data = DoubleMuon_Run2015D
data['isData']=True
#get the TChains for each sample
for s in backgrounds+[data]:
s['chain'] = getChain(s,histname="")
#plots
plots = {\
'nVert': {'title':'nVert', 'name':'nVert', 'binning': [50,0,50], 'histo':{}},
}
#make plot in each sample:
for s in backgrounds:
for pk in plots.keys():
plots[pk]['histo'][s['name']] = getPlotFromChain(s['chain'], plots[pk]['name'], plots[pk]['binning'], cutString = preselection)
for s in [data]:
for pk in plots.keys():
plots[pk]['histo'][s['name']] = getPlotFromChain(s['chain'], plots[pk]['name'], plots[pk]['binning'], cutString = preselection+"&&"+dataCut)
for pk in plots.keys():
plots[pk]['sum'] = plots[pk]['histo'][backgrounds[0]['name']].Clone()
for b in backgrounds[1:]:
plots[pk]['sum'].Add(plots[pk]['histo'][b['name']])
#Some coloring
TTJets_50ns["color"]=ROOT.kRed
TTJets_25ns["color"]=ROOT.kRed
WJetsHTToLNu_25ns["color"]=ROOT.kGreen
WJetsToLNu_25ns["color"]=ROOT.kGreen
#get the TChains for each sample
for s in backgrounds:
s['chain'] = getChain(s, histname="")
#plots
plots = {\
'nTrueInt': {'title':'nTrueInt', 'name':'nTrueInt', 'binning': [50,0,50], 'histo':{}},
}
#make plot in each sample:
for s in backgrounds:
for pk in plots.keys():
plots[pk]['histo'][s['name']] = getPlotFromChain(
s['chain'],
plots[pk]['name'],
plots[pk]['binning'],
cutString=preselection)
for pk in plots.keys():
plots[pk]['sum'] = plots[pk]['histo'][backgrounds[0]['name']].Clone()
for b in backgrounds[1:]:
plots[pk]['sum'].Add(plots[pk]['histo'][b['name']])
#Some coloring
TTJets_Lep["color"] = ROOT.kBlack
WJetsToLNu["color"] = ROOT.kGreen
#TTVH["color"]=ROOT.kMagenta
DY["color"] = ROOT.kBlue
diBoson["color"] = ROOT.kRed
QCD_Mu5["color"] = ROOT.kCyan
# backgrounds = [TTJets_25ns, DY_25ns, singleTop_25ns, diBoson_25ns, WJetsHTToLNu_25ns]#, QCD]
for b in backgrounds:
b["isData"] = False
# get the TChains for each sample
for s in backgrounds:
s["chain"] = getChain(s, histname="")
# plots
plots = {"nTrueInt": {"title": "nTrueInt", "name": "nTrueInt", "binning": [50, 0, 50], "histo": {}}}
# make plot in each sample:
for s in backgrounds:
for pk in plots.keys():
plots[pk]["histo"][s["name"]] = getPlotFromChain(
s["chain"], plots[pk]["name"], plots[pk]["binning"], cutString=preselection
)
for pk in plots.keys():
plots[pk]["sum"] = plots[pk]["histo"][backgrounds[0]["name"]].Clone()
for b in backgrounds[1:]:
plots[pk]["sum"].Add(plots[pk]["histo"][b["name"]])
# Some coloring
TTJets_Lep["color"] = ROOT.kBlack
WJetsToLNu["color"] = ROOT.kGreen
# TTVH["color"]=ROOT.kMagenta
DY["color"] = ROOT.kBlue
diBoson["color"] = ROOT.kRed
QCD_Mu5["color"] = ROOT.kCyan
def loopAndFill(stacks, mode="loop"):
allSamples=[]
allSampleNames=[]
allPlots = []
usedBranches = []
for s in stacks:
usedBranches = list(set(usedBranches+s.usedBranches))
for l in s.stackLists:
for p in l:
allPlots.append(p)
if p.leaf:
if not p.leaf in usedBranches:
usedBranches.append(p.leaf)
if p.weightString and not p.weightString in usedBranches:
usedBranches.append(p.weightString)
else:
usedBranches = list(set(usedBranches+p.usedBranches))
if not p.sample in allSamples:
assert p.sample.has_key('dir') or p.sample.has_key('dirname'), "Missing key dir or dirname in sample %s"%repr(p.sample)
allSamples.append(p.sample)
if mode=='loop':
assert not any ([p.string for p in allPlots]), "Loop mode is %s but specified 'string' for: %s"%(mode, ", ".join([p.name for p in allPlots if p.string]))
if mode=='draw':
assert all([p.string for p in allPlots]), "Loop mode is %s but specified no 'string' for: %s"%(mode, ", ".join([p.name for p in allPlots if not p.string]))
print "Found",len(allSamples),'different samples:',", ".join(s['name'] for s in allSamples)
for s in allSamples:
cutStringForSample=[]
plotsPerCutForSample={}
# print s['name'], s.has_key('isData'), s.has_key('isData') and s['isData'], s.has_key('isData') and s['isData'] and s.has_key('dataCut')
for p in allPlots:
if p.sample==s:
cut = p.cut['string'] if not (s.has_key('isData') and s['isData'] and p.cut.has_key('dataCut')) else "("+p.cut['string']+")&&("+p.cut['dataCut']+")"
if not cut in cutStringForSample:
cutStringForSample.append(cut)
plotsPerCutForSample[cut]=[]
if not p in plotsPerCutForSample[cut]:
plotsPerCutForSample[cut].append(p)
s['plotsPerCutForSample'] = plotsPerCutForSample
for s in allSamples:
sampleScaleFac = 1 if not s.has_key('scale') else s['scale']
if sampleScaleFac!=1:
print "Using sampleScaleFac", sampleScaleFac ,"for sample",s["name"]
for b in s['bins']:
c = ROOT.TChain('Events' if not s.has_key('treeName') else s['treeName'])
counter=0
dir = s['dirname'] if s.has_key('dirname') else s['dir']
for f in getFileList(dir+'/'+b, maxN = -1 if not (s.has_key('small') and s['small']) else 1, histname=""):#, minAgeDPM, histname, xrootPrefix, maxN):
if not f[-5:]=='.root':continue
counter+=1
c.Add(f)
ntot = c.GetEntries()
print "Added ",counter,'files from sample',s['name'],'dir',dir,'bin',b,'ntot',ntot
switchOnBranches(c, usedBranches)
if ntot==0:
print "Warning! Found zero events in",s['name'],'bin',b," -> do nothing"
continue
if mode.lower()=='loop':
for ics, cutString in enumerate(s['plotsPerCutForSample'].keys()):
plotsToFill = s['plotsPerCutForSample'][cutString]
elistName = "eList_"+s['name']+'_'+b+'_'+str(ics)
elist = ROOT.TEventList(elistName)
c.Draw(">>"+elistName,cutString)
# print "elist",elist,elist.GetN(),cutString,'plots',plotsToFill
number_events = elist.GetN()# if not (s.has_key('small') and s['small']) else min(elist.GetN(), 100)
print "Reading: ", s["name"], b, "with",number_events,"events passing cutString", cutString, 'and will fill', len([p.name for p in plotsToFill]),'vars.'
for p in plotsToFill:
if not (p.cut.has_key('func') and p.cut['func']):
p.cut['func']=None
if p.TTreeFormula:
assert p.TTreeFormula and not (p.TTreeFormula==""), "Problem in TTreeFormula %s" % p.TTreeFormula
fString='ROOT.TTreeFormula("'+p.name+'","'+p.TTreeFormula+'",c)'
exec('p.ttreeFormula='+fString)
print "Created TTreeFormula:",fString
for i in range(0,number_events):
if (i%10000 == 0) and i>0 :
print i
c.GetEntry(elist.GetEntry(i))
for p in plotsToFill:
# print p.cut['func'], p.cut['func'](c)
if (not p.cut['func']) or p.cut['func'](c):
weight = c.GetLeaf(p.weightString).GetValue() if p.weightString else 1.
reWeight = p.weightFunc(c) if p.weightFunc else 1.
