writing {0} events'.format(self.eventsStored))
self.outfile.cd()
cutflowHist = ROOT.TH1D('summedWeights','summedWeights',1,0,1)
cutflowHist.SetBinContent(1,self.summedWeights)
self.outfile.Write()
self.outfile.Close()
self.leptonScales.finish()
def flush(self):
sys.stdout.flush()
sys.stderr.flush()
#############################
### primary analysis loop ###
#############################
def analyze(self):
'''
The primary analyzer loop.
'''
logging.info('Beginning Analysis')
start = time.time()
new = start
old = start
if hasProgress:
self.pbar.maxval = self.totalEntries
self.pbar.start()
total = 0
for f, fName in enumerate(self.fileNames):
if fName.startswith('/store'): fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
tfile = ROOT.TFile.Open(fName,'READ')
tree = tfile.Get(self.treename)
#skimName = 'skim{0}'.format(f)
#tree.Draw('>>{0}'.format(skimName),self.preselection,'entrylist')
#skimlist = ROOT.gDirectory.Get(skimName)
#listEvents = skimlist.GetN()
#for r in xrange(listEvents):
for row in tree:
total += 1
#tree.GetEntry(skimlist.Next())
self.pbar.update(total)
self.setupEvent(tree)
self.perRowAction()
tfile.Close('R')
self.pbar.update(self.totalEntries)
else:
total = 0
for f, fName in enumerate(self.fileNames):
if fName.startswith('/store'): fName = '{0}/{1}'.format('/hdfs' if self.hasHDFS else 'root://cmsxrootd.hep.wisc.edu/',fName)
logging.info('Processing file {0} of {1}: {2}'.format(f+1, len(self.fileNames), fName))
tfile = ROOT.TFile.Open(fName,'READ')
tree = tfile.Get(self.treename)
#skimName = 'skim{0}'.format(f)
#tree.Draw('>>{0}'.format(skimName),self.preselection,'entrylist')
#skimlist = ROOT.gDirectory.Get(skimName)
#listEvents = skimlist.GetN()
#for r in xrange(listEvents):
for row in tree:
total += 1
if total==2: start = time.time() # just ignore first event for timing
#tree.GetEntry(skimlist.Next())
if total % 1000 == 1:
cur = time.time()
elapsed = cur-start
remaining = float(elapsed)/total * float(self.totalEntries) - float(elapsed)
mins, secs = divmod(int(remaining),60)
hours, mins = divmod(mins,60)
logging.info('{0}: Processing event {1}/{2} - {3}:{4:02d}:{5:02d} remaining'.format(self.outputTreeName,total,self.totalEntries,hours,mins,secs))
self.flush()
self.setupEvent(tree)
self.perRowAction()
tfile.Close('R')
def setupEvent(self,tree):
'''Setup the event objects'''
# load objects
self.event = Event(tree)
if self.event.isData(): self.shift = ''
if not self.event.isData(): self.gen = [GenParticle(tree,entry=i) for i in range(tree.genParticles_count)]
self.electrons = [Electron(tree,entry=i,shift=self.shift) for i in range(tree.electrons_count)]
self.muons = [Muon(tree,entry=i,shift=self.shift) for i in range(tree.muons_count)]
self.taus = [Tau(tree,entry=i,shift=self.shift) for i in range(tree.taus_count)]
if hasattr(tree, 'photons_count'): self.photons = [Photon(tree,entry=i,shift=self.shift) for i in range(tree.photons_count)]
self.jets = [Jet(tree,entry=i,shift=self.shift) for i in range(tree.jets_count)]
self.pfmet = Met(tree,shift=self.shift)
def perRowAction(self):
'''Per row action, can be overridden'''
# select candidates
cands = self.selectCandidates()
cands['event'] = self.event
# store event?
goodToStore = self.cutTree.evaluate(cands)
# do we store the tree?
if not goodToStore: return
self.tree.fill(cands)
self.eventsStored += 1
#self.outfile.Flush()
def selectCandidates(self):
'''
Select candidates
format should be:
candidates = {
"objectName" : ("collectionName", position),
...
}
'''
logging.warning("You must override selectCandidates.")
