def do_fill(opts,fout,s,v,sel,trg,ref,KFWght=None):
trg,trg_orig = trigData(opts,s,trg)
# cut
cut,cutlabel = write_cuts(sel,trg,reftrig=ref,sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,KFWght=KFWght,trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut: %s%s%s: %s"%(blue,cutlabel,plain,cut))
# names
sample = s['pointer']
names = getNames(opts,s,v,sel,trg_orig,ref)
wpars = weightInfo(opts.weight,KFWght)
# containers
canvas = TCanvas("cfill","cfill",1200,800)
fout.Delete(names['hist'])
h = TH1F(names['hist'],names['hist-title'],int(v['nbins_x']),float(v['xmin']),float(v['xmax']))
h.Sumw2()
# do actual filling
inroot('%s.draw("%s","%s","%s")'%(sample,h.GetName(),v['root'],cut))
if opts.debug: l3("%sFilled: %40s(N=%9d, Int=%9d)%s"%(yellow,h.GetName(),h.GetEntries(),h.Integral(),plain))
# write histogram to file
gDirectory.cd('%s:/'%fout.GetName())
path = "%s/%s/%s"%('plots',wpars,names['path-hist'])
makeDirsRoot(fout,path)
gDirectory.cd(path)
h.Write(h.GetName(),TH1.kOverwrite)
gDirectory.cd('%s:/'%fout.GetName())
# clean
h.Delete()
canvas.Close()
trg = dc(trg_orig)
def getKFWght(opts,loadedSamples,sel,trg):
inroot('float nDat=0.0, nQCD=0.0, nBkg=0.0;')
inroot('TH1F *hDat = new TH1F("hDat","hDat",1,0,1);')
inroot('TH1F *hQCD = new TH1F("hQCD","hQCD",1,0,1);')
inroot('TH1F *hBkg = new TH1F("hBkg","hBkg",1,0,1);')
### LOOP over samples
for s in loadedSamples:
### Skip some
if any([x in s['tag'] for x in ['JetMon','VBF','GluGlu']]): continue
if opts.debug: l3("%sSample: %s%s"%(purple,s['tag'],plain))
### Clean some
if opts.debug and 'KFAC' in opts.weight[1]: l3("Option specified k-factor and puWt ignored in k-factor calculation.")
opts.weightlocal = dc(opts.weight)
opts.weightlocal[1] = list(set(opts.weight[1])-set(['KFAC','PU']))
### Get cut and weight
trg,trg_orig = trigData(opts,s,trg)
cut = write_cuts(sel,trg,sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weightlocal,trigequal=trigTruth(opts.usebool))[0]
trg = dc(trg_orig)
if opts.debug: l3("Cut: %s"%cut)
### Data
if 'Data' in s['tag'] or 'DataV' in s['tag']:
inroot('%s.draw("%s","%s","%s")'%(s['pointer'],ROOT.hDat.GetName(),"0.5",cut))
### QCD
elif 'QCD' in s['tag']:
inroot('%s.draw("%s","%s","%s")'%(s['pointer'],ROOT.hQCD.GetName(),"0.5",cut))
### Bkg
else:
inroot('%s.draw("%s","%s","%s")'%(s['pointer'],ROOT.hBkg.GetName(),"0.5",cut))
print "Data: %8.2f | Bkg: %8.2f | QCD: %8.2f"%(ROOT.hDat.Integral(),ROOT.hBkg.Integral(),ROOT.hQCD.Integral())
### finish
KFWght = (ROOT.hDat.Integral()-ROOT.hBkg.Integral())/ROOT.hQCD.Integral()
inroot('delete hDat; delete hQCD; delete hBkg;')
if opts.debug: l2("KFWght calculated at: %f"%KFWght)
return KFWght
def printSelTrg(opts, KFWghts):
from write_cuts import write_cuts
l1("Listing cutstrings for control:")
for s in opts.selection:
for t in opts.trigger:
KFWght = KFWghts[('-'.join(sorted(s)), '-'.join(t))]
l2("Sel: %20s, Trg: %20s" % ("(%s)" % s, "(%s)" % t))
cutsel = write_cuts(
s, [],
sample='Data' if opts.fileformat == '1' else 'DataA',
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool))[0]
cutsel2 = write_cuts(s, [],
sample='QCD250',
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool))[0]
cuttrg = write_cuts([],
t,
sample='QCD250',
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool))[0]
cuttrgdat = write_cuts(
[],
trigData(opts, "", t)[0],
sample='Data' if opts.fileformat == '1' else 'DataA',
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool))[0]
l3("%s Sel: (e.g. Data) %s %s" % (Red, plain, cutsel))
l3("%s Sel: (e.g. QCD250) %s %s" % (Red, plain, cutsel2))