# print c, p.weightFunc, p.weightFunc(c), getVarValue(c, "nVert"), c.GetLeaf("nVert").GetValue(), c.nVert
if p.leaf:
val = getVarValue(c, p.leaf, p.ind)
# print "Fill leaf",p.leaf, p.ind, val, weight,sampleScaleFac
if p.TTreeFormula:
p.ttreeFormula.UpdateFormulaLeaves()
val = p.ttreeFormula.EvalInstance()
if p.func:
val = p.func(c)
# if val>170:print val, reWeight, weight, sampleScaleFac, p.leaf, p.ind, i, c.GetEntries(), elist.GetEntry(i),"x",c.GetLeaf('Jet_pt').GetValue(4), c.GetLeaf('met_pt').GetValue(), c.GetLeaf('lumi').GetValue(), c.GetLeaf('evt').GetValue()
if val<float('inf'):
p.histo.Fill(val, reWeight*weight*sampleScaleFac)
# print p.histo.GetName(), b, val, weight*sampleScaleFac, reWeight*weight*sampleScaleFac
elif mode.lower()=='draw':
for ics, cutString in enumerate(s['plotsPerCutForSample'].keys()):
plotsToFill = s['plotsPerCutForSample'][cutString]
print "Reading: ", s["name"], b, "with cutString", cutString, 'and will fill', len([p.name for p in plotsToFill]),'vars.'
for p in plotsToFill:
# print c, p.string, p.binning, cutString, p.weightString, p.binningIsExplicit, sampleScaleFac
tmp = getPlotFromChain(c, p.string, p.binning, cutString, p.weightString, binningIsExplicit=p.binningIsExplicit)
tmp.Scale(sampleScaleFac)
p.histo.Add(tmp)
# for ics, cutString in enumerate(s['plotsPerCutForSample'].keys()):
# plotsToFill = s['plotsPerCutForSample'][cutString]
# for p in plotsToFill:
# print c.GetEntries(), p.name,p.histo.Integral()
# c.GetListOfFiles().ls()
c.Reset()
del c
#do over-flow bins
for p in allPlots:
if p.overFlow and p.overFlow in [ "upper", "both"]:
nbins = p.histo.GetNbinsX()
p.histo.SetBinContent(nbins , p.histo.GetBinContent(nbins) + p.histo.GetBinContent(nbins + 1))
p.histo.SetBinError(nbins , sqrt(p.histo.GetBinError(nbins)**2 + p.histo.GetBinError(nbins + 1)**2))
if p.overFlow and p.overFlow in [ "lower", "both"]:
p.histo.SetBinContent(1 , p.histo.GetBinContent(0) + p.histo.GetBinContent(1))
p.histo.SetBinError(1 , sqrt(p.histo.GetBinError(0)**2 + p.histo.GetBinError(1)**2))
for s in stacks:
sumStackHistos(s)
def loopAndFill(stacks, mode="loop"):
allSamples = []
allSampleNames = []
allPlots = []
usedBranches = []
for s in stacks:
usedBranches = list(set(usedBranches + s.usedBranches))
for l in s.plotLists:
for p in l:
allPlots.append(p)
if p.leaf:
if not p.leaf in usedBranches:
usedBranches.append(p.leaf)
if p.weightString and not p.weightString in usedBranches:
usedBranches.append(p.weightString)
else:
usedBranches = list(set(usedBranches + p.usedBranches))
if not p.sample in allSamples:
assert p.sample.has_key('dir') or p.sample.has_key(
'dirname'
), "Missing key dir or dirname in sample %s" % repr(
p.sample)
allSamples.append(p.sample)
if mode == 'loop':
assert not any([
p.string for p in allPlots
]), "Loop mode is %s but specified 'string' for: %s" % (
mode, ", ".join([p.name for p in allPlots if p.string]))
if mode == 'draw':
assert all([
p.string for p in allPlots
]), "Loop mode is %s but specified no 'string' for: %s" % (
mode, ", ".join([p.name for p in allPlots if not p.string]))
