def CreateData(fileList, filename):
pathList = fileList #['test1.root', 'test2.root']
signalTreeList = TList()
backgroundTreeList = TList()
outputFile = TFile(filename, 'recreate')
pyfilelist = []
pySignalTreelist = []
pyBackgroundTreelist = []
for path in pathList:
print("Path", path)
inputFile = TFile(path, 'read')
pyfilelist.append(inputFile) # Make this TFile survive the loop!
inputSignalTree = inputFile.Get('Signal')
inputBackgroundTree = inputFile.Get('Background')
pySignalTreelist.append(
inputSignalTree) # Make this TTree survive the loop!
pyBackgroundTreelist.append(
inputBackgroundTree) # Make this TTree survive the loop!
outputSignalTree = inputSignalTree.CloneTree(
) #instead of extensive processing
outputBackgroundTree = inputBackgroundTree.CloneTree(
) #instead of extensive processing
signalTreeList.Add(inputSignalTree)
backgroundTreeList.Add(inputBackgroundTree)
outputFile.cd()
outputSignalTree = TTree.MergeTrees(signalTreeList)
outputBackgroundTree = TTree.MergeTrees(backgroundTreeList)
outputFile.Write()
outputFile.Close()
def run_analysis(options,args):
tm = tree_manager()
pu_weight_sum = 0.0
selected_events = []
metaInfoTrees = []
nEvents_total = int(0)
pwd = ROOT.gDirectory.GetPath()
for kFile,input_file in enumerate(args):
print
print 'processing input file %i/%i: %s'%(kFile+1,
len(args),
input_file)
in_file = TFile.Open(input_file,'read')
ROOT.gDirectory.cd(pwd)
leptonType = options.leptonType
tree = None
nEvents_sample = 0
specific = None
treeName = 'Ntuple'
if not options.allBranches:
if leptonType == 'muon':
#specific = muonBranches+commonBranches
mmg = in_file.Get('mmg')
tree = mmg.Get('final').Get(treeName)
metaInfoTrees.append(mmg.Get('metaInfo').CloneTree())
nEvents_sample = mmg.Get('eventCount').GetBinContent(1)
nEvents_total += mmg.Get('skimCounter').GetBinContent(1)
mmg = None
elif leptonType == 'electron':
#specific = electronBranches+commonBranches
eeg = in_file.Get('eeg')
tree = eeg.Get('final').Get(treeName)
metaInfoTrees.append(eeg.Get('metaInfo').CloneTree())
nEvents_sample = eeg.Get('eventCount').GetBinContent(1)
nEvents_total += eeg.Get('skimCounter').GetBinContent(1)
eeg = None
else:
raise Exception('invalid lepton type: %s'%options.leptonType)
total_events = tree.GetEntriesFast()
tick_size = total_events/100.0
if tick_size < 1: tick_size = 1.0
#tm.importTree(treeName,tree,specific)
#tm.cloneTree(treeName,'%s_zs'%treeName,specific)
#tm.cloneTree(treeName,'%s_zgs'%treeName,specific)
#tm.cloneTree(treeName,'%s_zgs_nosihih'%treeName,specific)
#setup process dependent stuff
cuts = setupCuts(options)
#lepton_mass = lepton_masses[options.leptonType]
#z_info = z_infos[options.leptonType]
#lepton_info = lepton_infos[options.leptonType]
#setup pu-reweighing
#pu_weight = pu_weight_nominal
#if options.isSummer11:
# pu_weigt = pu_weight_summer11
procWeight = 1.0
if options.datType != 'data':
procWeight = (options.crossSection *
run_lumi[options.leptonType][options.runYear]\
[options.runType])
# setup the corrector (this links the appropriate four momenta
# into a common naming scheme
correct = setup_corrections(options.runYear , options.runType,
options.leptonType, options.datType,
options.leptonCor , options.gamCor,
options.vanilla )
ievent = long(0)
for event in tree:
ievent+=1
#print ievent,total_events,fmod(ievent/total_events,0.01)
if( not (ievent+1)%int(tick_size) or
ievent+1 == total_events ):
sys.stdout.write('\r%3.0f%s complete! (%i/%i)'%(((ievent+1)/
tick_size),
'%',
ievent+1,
total_events))
sys.stdout.flush()
# setup the common event momentum
# ell1 = lepton1, ell2 = lepton2
# gam = photon, Z = dilepton, Zg = Z+photon
correct(event)
run_idx = getRunIndex(event.run[0],options.runYear,
options.runType,options.datType,
options.leptonType)
setattr(event,'procWeight',procWeight)
setattr(event,'puWeight',1.0)
if options.datType != 'data':
setattr(event,'eventFraction',float(ievent+1)/total_events)