l3("%s Trg: (e.g. QCD250) %s %s" % (Purple, plain, cuttrg))
l3("%sTrgDat: (e.g. Data) %s %s" % (Purple, plain, cuttrgdat))
print
def mkFitFlatTree(opts,s,sel,trg):
# info
jsoninfo = json.loads(filecontent(opts.jsoninfo))
jsonsamp = json.loads(filecontent(opts.jsonsamp))
jsonvars = json.loads(filecontent(opts.jsonvars))
ismc = True if not 'Data' in s['tag'] else False
# prepare
tags = {"NOM":"sNOM","VBF":"sVBF","TPN":"sTPN","TPV":"sTPV"}
tag = tags[trg[0]]
nfin = s['fname']
nfout = nfin.replace('.root','_%s.root'%tag)
if not os.path.exists(opts.destination): makeDirs(opts.destination)
fin = TFile.Open(opts.globalpath+nfin,"read")
fout = TFile.Open(opts.destination+nfout,"recreate")
l2("Working for %s"%s['tag'])
l3("File in : %s"%nfin)
l3("File out: %s"%nfout)
# process
fin.cd()
tin = fin.Get("Hbb/events")
hpass = fin.Get("Hbb/TriggerPass")
tin.SetBranchStatus("*",0)
for b in list(set(sum([x['bare'].split(',') for x in jsonvars['variables'].itervalues() if not "-"==x['bare']],[]))):
tin.SetBranchStatus(b,1)
if ismc:
for b in ["puWt","trigWtNOM","trigWtVBF"]:
tin.SetBranchStatus(b,1)
# cuts
cut,cutlabel = write_cuts(sel,trg,reftrig=["None"],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s"%(s['tag'],blue,cutlabel,plain,cut))
# cut = ""
# if tag=="NOM":
# cut ="selNOM && (triggerResult[5] || triggerResult[7]) && nLeptons==0"
# elif tag=="VBF":
# cut = "selVBF && triggerResult[9] && (!(selNOM && (triggerResult[0] || triggerResult[1]))) && nLeptons==0"
# else: sys.exit(Red+"Tag type unclear: NOM/VBF. Exiting."+plain)
# if opts.debug: l3("Cut %s: %s%s%s"%(s['tag'],blue,cut,plain))
# process
fout.cd()
if hpass: hpass.Write("TriggerPass")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("%s:/%s"%(fout.GetName(),"Hbb"))
tout = tin.CopyTree(cut)
l3("Events: %d"%tout.GetEntries())
tout.Write()
# cleaning
fout.Close()
fin.Close()
def mkFitFlatTree(opts,s,sel,trg):
# info
jsoninfo = json.loads(filecontent(opts.jsoninfo))
jsonsamp = json.loads(filecontent(opts.jsonsamp))
ismc = True if not 'Data' in s['tag'] else False
# prepare
tag = 'VBF' if 'VBF' in trg else 'NOM'
nfin = s['fname']
nfout = nfin.replace('flatTree','Fit').replace('.root','_sel%s.root'%tag)
if not os.path.exists(opts.destination): makeDirs(opts.destination)
fin = TFile.Open(opts.globalpath+nfin,"read")
fout = TFile.Open(opts.destination+nfout,"recreate")
l2("Working for %s"%s['tag'])
l3("File in : %s"%nfin)
l3("File out: %s"%nfout)
# process
fin.cd()
tin = fin.Get("Hbb/events")
hpass = fin.Get("Hbb/TriggerPass")
tin.SetBranchStatus("*",0)
for b in ["mvaNOM","mvaVBF","selNOM","selVBF","mvaZ","dPhibb","mbbReg","mbb","nLeptons","triggerResult","jetBtag","b1"]:
tin.SetBranchStatus(b,1)
if ismc:
for b in ["puWt","trigWtNOM","trigWtVBF"]:
tin.SetBranchStatus(b,1)
# cuts
cut,cutlabel = write_cuts(sel,trg,reftrig=["None"],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s"%(s['tag'],blue,cutlabel,plain,cut))
# cut = ""
# if tag=="NOM":
# cut ="selNOM && (triggerResult[5] || triggerResult[7]) && nLeptons==0"
# elif tag=="VBF":
# cut = "selVBF && triggerResult[9] && (!(selNOM && (triggerResult[0] || triggerResult[1]))) && nLeptons==0"
# else: sys.exit(Red+"Tag type unclear: NOM/VBF. Exiting."+plain)
# if opts.debug: l3("Cut %s: %s%s%s"%(s['tag'],blue,cut,plain))
# process
fout.cd()
if hpass: hpass.Write("TriggerPass")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("%s:/%s"%(fout.GetName(),"Hbb"))
tout = tin.CopyTree(cut)
l3("Events: %d"%tout.GetEntries())
tout.Write()
# cleaning
fout.Close()