print "Found", len(allSamples), 'different samples:', ", ".join(
s['name'] for s in allSamples)
for s in allSamples:
cutStringForSample = []
plotsPerCutForSample = {}
# print s['name'], s.has_key('isData'), s.has_key('isData') and s['isData'], s.has_key('isData') and s['isData'] and s.has_key('dataCut')
for p in allPlots:
if p.sample == s:
cut = p.cut['string'] if not (
s.has_key('isData') and s['isData']
and p.cut.has_key('dataCut')
) else "(" + p.cut['string'] + ")&&(" + p.cut['dataCut'] + ")"
if not cut in cutStringForSample:
cutStringForSample.append(cut)
plotsPerCutForSample[cut] = []
if not p in plotsPerCutForSample[cut]:
plotsPerCutForSample[cut].append(p)
s['plotsPerCutForSample'] = plotsPerCutForSample
for s in allSamples:
sampleScaleFac = 1 if not s.has_key('scale') else s['scale']
if sampleScaleFac != 1:
print "Using sampleScaleFac", sampleScaleFac, "for sample", s[
"name"]
bins = s['bins'] if s.has_key('bins') else ['default']
for b in bins:
treeName = 'Events' if not s.has_key('treeName') else s['treeName']
maxN = -1 if not (s.has_key('small') and s['small']) else 1
c = ROOT.TChain(treeName)
counter = 0
dir = s['dirname'] if s.has_key('dirname') else s['dir']
fileList = getFileList(
dir + '/' + b, maxN=maxN,
histname="") if s.has_key('bins') else [s['file']]
for f in fileList:
if not f[-5:] == '.root': continue
# counter+=1
# c.Add(f)
if checkRootFile(f, checkForObjects=[treeName]):
counter += 1
c.Add(f)
else:
print "File %s looks broken." % f
ntot = c.GetEntries()
print "Added ", counter, 'files from sample', s[
'name'], 'dir', dir, 'bin', b, 'ntot', ntot
switchOnBranches(c, usedBranches)
if ntot == 0:
print "Warning! Found zero events in", s[
'name'], 'bin', b, " -> do nothing"
continue
if mode.lower() == 'loop':
for ics, cutString in enumerate(
s['plotsPerCutForSample'].keys()):
plotsToFill = s['plotsPerCutForSample'][cutString]
elistName = "eList_" + s['name'] + '_' + b + '_' + str(ics)
elist = ROOT.TEventList(elistName)
c.Draw(">>" + elistName, cutString)
# print "elist",elist,elist.GetN(),cutString,'plots',plotsToFill
number_events = elist.GetN(
) # if not (s.has_key('small') and s['small']) else min(elist.GetN(), 100)
print "Reading: ", s[
"name"], b, "with", number_events, "events passing cutString", cutString, 'and will fill', len(
[p.name for p in plotsToFill]), 'vars.'
for p in plotsToFill:
if not (p.cut.has_key('func') and p.cut['func']):
p.cut['func'] = None
if p.TTreeFormula:
assert p.TTreeFormula and not (
p.TTreeFormula == ""
), "Problem in TTreeFormula %s" % p.TTreeFormula
fString = 'ROOT.TTreeFormula("' + p.name + '","' + p.TTreeFormula + '",c)'
exec('p.ttreeFormula=' + fString)
print "Created TTreeFormula:", fString
for i in range(0, number_events):
if (i % 10000 == 0) and i > 0:
print i
c.GetEntry(elist.GetEntry(i))
for p in plotsToFill:
# print p.cut['func'], p.cut['func'](c)
if (not p.cut['func']) or p.cut['func'](c):
weight = c.GetLeaf(p.weightString).GetValue(
) if p.weightString else 1.
reWeight = p.weightFunc(
c) if p.weightFunc else 1.