event.puWeight = pu_S10_CD_reweight(event.nTruePU[0])
#selected_z = []
#selected_pho_nosihih = []
#selected_pho = []
#bad_leptons = []
if options.datType == 'data':
# kill run 170722
# kill the obvious pile up combinatorial event
if ( event.run[0] == 170722 or
(event.run[0] == 166512 and
event.lumi[0] == 1678 and
event.evt[0] == 1822682238) ):
continue
bestLLG = None
bestZdiff = -1
for i in range(event.N_PATFinalState):
cuts.getCutflow('trigger')(event,i)
if options.exlProc and not cuts.getCutflow('trigger') :
continue
cuts.getCutflow('pho')(event,i)
cuts.getCutflow('leptons')(event,i)
if ( options.exlProc and
not cuts.getCutflow('leptons') and
not cuts.getCutflow('pho') ):
continue
cuts.getCutflow('z')(event,i)
if options.exlProc and not cuts.getCutflow('z'):
continue
if ( cuts.getCutflow('trigger') and
cuts.getCutflow('leptons') and
cuts.getCutflow('pho') and
cuts.getCutflow('z') ):
thisZdiff = abs(Z_POLE-event.Z[i].M())
if( cuts.getCut('mindr')[0](event.ell1[i],
event.ell2[i],
event.gam[i]) and
(thisZdiff < bestZdiff or bestLLG is None) ):
bestZdiff = thisZdiff
bestLLG = i
#event object selection done
if options.exlProc and bestLLG is None:
continue
bestZ = bestLLG
if bestLLG is not None:
setattr(event,'ell1SF',1.0)
setattr(event,'ell2SF',1.0)
#if run_idx != -1:
# event.ell1SF = leptonSF_nominal(event.nGoodVtx,
# getattr(event,lepton_info['pt'])[idx1],
# getattr(event,lepton_info['eta'])[idx1],
# run_idx,
# options.leptonType)
# event.ell2SF = leptonSF_nominal(event.nGoodVtx,
# getattr(event,lepton_info['pt'])[idx2],
# getattr(event,lepton_info['eta'])[idx2],
# run_idx,
# options.leptonType)
setattr(event,'bestZ',bestLLG)
outTrees.bestZTree(event,tm)
#tm.fillTree('%s_zs'%treeName,{})
#bestPhoNoSihih = None
#bestPhoNoSihihPt = -1
#for idxph in selected_pho_nosihih:
# pho.SetPtEtaPhiM(event.phoCorEt[idxph],
# event.phoEta[idxph],
# event.phoPhi[idxph],
# 0.0)
# if bestPhoNoSihih is None or pho.Pt() > bestPhoNoSihihPt:
# if ( bestZ is not None and
# cuts.getCut('mindr')[0](event.bestZLeg1,
# event.bestZLeg2,
# pho) ):
# bestPhoNoSihih = idxph
# bestPhoNoSihihPt = pho.Pt()
# elif( bestZ is None ):
# bestPhoSihih = idxph
# bestPhoSihihPt = pho.Pt()
bestPho = bestLLG #and bestPhoNoSihih is None: (below)
if options.exlProc and bestPho is None:
continue
if bestPho is not None:
setattr(event,'phoSF',1.0)
#if run_idx != -1:
# event.phoSF = phoSF_nominal(event.nGoodVtx,
# event.phoEt[bestPho],
# event.phoEta[bestPho],
# run_idx)
setattr(event,'bestPho',bestPho)
#if bestPhoNoSihih is not None:
# setattr(event,'phoNoSihihSF',event.phoSF)
# setattr(event,'bestPhoNoSihihIdx',bestPho)
# setattr(event,'bestPhoNoSihih',pho)
#elif bestPhoNoSihih is not None:
# pho.SetPtEtaPhiM(event.phoCorEt[bestPhoNoSihih],
# event.phoEta[bestPhoNoSihih],
# event.phoPhi[bestPhoNoSihih],
# 0.0)
# setattr(event,'phoNoSihihSF',1.0)
# if run_idx != -1:
# event.phoNoSihihSF = phoSF_nominal(event.nGoodVtx,
# event.phoEt[bestPhoNoSihih],
# event.phoEta[bestPhoNoSihih],
# run_idx)
# setattr(event,'bestPhoNoSihihIdx',bestPhoNoSihih)
# setattr(event,'bestPhoNoSihih',pho)
if bestLLG is not None:
#if bestPhoNoSihih is not None:
# thezg = event.bestZ + event.bestPhoNoSihih
# setattr(event,'bestZGNoSihih',thezg)
# outTrees.bestZGTreeNoSihih(event,tm)
# tm.fillTree('EventTree_zgs_nosihih',{})
hzg_r94cat = hzg_4cat_r9based[leptonType](event,bestLLG)
setattr(event,'bestZG_r94cat',hzg_r94cat)
hzg_r94cat_mod = \
hzg_4cat_r9based_mod[leptonType](event,bestLLG)
setattr(event,'bestZG_r94cat_mod',hzg_r94cat_mod)
thezg = event.Zg[bestLLG]
selected_events.append((event.run[bestLLG],
event.lumi[bestLLG],
event.evt[bestLLG]))
setattr(event,'bestZG',thezg)
outTrees.bestZGTree(event,tm)
pu_weight_sum += event.puWeight
#tm.fillTree('%s_zgs'%treeName,{})
tree = None
in_file.Close()
del in_file
#make a nice file name
input_file = args[0]
nameparts = input_file[input_file.rfind('/')+1:]
nameparts = nameparts.split('.')