fin.Close()
def mkPDFFlatTree(opts,s,sel,trg):
# info
jsoninfo = json.loads(filecontent(opts.jsoninfo))
jsonsamp = json.loads(filecontent(opts.jsonsamp))
ismc = True if not 'Data' in s['tag'] else False
# prepare
tag = 'VBF' if 'VBF' in trg else 'NOM'
makeDirs(opts.destination)
nfin = s['fname']
nfout = nfin.replace('flatTree','%sFlatTree'%opts.tag).replace('.root','_%s.root'%tag)
fin = TFile.Open(opts.globalpath+nfin,"read")
fout = TFile.Open(opts.destination+nfout,"recreate")
l2("Working for %s, renaming with %s"%(s['tag'],opts.tag))
l3("File in : %s"%nfin)
l3("File out: %s"%nfout)
# process
fin.cd()
tin = fin.Get("Hbb/events")
# hpass = fin.Get("Hbb/TriggerPass")
tin.SetBranchStatus("*",0)
for b in ["mvaNOM","mvaVBF","selNOM","selVBF","dPhibb","mbbReg","mbb","nLeptons","triggerResult","pdfX1","pdfX2","pdfID1","pdfID2","pdfQ"]:
tin.SetBranchStatus(b,1)
if ismc:
for b in ["puWt","trigWtNOM","trigWtVBF"]:
tin.SetBranchStatus(b,1)
# cuts
cut,cutlabel = write_cuts(sel,trg,reftrig=["None"],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s"%(s['tag'],blue,cutlabel,plain,cut))
# cut = ""
# if tag=="NOM":
# cut ="selNOM && (triggerResult[5] || triggerResult[7]) && nLeptons==0"
# elif tag=="VBF":
# cut = "selVBF && triggerResult[9] && (!(selNOM && (triggerResult[0] || triggerResult[1]))) && nLeptons==0"
# else: sys.exit(Red+"Tag type unclear: NOM/VBF. Exiting."+plain)
# if opts.debug: l3("Cut %s: %s%s%s"%(s['tag'],blue,cut,plain))
# process
fout.cd()
# hpass.Write("TriggerPass")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("%s:/%s"%(fout.GetName(),"Hbb"))
tout = tin.CopyTree(cut,"",opts.nentries)
l3("Events: %d"%tout.GetEntries())
tout.Write()
# cleaning
fout.Close()
fin.Close()
def convertSamples(opts, samples):
l1("Converting samples:")
# remove files if reformat called
if opts.reformat:
for sample in samples.itervalues():
sname = opts.globalpath + '/' + sample[
'fname'][:-5] + '_reformatted.root'
if os.path.exists(sname): os.remove(sname)
sys.exit(
red +
"Reformat function was called. All reformatted trees were removed. Rerun for more converting, but REMOVE the reformat flag (else you'll keep deleting the files)."
+ plain)
elif opts.preselect:
for sample in samples.itervalues():
sname = opts.globalpath + '/' + sample[
'fname'][:-5] + '_preselected.root'
if os.path.exists(sname): os.remove(sname)
sys.exit(
red +
"Preselect function was called. All preselected trees were removed. Rerun for more converting, but REMOVE the preselect flag (else you'll keep deleting the files)."
+ plain)
# actually reformat/preselect trees (one at a time to avoid memory filling up)
for sample in samples.itervalues():
if opts.treepreselection == []:
sname = opts.globalpath + '/' + sample[
'fname'][:-5] + '_reformatted.root'
if (not os.path.exists(sname)):
inroot('reformat("%s","%s",variables,%s,"%s")' %
(opts.globalpath, sample['fname'], str(
opts.fileformat), opts.source))
sys.exit(
red +
"Sample reformat function was needed first. Rerun for actual plotting (or more converting)."
+ plain)
else:
sname = opts.globalpath + '/' + sample[
'fname'][:-5] + '_preselected.root'
if (not os.path.exists(sname)):
cut, label = write_cuts(opts.treepreselection, [], [], [],
sample=sample['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
trigequal=trigTruth(opts.usebool),
varskip=opts.skip)
inroot('preselect("%s","%s",variables,"%s","%s")' %
(opts.globalpath, sample['fname'], cut, opts.source))
sys.exit(
red +
"Sample preselect function was needed first. Rerun for actual plotting (or more converting)."