return {}
#################
### utilities ###
#################
def findDecay(self,m_pdgid,d1_pdgid,d2_pdgid):
'''Check if requested decay present in event'''
for g in self.gen:
if m_pdgid==g.pdgId():
if (
(d1_pdgid==g.daughter_1()
and d2_pdgid==g.daughter_2())
or (d1_pdgid==g.daughter_2()
and d2_pdgid==g.daughter_1())
):
return True
return False
def getCands(self,coll,func):
return filter(func,coll)
# cands = []
# for cand in coll:
# if func(cand): cands += [cand]
# return cands
def cleanCands(self,src,other,dr):
cleaned = []
for s in src:
keep = True
for o in other:
if deltaR(s.eta(),s.phi(),o.eta(),o.phi())<dr:
keep = False
break
if keep:
cleaned += [s]
return cleaned
def getCollectionString(self,cand):
if isinstance(cand,Electron): return 'e'
elif isinstance(cand,Muon): return 'm'
elif isinstance(cand,Tau): return 't'
elif isinstance(cand,Photon): return 'g'
elif isinstance(cand,Jet): return 'j'
else: return 'a'
def checkTrigger(self,*datasets,**triggerNames):
'''Check trigger using trigger map'''
isData = self.event.isData()>0.5
# reject triggers if they are in another dataset
# looks for the dataset name in the filename
# for MC it accepts any
reject = True if isData else False
for dataset in datasets:
# if we match to the dataset, start accepting triggers
if dataset in self.fileNames[0] and isData: reject = False
for trigger in triggerNames[dataset]:
var = '{0}Pass'.format(trigger)
passTrigger = getattr(self.event,var)()
if passTrigger>0.5:
# it passed the trigger
# in data: reject if it corresponds to a higher dataset
return False if reject else True
# dont check the rest of data
if dataset in self.fileNames[0] and isData: break
return False
def metFilter(self,cands):
filterList = [
'HBHENoiseFilter',
'HBHENoiseIsoFilter',
'globalTightHalo2016Filter',
'EcalDeadCellTriggerPrimitiveFilter',
'goodVertices',
'eeBadScFilter',
'noBadMuons',
'BadChargedCandidateFilter',
]
notFilterList = [
'duplicateMuons',
'badMuons',
]
for f in filterList:
if not getattr(self.event,f)(): return False
for f in notFilterList:
if getattr(self.event,f)(): return False
return True
##################
### Common IDs ###
##################
# override in derived class if desired
# base selections for H++ analysis
def passLoose(self,cand):
return passHppLoose(cand)
def passMedium(self,cand):
return passHppMedium(cand)
def passTight(self,cand):
return passHppTight(cand)
def passPhotonId(self,cand):
return passPhoton(cand)
def passElectronVeto(self,cand):
return passElectronVeto(cand)
def passPhotonPreselection(self,cand):
return passPreselection(cand)
def passAny(self,cand):
return True
def passPhotonPreselectionNoElectronVeto(self,cand):
return passPreselectionNoElectronVeto(cand)
def looseScale(self,cand):
#key = 'CutbasedVeto' if abs(cand.eta())<1.479 else 'CutbasedLoose'
if cand.collName=='muons': return self.leptonScales.getScale('MediumIDLooseIso',cand,doError=True)
#elif cand.collName=='electrons': return self.leptonScales.getScale(key,cand,doError=True)
elif cand.collName=='electrons': return self.leptonScales.getScale('CutbasedLoose',cand,doError=True)
else: return [1.,1.,1.]
def mediumScale(self,cand):
if cand.collName=='muons': return self.leptonScales.getScale('MediumIDTightIso',cand,doError=True)
elif cand.collName=='electrons': return self.leptonScales.getScale('CutbasedMedium',cand,doError=True)
else: return [1.,1.,1.]
def tightScale(self,cand):
#if cand.collName=='muons': return self.leptonScales.getScale('MediumIDTightIso',cand,doError=True)
if cand.collName=='muons': return self.leptonScales.getScale('TightIDTightIso',cand,doError=True)
elif cand.collName=='electrons': return self.leptonScales.getScale('CutbasedTight',cand,doError=True)
else: return [1.,1.,1.]
def mediumFakeRate(self,cand):
return self.fakeRates.getFakeRate(cand,'HppMedium','HppLoose',doError=True)
def tightFakeRate(self,cand):
return self.fakeRates.getFakeRate(cand,'HppTight','HppLoose',doError=True)
def tightFromMediumFakeRate(self,cand):
return self.fakeRates.getFakeRate(cand,'HppTight','HppMedium',doError=True)
def getPassingCands(self,mode,*colls):
if mode=='Loose': passMode = self.passLoose
elif mode=='Medium': passMode = self.passMedium
elif mode=='Tight': passMode = self.passTight
elif mode=='Photon': passMode = self.passPhotonId
elif mode=='ElectronVeto': passMode = self.passElectronVeto
elif mode=='PhotonPreselection': passMode = self.passPhotonPreselection
elif mode=='PhotonPreselectionNoElectronVeto': passMode = self.passPhotonPreselectionNoElectronVeto
elif mode=='PassAny' : passMode = self.passAny
else: return []
cands = []
for coll in colls:
cands += self.getCands(coll,passMode)
return cands
def numJets(self,cleanJets,mode,pt):
jetColl = self.getCands(
cleanJets,
lambda cand: getattr(cand,mode)()>0.5 and cand.pt()>pt
)
return len(jetColl)
##########################