#output selected event numbers to file if needed
print
print 'Selected %i (%.2f) events after processing!'%(len(selected_events),
pu_weight_sum)
try:
os.makedirs(options.prefix)
print 'Created prefix directory: %s'%options.prefix
except os.error:
print 'Prefix directory: %s already exists'%options.prefix
if options.dumpSelectedEvents:
#sort events
selected_events.sort(key=lambda event: event[2])
selected_events.sort(key=lambda event: event[1])
selected_events.sort(key=lambda event: event[0])
evf = open(options.prefix +
'%s_%s_%s_processed.%s'%('_'.join(nameparts[:-1]),
options.runType,
options.leptonType,
'txt'),
'w')
for ev in selected_events:
evf.write('Run, Lumi, Event #:\t%i\t%i\t%i\n'%ev)
evf.close()
#push all of our output trees to a file
outFileName = ''
if options.vanilla:
outFileName = '%s_%s_%s_%s_%s_processed.%s'\
%('_'.join(nameparts[:-1]),
options.runType,
options.datType,
options.leptonType,
'vanilla',
nameparts[-1])
else:
outFileName = '%s_%s_%s_%s_%s_%s_processed.%s'\
%('_'.join(nameparts[:-1]),
options.runType,
options.datType,
options.leptonType,
options.leptonCor,
options.gamCor,
nameparts[-1])
hEventCount = TH1I('eventCount','Total Events Processed',1,0,1)
hEventCount.SetBinContent(1,nEvents_total)
metaTList = TList()
for tree in metaInfoTrees:
metaTList.Add(tree)
metaTree = TTree.MergeTrees(metaTList)
outf = TFile.Open(options.prefix + outFileName,'RECREATE')
outf.cd()
metaTree.Write()
hEventCount.Write()
tm.write()
outf.Close()
ROOT.gDirectory.cd(pwd)
format(home),
"{0}/scratch0/ntuple/background_analysis/PFAnalysis_QCDEM3080_5.root".
format(home),
"{0}/scratch0/ntuple/background_analysis/PFAnalysis_QCDEM3080_6.root".
format(home),
"{0}/scratch0/ntuple/background_analysis/PFAnalysis_QCDEM3080_7.root".
format(home),
"{0}/scratch0/ntuple/background_analysis/PFAnalysis_QCDEM3080_8.root".
format(home),
"{0}/scratch0/ntuple/background_analysis/PFAnalysis_QCDEM3080_9.root".
format(home),
]
tree_list = TList()
tree_name = "Summary/tree"
output_file_name = "~/scratch0/PFAnalysis_QCDEM3080_0.root"
files = [
TFile(file_name) for file_name in file_list if os.path.exists(file_name)
]
print("{0} files found.".format(len(files)))
trees = [file.Get(tree_name) for file in files]
for tree in trees:
if tree:
tree_list.Add(tree)
merged_tree = TTree.MergeTrees(tree_list)
output_file = TFile(output_file_name, "recreate")
merged_tree.Write()
output_file.Close()
)
file = TFile(
"/home/arun/ttHAnalysis/2016/2017Feb21_fastsim_dR03mvaLoose/histograms/2lss_1tau/forBDTtraining_SS_OS/ntuple_2lss_1tau_SS_OS_all.root"
)
if process == "signal":
tree = file.Get("2lss_1tau_lepSS_sumOS_Loose/sel/evtntuple/signal/evtTree")
elif process == "TTV":
tree_ttw = file.Get(
"2lss_1tau_lepSS_sumOS_Loose/sel/evtntuple/TTW/evtTree")
tree_ttz = file.Get(
"2lss_1tau_lepSS_sumOS_Loose/sel/evtntuple/TTZ/evtTree")
list = TList()
list.Add(tree_ttw)
list.Add(tree_ttz)
tree = TTree.MergeTrees(list)
tree.SetName("bkgTree")
c1 = TCanvas()
c1.SetFillColor(10)
c1.SetBorderSize(2)
c1.SetLeftMargin(0.12)
c1.SetBottomMargin(0.12)
c1.SetRightMargin(0.05)
c1.SetLogy()
histogram_base = TH1F("histogram_base", "", 100, -1., 1.)
histogram_base.SetTitle("")
histogram_base.SetStats(False)
histogram_base.SetMinimum(0.001)
histogram_base.SetMaximum(10.0)