+ plain)
def do_fill(opts,fout,s,v,sel,trg,ref,KFWght=None,skipWght=None):
# info
l2("Filling for %s"%v['var'])
# containers
cuts = {}
cutlabels = {}
names = {}
canvas = TCanvas("cfill","cfill",1200,1000)
# trg
trg, trg_orig = trigData(opts,s,trg)
# names
jsoninfo = json.loads(filecontent(opts.jsoninfo))
names['global'] = getNames(opts,s,v,sel,trg_orig,ref)
keepMapInfo = None
if skipWght==True:
keepMapInfo = [x for x in opts.weight[1] if (x[0:3]=='MAP' or x[0:3]=='FUN' or x[0:3]=='COR')]
opts.weight[1] = [dc(x) for x in opts.weight[1] if not (x[0:3]=='MAP' or x[0:3] == 'FUN' or x[0:3]=='COR')]
wpars = weightInfo(opts.weight,KFWght)
# TEffi object
TEffi = TEffiType(v)
# looping over different tags
for tag in ['Num','Den']:
# cuts
cuts[tag],cutlabels[tag] = write_cuts(sel,trg if tag=='Num' else ['None'],reftrig=ref,sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,KFWght=KFWght,varskip=opts.skip+[v['root']],trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut %s: %s%s%s: %s"%(tag,blue,cutlabels[tag],plain,cuts[tag]))
# loading/filling
names[tag] = getNames(opts,s,v,sel,trg_orig if tag=='Num' else ['None'],ref,tag)
if not s['tag'] in TEffi.h[tag] or TEffi.h[tag][s['tag']]==None:
fout.Delete(names[tag]['hist'])
TEffi.fill(s['pointer'],s['tag'],tag,names[tag],cuts[tag])
if opts.debug: l3("%sFilled: %40s(N=%9d, Int=%9d)%s"%(yellow,TEffi.h[tag][s['tag']].GetName(),TEffi.h[tag][s['tag']].GetEntries(),TEffi.h[tag][s['tag']].Integral(),plain))
# consider ratio
tag = 'Rat'
names[tag] = getNames(opts,s,v,sel,trg_orig,ref,tag)
TEffi.effi(names[tag],jsoninfo['colours'][s['tag']],markerStyle(s['tag'],jsoninfo['markers'][s['tag']],opts))
# write histogram to file
path = "%s/%s/%s"%('turnonCurves',wpars,names['global']['path-turnon'])
TEffi.write(fout,path)
# clean
#TEffi.delete()
canvas.Close()
trg = dc(trg_orig)
if skipWght==True:
opts.weight[1] += keepMapInfo
def do_fill(opts, fout, s, v, sel, trg, ref, KFWght=None):
trg, trg_orig = trigData(opts, s, trg)
# cut
cut, cutlabel = write_cuts(sel,
trg,
reftrig=ref,
sample=s['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool))
if opts.debug: l3("Cut: %s%s%s: %s" % (blue, cutlabel, plain, cut))
# names
sample = s['pointer']
names = getNames(opts, s, v, sel, trg_orig, ref)
wpars = weightInfo(opts.weight, KFWght)
# containers
canvas = TCanvas("cfill", "cfill", 1200, 800)
fout.Delete(names['hist'])
h = TH1F(names['hist'], names['hist-title'], int(v['nbins_x']),
float(v['xmin']), float(v['xmax']))
h.Sumw2()
# do actual filling
inroot('%s.draw("%s","%s","%s")' % (sample, h.GetName(), v['root'], cut))
if opts.debug:
l3("%sFilled: %40s(N=%9d, Int=%9d)%s" %
(yellow, h.GetName(), h.GetEntries(), h.Integral(), plain))
# write histogram to file
gDirectory.cd('%s:/' % fout.GetName())
path = "%s/%s/%s" % ('plots', wpars, names['path-hist'])
makeDirsRoot(fout, path)
gDirectory.cd(path)
h.Write(h.GetName(), TH1.kOverwrite)
gDirectory.cd('%s:/' % fout.GetName())
# clean
h.Delete()
canvas.Close()
trg = dc(trg_orig)
def mkBDTcorrelations():
mp = parser()
opts,fout,samples = main(mp,False,False,True)
sels = ['NOM','VBF']
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