### add object to tree ###
##########################
def addTriggers(self):
if self.version=='76X':
# single lepton
self.tree.add(lambda cands: self.event.IsoMu20Pass(), 'pass_IsoMu20', 'I')
self.tree.add(lambda cands: self.event.IsoTkMu20Pass(), 'pass_IsoTkMu20', 'I')
self.tree.add(lambda cands: self.event.Ele23_WPLoose_GsfPass(), 'pass_Ele23_WPLoose_Gsf', 'I')
# double lepton
self.tree.add(lambda cands: self.event.Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZPass(), 'pass_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZPass(), 'pass_Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Ele17_Ele12_CaloIdL_TrackIdL_IsoVL_DZPass(), 'pass_Ele17_Ele12_CaloIdL_TrackIdL_IsoVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Mu8_TrkIsoVVL_Ele17_CaloIdL_TrackIdL_IsoVLPass(), 'pass_Mu8_TrkIsoVVL_Ele17_CaloIdL_TrackIdL_IsoVL', 'I')
self.tree.add(lambda cands: self.event.Mu17_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVLPass(), 'pass_Mu17_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL', 'I')
self.tree.add(lambda cands: self.event.DoubleMediumIsoPFTau35_Trk1_eta2p1_RegPass(), 'pass_DoubleMediumIsoPFTau35_Trk1_eta2p1_Reg', 'I')
else:
# single lepton
self.tree.add(lambda cands: self.event.IsoMu24Pass(), 'pass_IsoMu24', 'I')
self.tree.add(lambda cands: self.event.IsoTkMu24Pass(), 'pass_IsoTkMu24', 'I')
self.tree.add(lambda cands: self.event.Mu50Pass(), 'pass_Mu50', 'I')
self.tree.add(lambda cands: self.event.TkMu50Pass(), 'pass_TkMu50', 'I')
self.tree.add(lambda cands: self.event.Ele27_WPTight_GsfPass(), 'pass_Ele27_WPTight_Gsf', 'I')
# double lepton
self.tree.add(lambda cands: self.event.Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZPass(), 'pass_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZPass(), 'pass_Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_DZPass(), 'pass_Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVLPass(), 'pass_Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL', 'I')
self.tree.add(lambda cands: self.event.Mu23_TrkIsoVVL_Ele8_CaloIdL_TrackIdL_IsoVLPass(), 'pass_Mu23_TrkIsoVVL_Ele8_CaloIdL_TrackIdL_IsoVL', 'I')
self.tree.add(lambda cands: self.event.Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZPass(), 'pass_Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZ', 'I')
self.tree.add(lambda cands: self.event.Mu23_TrkIsoVVL_Ele8_CaloIdL_TrackIdL_IsoVL_DZPass(), 'pass_Mu23_TrkIsoVVL_Ele8_CaloIdL_TrackIdL_IsoVL_DZ', 'I')
self.tree.add(lambda cands: self.event.DoubleMediumCombinedIsoPFTau35_Trk1_eta2p1_RegPass(), 'pass_DoubleMediumCombinedIsoPFTau35_Trk1_eta2p1_Reg', 'I')
# triple lepton
self.tree.add(lambda cands: self.event.Ele16_Ele12_Ele8_CaloIdL_TrackIdLPass(), 'pass_Ele16_Ele12_Ele8_CaloIdL_TrackIdL', 'I')
self.tree.add(lambda cands: self.event.Mu8_DiEle12_CaloIdL_TrackIdLPass(), 'pass_Mu8_DiEle12_CaloIdL_TrackIdL', 'I')
self.tree.add(lambda cands: self.event.DiMu9_Ele9_CaloIdL_TrackIdLPass(), 'pass_DiMu9_Ele9_CaloIdL_TrackIdL', 'I')
self.tree.add(lambda cands: self.event.TripleMu_12_10_5Pass(), 'pass_TripleMu_12_10_5', 'I')
def addPhotonTriggers(self):
self.tree.add(lambda cands: self.event.DoublePhoton60Pass(), 'pass_DoublePhoton60', 'I')
self.tree.add(lambda cands: self.event.Diphoton30_18_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass90Pass(), 'pass_Diphoton30_18_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass90', 'I')
self.tree.add(lambda cands: self.event.Photon175Pass(), 'pass_Photon175', 'I')
def addCandVar(self,label,varLabel,var,rootType):
'''Add a variable for a cand'''
self.tree.add(lambda cands: getattr(cands[label],var)(), '{0}_{1}'.format(label,varLabel), rootType)
def addFlavorDependentCandVar(self,label,varLabel,varMap,rootType):
'''Add a variable for a cand based on flavor'''
self.tree.add(lambda cands: getattr(cands[label],varMap[cands[label].collName])() if cands[label].collName in varMap else 0., '{0}_{1}'.format(label,varLabel), rootType)
def addMet(self,label):
'''Add Met variables'''
self.addCandVar(label,'pt','et','F')
self.addCandVar(label,'phi','phi','F')
def addCandidate(self,label):
'''Add variables relevant for all objects'''
self.addCandVar(label,'pt','pt','F')
self.addCandVar(label,'eta','eta','F')
self.addCandVar(label,'phi','phi','F')
self.addCandVar(label,'energy','energy','F')
def addJet(self,label):
'''Add variables relevant for jets'''
self.addCandidate(label)
def addLepton(self,label,doId=False,doScales=False,doFakes=False,doErrors=False):
'''Add variables relevant for leptons'''
self.addCandidate(label)
self.addCandVar(label,'charge','charge','I')
self.addCandVar(label,'dz','dz','F')
self.addCandVar(label,'pdgId','pdgId','I')
self.addFlavorDependentCandVar(label,'dxy', {'electrons':'dB2D', 'muons':'dB2D', 'taus':'dxy', '':''},'F')
self.addFlavorDependentCandVar(label,'isolation', {'electrons':'relPFIsoRhoR03', 'muons':'relPFIsoDeltaBetaR04', '':''},'F')