# print c, p.weightFunc, p.weightFunc(c), getVarValue(c, "nVert"), c.GetLeaf("nVert").GetValue(), c.nVert
if p.leaf:
val = getVarValue(c, p.leaf, p.ind)
# print "Fill leaf",p.leaf, p.ind, val, weight,sampleScaleFac
if p.TTreeFormula:
p.ttreeFormula.UpdateFormulaLeaves()
val = p.ttreeFormula.EvalInstance()
if p.func:
val = p.func(c)
# if val>170:print val, reWeight, weight, sampleScaleFac, p.leaf, p.ind, i, c.GetEntries(), elist.GetEntry(i),"x",c.GetLeaf('Jet_pt').GetValue(4), c.GetLeaf('met_pt').GetValue(), c.GetLeaf('lumi').GetValue(), c.GetLeaf('evt').GetValue()
if val < float('inf'):
p.histo.Fill(
val,
reWeight * weight * sampleScaleFac)
# print p.histo.GetName(), b, val, weight*sampleScaleFac, reWeight*weight*sampleScaleFac
elif mode.lower() == 'draw':
for ics, cutString in enumerate(
s['plotsPerCutForSample'].keys()):
plotsToFill = s['plotsPerCutForSample'][cutString]
print "Reading: ", s[
"name"], b, "with cutString", cutString, 'and will fill', len(
[p.name for p in plotsToFill]), 'vars.'
for p in plotsToFill:
print c, "String", p.string, p.binning, "Cut", cutString, p.weightString, p.binningIsExplicit, sampleScaleFac
tmp = getPlotFromChain(
c,
p.string,
p.binning,
cutString,
p.weightString,
binningIsExplicit=p.binningIsExplicit)
tmp.Scale(sampleScaleFac)
p.histo.Add(tmp)
# for ics, cutString in enumerate(s['plotsPerCutForSample'].keys()):
# plotsToFill = s['plotsPerCutForSample'][cutString]
# for p in plotsToFill:
# print c.GetEntries(), p.name,p.histo.Integral()
# c.GetListOfFiles().ls()
c.Reset()
del c
#do over-flow bins
for p in allPlots:
if p.overFlow and p.overFlow in ["upper", "both"]:
nbins = p.histo.GetNbinsX()
p.histo.SetBinContent(
nbins,
p.histo.GetBinContent(nbins) +
p.histo.GetBinContent(nbins + 1))
p.histo.SetBinError(
nbins,
sqrt(
p.histo.GetBinError(nbins)**2 +
p.histo.GetBinError(nbins + 1)**2))
if p.overFlow and p.overFlow in ["lower", "both"]:
p.histo.SetBinContent(
1,
p.histo.GetBinContent(0) + p.histo.GetBinContent(1))
p.histo.SetBinError(
1, sqrt(p.histo.GetBinError(0)**2 + p.histo.GetBinError(1)**2))
#sum stacks
for s in stacks:
sumStackHistos(s)
#normalize
for p in allPlots:
if p.normalizeTo:
t = p.normalizeTo.histo.Integral()
y = p.histo.Integral()
r = p.normalizeRef.histo.Integral() if p.normalizeRef else y
if r > 0:
p.histo.Scale(t / r)
stuff=[]
for name, varP, cutP, varC,cutC, binning in [
# ('MET_Inclusive', "MissingET.MET",'(1)', 'met_pt', '(1)', [45,0,450]),
# ('MET_GenPhoton80', "MissingET.MET",'(1)', 'met_pt', '(Sum$(genPartAll_pt>80&&genPartAll_pdgId==22)>=1)', [45,0,450]),
# ('MET_GenPhoton145', "MissingET.MET",'(1)', 'met_pt', '(Sum$(genPartAll_pt>145&&genPartAll_pdgId==22)>=1)', [45,0,450]),
# ('ptGenGamma_compMET', "Max$(Particle.PT*(Particle.Status==1&&abs(Particle.PID)==22))",'Max$(Particle.PT*(Particle.Status==1&&Particle.PID==22))>50', 