selsamples = INTERNALpicksamples(opts,jsons)
can = TCanvas("main","main",650,600)
hProf = INTERNALhistograms(opts,sels,jsons)
#INTERNALcanvases(opts)
l1("Creating profiles")
if not opts.read:
for isel,sel in enumerate(sels):
ssel = [s for s in selsamples if sel in s['fname']]
for s in ssel:
l2("Running for %s"%s['tag'])
cut,cutlabel = write_cuts(["None"],["None"],reftrig=["None"],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.complexWghts[(sel,'old')],trigequal=trigTruth(opts.usebool))
#cut = re.findall('\*.*',cut)[0][2:-1].replace('pu','ev.pu').replace('trig','ev.trig')
if opts.debug: l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s"%(s['tag'],blue,cutlabel,plain,cut))
cutextra = "mbbReg[%d]>=80. && mbbReg[%d]<=200."%(1 if sel=='NOM' else 2, 1 if sel=='NOM' else 2)
for v in [jsons['vars']['variables'][vv] for vv in opts.variable]:
if sel=='NOM' and '[2]' in v['root']: continue
if sel=='VBF' and '[1]' in v['root']: continue
if 'mva' in v and not sel in v: continue
s['tree'].Draw("%s:%s>>+%s"%(v['root'],"mva%s"%sel,hProf[(sel,v['var'],'BDT','QCD' if 'QCD' in s['fname'] else 'DAT')].GetName()),TCut(cutextra)*TCut(cut),"prof")
if 'mbbReg' in v['var']: continue
s['tree'].Draw("%s:%s>>+%s"%(v['root'],"mbbReg[%d]"%(1 if sel=='NOM' else 2),hProf[(sel,v['var'],'mbbReg','QCD' if 'QCD' in s['fname'] else 'DAT')].GetName()),TCut(cutextra)*TCut(cut),"prof")
else:
for k in hProf.iterkeys():
hProf[k] = fout.Get("h%s_sel%s_%s_%s"%(k[3],k[0],k[1],k[2]))
k = list(set([x[0:3] for x in hProf.iterkeys()]))
for ik in k:
low = min(hProf[(ik[0],ik[1],ik[2],'QCD')].GetBinContent(hProf[(ik[0],ik[1],ik[2],'QCD')].GetMinimumBin()),hProf[(ik[0],ik[1],ik[2],'DAT')].GetBinContent(hProf[(ik[0],ik[1],ik[2],'DAT')].GetMinimumBin()))
hig = max(hProf[(ik[0],ik[1],ik[2],'QCD')].GetBinContent(hProf[(ik[0],ik[1],ik[2],'QCD')].GetMaximumBin()),hProf[(ik[0],ik[1],ik[2],'DAT')].GetBinContent(hProf[(ik[0],ik[1],ik[2],'DAT')].GetMaximumBin()))
med = hProf[(ik[0],ik[1],ik[2],'DAT')].GetMean(2)
dif = hig-low
setlow = med - 1.6*dif
sethig = med + 1.6*dif
if not 'cos' in ik[1]:
setlow = max(setlow,0)
limits = {'dEtaqq1':[2,7,2,7],'dPhiqq1':[0,3,0,3],'jetBtag00':[0.5,1.2,0.8,1.0],'jetBtag01':[0.0,1.2,0.55,0.75],'jetQGLNOM0':[0,1,0.5,0.65],'jetQGLNOM1':[0,1,0.35,0.55],'jetQGLNOM2':[0,1,0.5,0.7],'jetQGLNOM3':[0,1,0.5,0.7],'mqq1':[0,2500,500,800],'mbbReg1':[115,145,115,145],'cosTheta1':[-0.35,0.35,-0.2,0.2],'jetQGLVBF0':[0,1,0.4,0.55],'jetQGLVBF1':[0,1,0.3,0.5],'jetQGLVBF2':[0,1,0.55,0.75],'jetQGLVBF3':[0,1,0.5,0.7],'mqq2':[0,2500,1000,1300],'mbbReg2':[115,145,115,145],'cosTheta2':[-0.35,0.35,-0.2,0.2],'dEtaqq2':[2,7,2,7],'dPhiqq2':[0,3,0,3],'softHt':[0,100,25,50],'softN2':[0,10,4,7]} #[3,7,4,6], [0,3,1,2] [0,3,1.5,2.5]
if ik[1] in limits:
if ik[2]=='BDT':
setlow = limits[ik[1]][0]
sethig = limits[ik[1]][1]
else:
setlow = limits[ik[1]][0]#2]
sethig = limits[ik[1]][1]#3]
# if 'jetBtag01' in ik[1] and ik[0]=='VBF' and ik[2]=='mbbReg':
# setlow = 0.4
# sethig = 0.55
hProf[(ik[0],ik[1],ik[2],'DAT')].GetYaxis().SetRangeUser(setlow,sethig)
hProf[(ik[0],ik[1],ik[2],'DAT')].GetYaxis().SetTitleOffset(1.4)