self.addFlavorDependentCandVar(label,'genMatch', {'electrons':'genMatch', 'muons':'genMatch', 'taus':'genJetMatch', '':''},'I')
self.tree.add(lambda cands: self.genDeltaR(cands[label]) if isinstance(cands[label],Electron) or isinstance(cands[label],Muon) else self.genJetDeltaR(cands[label]), '{0}_genDeltaR'.format(label), 'F')
self.addFlavorDependentCandVar(label,'genStatus', {'electrons':'genStatus', 'muons':'genStatus', 'taus':'genJetStatus','':''},'I')
self.addFlavorDependentCandVar(label,'genPdgId', {'electrons':'genPdgId', 'muons':'genPdgId', 'taus':'genJetPdgId', '':''},'I')
self.addFlavorDependentCandVar(label,'genPt', {'electrons':'genPt', 'muons':'genPt', 'taus':'genJetPt', '':''},'F')
self.addFlavorDependentCandVar(label,'genEta', {'electrons':'genEta', 'muons':'genEta', 'taus':'genJetEta', '':''},'F')
self.addFlavorDependentCandVar(label,'genPhi', {'electrons':'genPhi', 'muons':'genPhi', 'taus':'genJetPhi', '':''},'F')
self.addFlavorDependentCandVar(label,'genEnergy', {'electrons':'genEnergy', 'muons':'genEnergy', 'taus':'genJetEnergy','':''},'F')
self.addFlavorDependentCandVar(label,'genCharge', {'electrons':'genCharge', 'muons':'genCharge', 'taus':'genJetCharge','':''},'I')
self.addFlavorDependentCandVar(label,'genIsPrompt', {'electrons':'genIsPrompt', 'muons':'genIsPrompt', '':''},'I')
self.addFlavorDependentCandVar(label,'genIsFromTau', {'electrons':'genIsFromTau', 'muons':'genIsFromTau', '':''},'I')
self.addFlavorDependentCandVar(label,'genIsFromHadron',{'electrons':'genIsFromHadron','muons':'genIsFromHadron', '':''},'I')
if doId:
self.tree.add(lambda cands: self.passMedium(cands[label]), '{0}_passMedium'.format(label), 'I')
self.tree.add(lambda cands: self.passTight(cands[label]), '{0}_passTight'.format(label), 'I')
if doScales:
self.tree.add(lambda cands: self.looseScale(cands[label])[0], '{0}_looseScale'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.looseScale(cands[label])[1], '{0}_looseScaleUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.looseScale(cands[label])[2], '{0}_looseScaleDown'.format(label), 'F')
self.tree.add(lambda cands: self.mediumScale(cands[label])[0], '{0}_mediumScale'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.mediumScale(cands[label])[1], '{0}_mediumScaleUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.mediumScale(cands[label])[2], '{0}_mediumScaleDown'.format(label), 'F')
self.tree.add(lambda cands: self.tightScale(cands[label])[0], '{0}_tightScale'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightScale(cands[label])[1], '{0}_tightScaleUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightScale(cands[label])[2], '{0}_tightScaleDown'.format(label), 'F')
if doFakes:
self.tree.add(lambda cands: self.mediumFakeRate(cands[label])[0], '{0}_mediumFakeRate'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.mediumFakeRate(cands[label])[1], '{0}_mediumFakeRateUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.mediumFakeRate(cands[label])[2], '{0}_mediumFakeRateDown'.format(label), 'F')
self.tree.add(lambda cands: self.tightFakeRate(cands[label])[0], '{0}_tightFakeRate'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightFakeRate(cands[label])[1], '{0}_tightFakeRateUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightFakeRate(cands[label])[2], '{0}_tightFakeRateDown'.format(label), 'F')
self.tree.add(lambda cands: self.tightFromMediumFakeRate(cands[label])[0], '{0}_tightFromMediumFakeRate'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightFromMediumFakeRate(cands[label])[1], '{0}_tightFromMediumFakeRateUp'.format(label), 'F')
if doErrors: self.tree.add(lambda cands: self.tightFromMediumFakeRate(cands[label])[2], '{0}_tightFromMediumFakeRateDown'.format(label), 'F')
def addPhoton(self,label,doId=False,doScales=False,doFakes=False,doErrors=False):
'''Add variables relevant for photons'''
self.addCandidate(label)
self.addCandVar(label,'mvaNonTrigValues','mvaNonTrigValues','F')
self.addCandVar(label,'mvaNonTrigCategories','mvaNonTrigCategories','F')
self.addCandVar(label,'r9','r9','F')
self.addCandVar(label,'chargedIso','phoChargedIsolation','F')
self.addCandVar(label,'neutralHadronIso','phoNeutralHadronIsolation','F')
self.addCandVar(label,'photonIso','phoPhotonIsolation','F')
if doId:
self.tree.add(lambda cands: self.passPhotonId(cands[label]), '{0}_passId'.format(label), 'I')
self.tree.add(lambda cands: self.passElectronVeto(cands[label]), '{0}_passElectronVeto'.format(label), 'I')
self.tree.add(lambda cands: self.passPhotonPreselection(cands[label]), '{0}_passPreselection'.format(label), 'I')
self.tree.add(lambda cands: self.passPhotonPreselectionNoElectronVeto(cands[label]), '{0}_passPreselectionNoElectronVeto'.format(label), 'I')
def genDeltaR(self,cand):
'''Get the gen level deltaR'''
if cand.genMatch()==0: return 0.