'Max$(genPartAll_pt*( abs(genPartAll_pdgId)==22&&genPartAll_status==1 ))', 'Max$(genPartAll_pt*(genPartAll_pdgId==22&&genPartAll_status==1))>50', [50,0,300]),
# ('ptGenGamma', "Max$(Particle.PT*(Particle.Status==1&&abs(Particle.PID)==22))","(1)", 'Max$(genPartAll_pt*( abs(genPartAll_pdgId)==22&&genPartAll_status==1 ))',"(1)", [50,0,300]),
# ('HT', "Sum$(JetMA5.PT*(JetMA5.PT>30))",'Max$(Particle.PT*(Particle.Status==1&&Particle.PID==22))>50', 'Sum$(Jet_pt*(Jet_pt>30))', 'Max$(genPartAll_pt*(genPartAll_pdgId==22&&genPartAll_status==1))>50', [50,0,1000]),
# ('MET', "Max$(MissingET.MET)",'Max$(Particle.PT*(Particle.Status==1&&Particle.PID==22))>50', 'met_pt', 'Max$(genPartAll_pt*(genPartAll_pdgId==22&&genPartAll_status==1))>50', [100,0,500]),
('Jet0Pt', "Max$(JetMA5.PT*(JetMA5.PT>30))",'Max$(Particle.PT*(Particle.Status==1&&Particle.PID==22))>50', 'Max$(Jet_pt*(Jet_pt>30))', 'Max$(genPartAll_pt*(genPartAll_pdgId==22&&genPartAll_status==1))>50', [50,0,1000]),
# ('SumPt', "Sum$(Particle.PT*(Particle.Status==1))", 'met_sumEt', [100,0,3000]),
]:
h_c =getPlotFromChain(gJets, varC, binning, cutC,weight="weight")
h_mg=getPlotFromChain(mg_delphes_cms_13TeV, varP, binning,cutP,weight="(1)")
# h_p8=getPlotFromChain(p8_delphes_cms, varP, binning,cutP,weight="(1)")
# h_mg=getPlotFromChain(mg_hep_13TeV, varP, binning,cutP,weight="(1)")
# h_p8=getPlotFromChain(p8_hep, varP, binning,cutP,weight="(1)")
# h_p8.SetLineColor(ROOT.kRed)
h_c.SetLineColor(ROOT.kBlue)
# h_p8.SetMarkerColor(ROOT.kRed)
h_mg.SetMarkerColor(ROOT.kBlack)
h_c .SetMarkerColor(ROOT.kBlue)
# h_p8.SetMarkerSize(0)
h_mg.SetMarkerSize(0)
h_c .SetMarkerSize(0)
# h_p8.SetMarkerStyle(0)
h_mg.SetMarkerStyle(0)
h_c .SetMarkerStyle(0)
#p8_hep = ROOT.TChain("Delphes")
#for f in P8_hep:
# p8_hep.Add(f)
from StopsDilepton.tools.helpers import getChain, getObjDict, getEList, getVarValue, getPlotFromChain
from StopsDilepton.samples.cmgTuples_Spring15_mAODv2_25ns_0l_postProcessed import GJets
gJets = getChain(GJets, histname="")
stuff=[]
for name, varP, varC, binning in [
# ('MEx', "Sum$(Particle.Px*(Particle.Status==1))", 'met_genPt*cos(met_genPhi)', [100,-1,1]),
('ptGamma', "Max$(Particle.PT*(Particle.Status==1&&abs(Particle.PID)==22))", 'Max$(genPartAll_pt*( abs(genPartAll_pdgId)==22 ))', [100,0,500]),
# ('SumPt', "Sum$(Particle.PT*(Particle.Status==1))", 'met_sumEt', [100,0,3000]),
]:
h_c =getPlotFromChain(gJets, varC, binning,"1",weight="weight")
h_mg=getPlotFromChain(mg_hep, varP, binning,"1","1")
h_p8=getPlotFromChain(p8_hep, varP, binning,"1","1")
h_p8.SetLineColor(ROOT.kRed)
h_c.SetLineColor(ROOT.kBlue)
h_p8.SetMarkerColor(ROOT.kRed)
h_mg.SetMarkerColor(ROOT.kBlack)
h_c .SetMarkerColor(ROOT.kBlue)
h_p8.SetMarkerSize(0)
h_mg.SetMarkerSize(0)
h_c .SetMarkerSize(0)
h_p8.SetMarkerStyle(0)
h_mg.SetMarkerStyle(0)
h_c .SetMarkerStyle(0)
c1 = ROOT.TCanvas()
l=ROOT.TLegend(0.75,0.75,1.0,1.0)