hProf[(ik[0],ik[1],ik[2],'DAT')].GetXaxis().SetTitleOffset(1.0)
hProf[(ik[0],ik[1],ik[2],'DAT')].GetYaxis().SetNdivisions(507)
hProf[(ik[0],ik[1],ik[2],'DAT')].GetXaxis().SetNdivisions(507)
hProf[(ik[0],ik[1],ik[2],'DAT')].Draw("axis")
h = INTERNALgraph(hProf[(ik[0],ik[1],ik[2],'DAT')])
h.SetMarkerStyle(20)
h.SetMarkerSize(0.8)
h.SetMarkerColor(kBlack)
h.SetLineColor(kBlack)
h.SetFillStyle(0)
h.Draw("same pz")
g = INTERNALgraph(hProf[(ik[0],ik[1],ik[2],'QCD')])
# hProf[(ik[0],ik[1],ik[2],'QCD')].SetMarkerStyle(25)
# hProf[(ik[0],ik[1],ik[2],'QCD')].SetMarkerColor(kBlue)
# hProf[(ik[0],ik[1],ik[2],'QCD')].Draw("same e")
g.SetMarkerStyle(25)
g.SetMarkerColor(kBlue)
g.SetLineColor(kBlue)
g.SetFillStyle(0)
g.Draw("same pz")
leg = TLegend(0.62,0.75,0.9,0.92,"%s selection"%(ik[0].strip('sel')))
leg.SetFillStyle(-1)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.045)
#leg.AddEntry(hProf[(ik[0],ik[1],ik[2],'DAT')],'Data')
#leg.AddEntry(hProf[(ik[0],ik[1],ik[2],'QCD')],'QCD')
leg.AddEntry(h,'Data','LP')
leg.AddEntry(g,'QCD','LP')
leg.SetY1(leg.GetY2()-(leg.GetNRows()+1)*0.05)
leg.Draw()
can.SaveAs("plots/%s.png"%hProf[(ik[0],ik[1],ik[2],'DAT')].GetName().replace('hDAT','h'))
can.SaveAs("plots/%s.pdf"%hProf[(ik[0],ik[1],ik[2],'DAT')].GetName().replace('hDAT','h'))
fout.cd()
for h in hProf.itervalues():
h.Write(h.GetName(),TH1.kOverwrite)
# clean
fout.Close()
def get1DMap(opts,fout,samples,variables,sel,trg,ref,vx):
# info
l1("Creating 1D cors for (%s):"%(vx[0]))
print "+ (sel,trg,ref): (%s,%s,%s)"%(sel,trg,ref)
jsoninfo = json.loads(filecontent(opts.jsoninfo))
groups = list(set([jsoninfo['groups'][x['tag']] for x in samples]))
samplesbygroup = {}
for group in groups:
samplesbygroup[group] = [sample for sample in samples if jsoninfo['groups'][sample['tag']]==group]
ratios = []
if 'JetMon' in groups and 'QCD' in groups:
ratios += ['JetMon-QCD']
# storage
gDirectory.cd("%s:/"%fout.GetName())
for group in groups:
makeDirsRoot(fout,'1DMaps/%s'%group)
# calculate
xvals = array('f',[float(x) for x in vx[1].split("#")])
maps = {}
cuts = {}
inroot('TTree *t = 0;')
# To Save
canvas = TCanvas("cmap","cmap",1800,1200)
canvas.cd()
gPad.SetGrid(0,0)
gPad.SetRightMargin(0.14)
gStyle.SetPaintTextFormat("6.2f")
# LOOP over ALL GROUPS
for group in groups:
l2("Filling for group: %s%s%s"%(purple,group,plain))
maps[group] = {}
cuts[group] = {}
for tag in ['Num','Den','Rat']:
trg,trg_orig = trigData(opts,'',trg)
mapname = "1DMap_%s-%s_s%s-t%s-r%s-d%s_%s"%(group,tag,'-'.join(sorted(sel)),'-'.join(trg_orig),'-'.join(ref),'-'.join(trg),vx[0])
maptitle = "%s;%s;Scale factor"%(mapname,variables[vx[0]]['title_x'])
trg = dc(trg_orig)
maps[group][tag] = fout.FindObjectAny(mapname)
if (not maps[group][tag]) or (not len(xvals)-1==maps[group][tag].GetXaxis().GetNbins()):
maps[group][tag] = TH1F(mapname,maptitle,len(xvals)-1,xvals)
maps[group][tag].Sumw2()
## LOOP over ALL SAMPLES
for s in sorted(samplesbygroup[group],key=lambda x:('QCD' in x['tag'],not 'WJets' in x['tag'],jsoninfo['crosssections'][x['tag']])):
if tag=='Rat': continue
l3("Filling for sample: %s%s (%s)%s"%(cyan,s['tag'],tag,plain))
trg,trg_orig = trigData(opts,s,trg)