eta = cand.eta()
genEta = cand.genEta()
phi = cand.phi()
genPhi = cand.genPhi()
return deltaR(eta,phi,genEta,genPhi)
def genJetDeltaR(self,cand):
'''Get the gen level deltaR'''
if cand.genJetMatch()==0: return 0.
eta = cand.eta()
genEta = cand.genJetEta()
phi = cand.phi()
genPhi = cand.genJetPhi()
return deltaR(eta,phi,genEta,genPhi)
def addDiCandidate(self,label):
'''Add variables relevant for a two object candidate'''
self.addCandVar(label,'mass','M','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
self.addCandVar(label,'deltaR','deltaR','F')
self.addCandVar(label,'deltaEta','deltaEta','F')
self.addCandVar(label,'deltaPhi','deltaPhi','F')
self.addCandVar(label,'energy','Energy','F')
def addDiJet(self,label):
'''Add variables relevant for a dijet candidate'''
self.addDiCandidate(label)
def addDiLepton(self,label):
'''Add variables relevant for a dilepton candidate'''
self.addDiCandidate(label)
def addLeptonMet(self,label):
'''Add variables related to a lepton + met'''
self.addCandVar(label,'mt','Mt','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
self.addCandVar(label,'deltaPhi','deltaPhi','F')
def addComposite(self,label):
'''Add variables related to multi object variables'''
self.addCandVar(label,'mass','M','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
self.addCandVar(label,'energy','Energy','F')
def addCompositeMet(self,label):
'''Add variables related to multi object variables'''
self.addCandVar(label,'mt','Mt','F')
self.addCandVar(label,'pt','Pt','F')
self.addCandVar(label,'eta','Eta','F')
self.addCandVar(label,'phi','Phi','F')
class AnalysisBase(object):
'''
Analysis Tree
'''
def __init__(self,**kwargs):
inputFileNames = kwargs.pop('inputFileNames',[])
inputTreeDirectory = kwargs.pop('inputTreeDirectory','miniTree')
inputTreeName = kwargs.pop('inputTreeName','MiniTree')
inputLumiName = kwargs.pop('inputTreeName','LumiTree')
outputFileName = kwargs.pop('outputFileName','analysisTree.root')
outputTreeName = kwargs.pop('outputTreeName','AnalysisTree')
if hasProgress:
self.pbar = kwargs.pop('progressbar',ProgressBar(widgets=['{0}: '.format(outputTreeName),' ',SimpleProgress(),' events ',Percentage(),' ',Bar(),' ',ETA()]))
# input files
self.fileNames = []
if isinstance(inputFileNames, basestring): # inputFiles is a file name
if os.path.isfile(inputFileNames): # single file
if inputFileNames[-4:] == 'root': # file is a root file
self.fileNames += [inputFileNames]
else: # file is list of files
with open(inputFileNames,'r') as f:
for line in f:
self.fileNames += [line.strip()]
else:
self.fileNames = inputFileNames # already a python list or a cms.untracked.vstring()
if not isinstance(outputFileName, basestring): # its a cms.string(), get value
outputFileName = outputFileName.value()
# input tchain
self.tchain = ROOT.TChain('{0}/{1}'.format(inputTreeDirectory,inputTreeName))
tchainLumi = ROOT.TChain('{0}/{1}'.format(inputTreeDirectory,inputLumiName))
for fName in self.fileNames:
if fName.startswith('/store'): fName = 'root://cmsxrootd.hep.wisc.edu//{0}'.format(fName)
self.tchain.Add(fName)
tchainLumi.Add(fName)
# get the lumi info
self.numLumis = tchainLumi.GetEntries()
self.numEvents = 0
self.summedWeights = 0
for entry in xrange(self.numLumis):
tchainLumi.GetEntry(entry)
self.numEvents += tchainLumi.nevents
self.summedWeights += tchainLumi.summedWeights
logging.info("Will process {0} lumi sections with {1} events ({2}).".format(self.numLumis,self.numEvents,self.summedWeights))
self.flush()
# other input files
self.pileupWeights = PileupWeights()
self.leptonScales = LeptonScales()
# tfile
self.outfile = ROOT.TFile(outputFileName,"recreate")
# cut tree
self.cutTree = CutTree()
# analysis tree
self.tree = AnalysisTree(outputTreeName)
self.eventsStored = 0
# some things we always need:
# pileup
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[0], 'pileupWeight', 'F')
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[1], 'pileupWeightUp', 'F')
self.tree.add(lambda rtrow,cands: self.pileupWeights.weight(rtrow)[2], 'pileupWeightDown', 'F')
def __exit__(self, type, value, traceback):
self.finish()
def __del__(self):
self.finish()
def finish(self):
logging.info('Finishing')
logging.info('Writing {0} events'.format(self.eventsStored))
self.outfile.cd()
cutflowHist = ROOT.TH1F('summedWeights','summedWeights',1,0,1)
cutflowHist.SetBinContent(1,self.summedWeights)
self.outfile.Write()
self.outfile.Close()
self.leptonScales.finish()
def flush(self):
sys.stdout.flush()
sys.stderr.flush()
#############################
### primary analysis loop ###
#############################
def analyze(self):
'''
The primary analyzer loop.
'''
logging.info('Beginning Analysis')
start = time.time()
new = start
old = start
treeEvents = self.tchain.GetEntries()
rtrow = self.tchain
if hasProgress:
for r in self.pbar(xrange(treeEvents)):
rtrow.GetEntry(r)
self.perRowAction(rtrow)
else:
for r in xrange(treeEvents):
if r==2: start = time.time() # just ignore first event for timing
rtrow.GetEntry(r)
if r % 1000 == 1:
cur = time.time()
elapsed = cur-start
remaining = float(elapsed)/r * float(treeEvents) - float(elapsed)
mins, secs = divmod(int(remaining),60)
hours, mins = divmod(mins,60)
logging.info('Processing event {0}/{1} - {2}:{3:02d}:{4:02d} remaining'.format(r,treeEvents,hours,mins,secs))
self.flush()
self.perRowAction(rtrow)
def perRowAction(self,rtrow):
'''Per row action, can be overridden'''
self.cache = {} # cache variables so you dont read from tree as much
# select candidates
cands = self.selectCandidates(rtrow)
# store event?
goodToStore = self.cutTree.evaluate(rtrow,cands)
# do we store the tree?
if not goodToStore: return
self.tree.fill(rtrow,cands)
self.eventsStored += 1
#self.outfile.Flush()
def selectCandidates(self,rtrow):
'''
Select candidates
format should be:
candidates = {
"objectName" : ("collectionName", position),
...
}
'''
logging.warning("You must override selectCandidates.")
return {}
########################
### object variables ###
########################
def getObjectVariable(self, rtrow, cand, var):
'''
Simple utility to get variables
'''
if len(cand)!=2:
return 0
coll, pos = cand
key = '{0}_{1}_{2}'.format(coll,var,pos)
if key in self.cache: return self.cache[key]
# get a TLorentzVector
if var=='p4':
pt = self.getObjectVariable(rtrow,cand,'pt')
eta = self.getObjectVariable(rtrow,cand,'eta')
phi = self.getObjectVariable(rtrow,cand,'phi')
energy = self.getObjectVariable(rtrow,cand,'energy')
val = ROOT.TLorentzVector()
val.SetPtEtaPhiE(pt,eta,phi,energy)
# if invalid, return 0
elif pos<0:
val = 0
# override muon pt/eta/phi/energy for rochester correction
elif coll=='muons' and var in ['pt','eta','phi','energy']:
val = getattr(rtrow,'{0}_rochester{1}'.format(coll,var.capitalize()))[pos]
elif coll=='muons' and var in ['pt_uncorrected','eta_uncorrected','phi_uncorrected','energy_uncorrected']:
val = getattr(rtrow,'{0}_{1}'.format(coll,var.split('_')[0]))[pos]
# the variable is in the input tree
elif hasattr(rtrow,'{0}_{1}'.format(coll,var)):
val = getattr(rtrow,'{0}_{1}'.format(coll,var))[pos]
# didnt catch it
else:
val = 0
self.cache[key] = val
return val
def getCompositeVariable(self,rtrow,var,*cands):
'''Create a composite candidate'''
key = '_'.join(['{0}_{1}'.format(*cand) for cand in cands] + [var])
if key in self.cache: return self.cache[key]
vec = ROOT.TLorentzVector()
for cand in cands:
vec += self.getObjectVariable(rtrow,cand,'p4')
if var=='p4':
val = vec
elif var in ['mass','Mass','m','M']:
val = vec.M()
elif var in ['pt','Pt']:
val = vec.Pt()
elif var in ['eta','Eta']:
val = vec.Eta()
elif var in ['phi','Phi']:
val = vec.Phi()
elif var in ['energy','Energy']:
val = vec.Energy()
elif len(cands)==2:
if var in ['deltaR','dR','dr','DR']:
eta1 = self.getObjectVariable(rtrow,cands[0],'eta')
phi1 = self.getObjectVariable(rtrow,cands[0],'phi')
eta2 = self.getObjectVariable(rtrow,cands[1],'eta')
phi2 = self.getObjectVariable(rtrow,cands[1],'phi')
val = deltaR(eta1,phi1,eta2,phi2)
elif var in ['deltaPhi','dPhi','dphi','DPhi']:
phi1 = self.getObjectVariable(rtrow,cands[0],'phi')
phi2 = self.getObjectVariable(rtrow,cands[1],'phi')
val = deltaPhi(phi1,phi2)
elif var in ['deltaEta','dEta','deta','DEta']:
eta1 = self.getObjectVariable(rtrow,cands[0],'eta')
eta2 = self.getObjectVariable(rtrow,cands[1],'eta')
val = abs(eta1-eta2)
else:
val = 0
else:
val = 0
self.cache[key] = val
return val
def getCompositeMetVariable(self,rtrow,var,met,*cands):
'''Get composite met variables'''
key = '_'.join(['{0}_{1}'.format(*cand) for cand in cands] + ['{0}_{1}'.format(*met)] + [var])
if key in self.cache: return self.cache[key]
candVec = self.getCompositeVariable(rtrow,'p4',*cands)
metVec = ROOT.TLorentzVector()
metPt = self.getObjectVariable(rtrow,met,'et')
metPhi = self.getObjectVariable(rtrow,met,'phi')
metVec.SetPtEtaPhiM(metPt,0,metPhi,0)
vec = candVec + metVec
if var=='p4':
val = vec
elif var in ['mt','Mt','mT','MT']:
#val = math.sqrt(2*candVec.Pt()*metPt*(1-math.cos(deltaPhi(candVec.Phi(),metPhi))))
val = math.sqrt(abs((candVec.Et()+metVec.Et())**2 - (vec.Pt())**2))
elif var in ['mass','Mass','m','M']:
val = vec.M()
elif var in ['pt','Pt']:
val = vec.Pt()
elif var in ['eta','Eta']:
val = vec.Eta()
elif var in ['phi','Phi']:
val = vec.Phi()
elif var in ['energy','Energy']:
val = vec.Energy()
elif len(cands)==1:
if var in ['deltaPhi','dPhi','dphi','DPhi']:
phi1 = self.getObjectVariable(rtrow,cands[0],'phi')
phi2 = metPhi
val = deltaPhi(phi1,phi2)
else:
val = 0
else:
val = 0
self.cache[key] = val
return val
def getTreeVariable(self, rtrow, var):
'''
Get event wide variables
'''
key = var
if key in self.cache: return self.cache[key]
if hasattr(rtrow,var):
val = getattr(rtrow,var)
else:
val = 0
logging.info("{0} not found.".format(var))
self.cache[key] = val
return val
def getCands(self,rtrow,coll,func):
cands = []
numColl = getattr(rtrow,'{0}_count'.format(coll))
for c in range(numColl):
cand = (coll,c)
if func(rtrow,cand): cands += [cand]
return cands
def getCollectionString(self,cand):
if cand[0]=='electrons': return 'e'
elif cand[0]=='muons': return 'm'
elif cand[0]=='taus': return 't'
elif cand[0]=='photons': return 'g'
elif cand[0]=='jets': return 'j'
else: return 'a'
##########################
### add object to tree ###
##########################
def addMet(self,label,met):
'''Add Met variables'''
self.addMetVar(label,met,'pt','et','F')
self.addMetVar(label,met,'phi','phi','F')
def addMetVar(self,label,met,varLabel,var,rootType):
'''Add a single met var'''
self.tree.add(lambda rtrow,cands: self.getObjectVariable(rtrow,met,var), '{0}_{1}'.format(label,varLabel), rootType)
def addJet(self,label):
'''Add variables relevant for jets'''
self.addCandVar(label,'pt','pt','F')
self.addCandVar(label,'eta','eta','F')
self.addCandVar(label,'phi','phi','F')
self.addCandVar(label,'energy','energy','F')
def addLepton(self,label):
'''Add variables relevant for leptons'''
self.addCandVar(label,'pt','pt','F')
self.addCandVar(label,'eta','eta','F')
self.addCandVar(label,'phi','phi','F')
self.addCandVar(label,'energy','energy','F')
self.addCandVar(label,'charge','charge','I')
self.addCandVar(label,'dz','dz','F')
#self.addCandVar(label,'dxy','dxy','F')
self.addFlavorDependentCandVar(label,'dxy',{'electrons':'dB2D','muons':'dB2D','taus':'dxy','':''},'F')
self.addCandVar(label,'genMatch','genMatch','I')
self.tree.add(lambda rtrow,cands: self.genDeltaR(rtrow,cands[label]), '{0}_genDeltaR'.format(label), 'F')
self.addCandVar(label,'genStatus','genStatus','I')
self.addCandVar(label,'genPdgId','genPdgId','I')
self.addCandVar(label,'genPt','genPt','F')
self.addCandVar(label,'genEta','genEta','F')
self.addCandVar(label,'genPhi','genPhi','F')
self.addCandVar(label,'genEnergy','genEnergy','F')
self.addCandVar(label,'genCharge','genCharge','I')