inroot('t = (TTree*)%s.gett();'%s['pointer'])
cuts[group][tag] = write_cuts(sel,trg if tag=='Num' else [],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,reftrig=ref,trigequal=trigTruth(opts.usebool),weight=opts.weight)[0] #,varskip=[variables[vx[0]]['root'],variables[vy[0]]['root']]
if opts.debug: print yellow,cuts[group][tag],plain
inroot('t->Draw("%s>>+%s",TCut("%s"));'%(variables[vx[0]]['root'],maps[group][tag].GetName(),cuts[group][tag]))
trg = dc(trg_orig)
else:
l3("Loaded from file for group: %s%s%s"%(cyan,group,plain))
## END LOOP over ALL SAMPLES
# to save
path = '%s/../trigger/plots/%s/1DMaps/%s'%(basepath,fout.GetName().split('/')[-1][:-5],group)
makeDirs(path)
# ratio
maps[group]['Rat'].Divide(maps[group]['Num'],maps[group]['Den'],1.0,1.0,'B')
#$ maps[group]['Rat'] = TEfficiency(maps[group]['Num'],maps[group]['Den'])
maps[group]['Rat'].SetName(mapname)
maps[group]['Rat'].SetTitle(maptitle)
# save
gDirectory.cd('%s:/1DMaps/%s'%(fout.GetName(),group))
##
for tag in ['Num','Den','Rat']:
if not tag in maps[group]: continue
maps[group][tag].Write(maps[group][tag].GetName(),TH1.kOverwrite)
gPad.SetRightMargin(0.14)
maps[group][tag].SetTitleOffset(1.0,"Y")
maps[group][tag].SetMarkerSize(maps[group][tag].GetMarkerSize()*0.75)
maps[group][tag].Draw("text45,error")
canvas.SaveAs('%s/%s.png'%(path,maps[group][tag].GetName()))
canvas.SaveAs('%s/%s.pdf'%(path,maps[group][tag].GetName()))
l3("Written %s map to (eog %s/%s.png)"%(tag,path,maps[group][tag].GetName()))
# END LOOP over ALL GROUPS
# FOCUS ON RATIO MAPS JetMon / QCD
gDirectory.cd("%s:/"%fout.GetName())
for ratio in ratios:
# store
makeDirsRoot(fout,'1DMaps/%s'%ratio)
maps[ratio] = {}
l2("Getting ratio for: %s%s%s"%(purple,ratio,plain))
# create
trg,trg_orig = trigData(opts,'',trg)
mapname = "1DMap_%s-%s_s%s-t%s-r%s-d%s_%s"%(ratio,'Rat','-'.join(sorted(sel)),'-'.join(trg_orig),'-'.join(ref),'-'.join(trg),vx[0])
maptitle = "%s;%s;Scale factor"%(mapname,variables[vx[0]]['title_x'])
trg = dc(trg_orig)
maps[ratio]['Rat'] = TH1F(mapname,maptitle,len(xvals)-1,xvals)
maps[ratio]['Rat'].Sumw2()
#$ maps[ratio]['Rat'].Divide(maps[ratio.split('-')[0]]['Rat'].GetPaintedHistogram(),maps[ratio.split('-')[1]]['Rat'].GetPaintedHistogram())
maps[ratio]['Rat'].Divide(maps[ratio.split('-')[0]]['Rat'],maps[ratio.split('-')[1]]['Rat'])
# plot
canvas.cd()
maps[ratio]['Rat'].SetTitleOffset(1.0,"Y")
maps[ratio]['Rat'].SetMarkerSize(maps[ratio]['Rat'].GetMarkerSize()*0.75)
maps[ratio]['Rat'].Draw('text45,error')
# save
gDirectory.cd('%s:/1DMaps/%s'%(fout.GetName(),ratio))
maps[ratio]['Rat'].Write(maps[ratio]['Rat'].GetName(),TH1.kOverwrite)
path = "%s/../trigger/plots/%s/1DMaps/%s"%(basepath,fout.GetName().split('/')[-1][:-5],ratio)
makeDirs(path)
for tag in ['Num','Den','Rat']:
if not tag in maps[ratio]: continue
canvas.SaveAs("%s/%s.png"%(path,maps[ratio][tag].GetName()))
canvas.SaveAs("%s/%s.pdf"%(path,maps[ratio][tag].GetName()))
l2("Written map to (eog %s/%s.png)"%(path,maps[ratio]['Rat'].GetName()))
# 2d copy
binsx = []
for i in range(1,maps[ratio]['Rat'].GetNbinsX()+2): binsx += [maps[ratio]['Rat'].GetXaxis().GetBinLowEdge(i)]
#print binsx