self.addCandVar(label,'genIsPrompt','genIsPrompt','I')
self.addCandVar(label,'genIsFromTau','genIsFromTau','I')
self.addCandVar(label,'genIsFromHadron','genIsFromHadron','I')
self.addFlavorDependentCandVar(label,'isolation',{'electrons':'relPFIsoRhoR03','muons':'relPFIsoDeltaBetaR04','':''},'F')
def genDeltaR(self,rtrow,cand):
'''Get the gen level deltaR'''
eta = self.getObjectVariable(rtrow,cand,'eta')
genEta = self.getObjectVariable(rtrow,cand,'genEta')
phi = self.getObjectVariable(rtrow,cand,'phi')
genPhi = self.getObjectVariable(rtrow,cand,'genPhi')
return deltaR(eta,phi,genEta,genPhi)
def addCandVar(self,label,varLabel,var,rootType):
'''Add a variable for a cand'''
self.tree.add(lambda rtrow,cands: self.getObjectVariable(rtrow,cands[label],var), '{0}_{1}'.format(label,varLabel), rootType)
def addFlavorDependentCandVar(self,label,varLabel,varMap,rootType):
'''Add a variable for a cand based on flavor'''
self.tree.add(lambda rtrow,cands: self.getObjectVariable(rtrow,cands[label],varMap[cands[label][0]]), '{0}_{1}'.format(label,varLabel), rootType)
def addDiJet(self,label,obj1,obj2):
'''Add variables relevant for a dijet candidate'''
self.addDiCandVar(label,obj1,obj2,'mass','mass','F')
self.addDiCandVar(label,obj1,obj2,'pt','pt','F')
self.addDiCandVar(label,obj1,obj2,'eta','eta','F')
self.addDiCandVar(label,obj1,obj2,'phi','phi','F')
self.addDiCandVar(label,obj1,obj2,'deltaR','deltaR','F')
self.addDiCandVar(label,obj1,obj2,'deltaEta','deltaEta','F')
self.addDiCandVar(label,obj1,obj2,'deltaPhi','deltaPhi','F')
self.addDiCandVar(label,obj1,obj2,'energy','energy','F')
def addDiLepton(self,label,obj1,obj2):
'''Add variables relevant for a dilepton candidate'''
self.addDiCandVar(label,obj1,obj2,'mass','mass','F')
self.addDiCandVar(label,obj1,obj2,'pt','pt','F')
self.addDiCandVar(label,obj1,obj2,'eta','eta','F')
self.addDiCandVar(label,obj1,obj2,'phi','phi','F')
self.addDiCandVar(label,obj1,obj2,'deltaR','deltaR','F')
self.addDiCandVar(label,obj1,obj2,'deltaEta','deltaEta','F')
self.addDiCandVar(label,obj1,obj2,'deltaPhi','deltaPhi','F')
self.addDiCandVar(label,obj1,obj2,'energy','energy','F')
def addDiCandVar(self,label,obj1,obj2,varLabel,var,rootType):
'''Add a variable for a dilepton candidate'''
self.tree.add(lambda rtrow,cands: self.getCompositeVariable(rtrow,var,cands[obj1],cands[obj2]), '{0}_{1}'.format(label,varLabel), rootType)
def addLeptonMet(self,label,obj,met):
'''Add variables related to a lepton + met'''
self.addCandMetVar(label,obj,met,'mass','mass','F')
self.addCandMetVar(label,obj,met,'pt','pt','F')
self.addCandMetVar(label,obj,met,'eta','eta','F')
self.addCandMetVar(label,obj,met,'deltaPhi','deltaPhi','F')
self.addCandMetVar(label,obj,met,'mt','mt','F')
def addCandMetVar(self,label,obj,met,varLabel,var,rootType):
'''Add a single lepton met var'''
self.tree.add(lambda rtrow,cands: self.getCompositeMetVariable(rtrow,var,met,cands[obj]), '{0}_{1}'.format(label,varLabel), rootType)
def addComposite(self,label,*objs):
'''Add variables realated to multi object variables'''
self.addCompositeVar(label,objs,'mass','mass','F')
self.addCompositeVar(label,objs,'pt','pt','F')
self.addCompositeVar(label,objs,'eta','eta','F')
self.addCompositeVar(label,objs,'phi','phi','F')
self.addCompositeVar(label,objs,'energy','energy','F')
def addCompositeVar(self,label,objs,varLabel,var,rootType):
'''Add single variable for multiple objects'''
self.tree.add(lambda rtrow,cands: self.getCompositeVariable(rtrow,var,*[cands[obj] for obj in objs]), '{0}_{1}'.format(label,varLabel), rootType)