binsx_array = array('f',binsx)
binsy_array = array('f',[0.0,1.0])
ratio2d = TH2F('ratio2D','ratio2D',len(binsx_array)-1,binsx_array,len(binsy_array)-1,binsy_array)
for i in range(maps[ratio]['Rat'].GetNbinsX()+2):
#print maps[ratio]['Rat'].GetXaxis().GetBinLowEdge(i)
#print maps[ratio]['Rat'].GetBinContent(i)
ratio2D.SetBinContent(i,1,maps[ratio]['Rat'].GetBinContent(i))
ratio2D.SetBinError(i,1,maps[ratio]['Rat'].GetBinError(i))
#plot
canvas.cd()
ratio2D.SetTitle('%s;%s;%s'%('',maps[ratio]['Rat'].GetXaxis().GetTitle(),'Scale factor'))
ratio2D.Draw('colz,error,text45')
canvas.SaveAs("%s/2D%s.png"%(path,maps[ratio][tag].GetName()))
canvas.SaveAs("%s/2D%s.pdf"%(path,maps[ratio][tag].GetName()))
l2("Written map to (eog %s/2D%s.png)"%(path,maps[ratio]['Rat'].GetName()))
# clean
canvas.Close()
def datamc():
# options
mp = parser()
opts,fout,samples,variables = main.main(mp,False,True,True)
# root setup
ROOTsetup()
eps = 0.0001
# samples / variables
ji, jv, js, Lsamples = loadSamples(opts,samples)
Lvariables = {k:v for (k,v) in variables.iteritems() if k in opts.variable}
# canvas
can = TCanvas("c","c",900,750)
can.cd()
# histos
histos = hists(Lsamples,Lvariables,opts.selection)
stacks = {}
##################################################
l1("Filling histograms")
for s in opts.selection:
for t in opts.trigger:
# cms paves
pcms1,pcms2 = FormatCMSPaves(opts,s)
#### # cuts
#### cut,cutlabel = write_cuts(s,t,reftrig=["None"],sample=Lsamples[Lsamples.keys()[0]]['i']['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
#### cut1,cut2 = cut.split(' * ')[0][1:],cut.split(' * ')[1][:-1]
##################################################
# sample loop
for sn,si in sorted(Lsamples.iteritems()):
l2("Sample: %s"%sn)
st = si['i']['tag']
sg = si['g']
ca,calabel = write_cuts(s,t,reftrig=["None"],sample=st,jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
ca1,ca2 = ca.split(' * ')[0][1:],ca.split(' * ')[1][:-1]
n = si['t'].GetEntries()
print ca2
# variable loop
for vn,vi in sorted(Lvariables.iteritems()):
l3(vn)
ht = hTag(st,vn,s[0])
si['t'].Draw("%s>>%s"%(vi['root'],ht),"%s"%ca2)
##################################################
# stacking
for sn,si in sorted(Lsamples.iteritems()):
sg = si['g']
st = si['i']['tag']
for vn,vi in sorted(Lvariables.iteritems()):
hg = hTag(sg,vn,s[0])
ht = hTag(st,vn,s[0])
Hg = histos[hg]
Ht = histos[ht]
Hg.Add(Ht)
##################################################
# k-factor
INTEGRALS = {"Data":0.0,"QCD":0.0,"Other":0.0,"TTJets":0.0}
if "KF" in opts.weight[1] and not ('TP' in t[0]):
#print "if"
for ig,g in enumerate(list(set([x['g'] for (k,x) in Lsamples.iteritems()]))):
var = Lvariables.keys()[0]
hg = hTag(g,var,s[0])
if g=="VBF125": continue
elif g=="Data": INTEGRALS["Data"] += float(histos[hg].Integral())
elif g=="QCD": INTEGRALS["QCD"] += float(histos[hg].Integral())
else: INTEGRALS["Other"] += float(histos[hg].Integral())
kfactor = (INTEGRALS["Data"]-INTEGRALS["Other"])/INTEGRALS["QCD"]
l1("K-factor: %.2f"%kfactor)
elif "KF" in opts.weight[1]:
#print "elif"
for ig,g in enumerate(list(set([x['g'] for (k,x) in Lsamples.iteritems()]))):
var = Lvariables.keys()[0]
hg = hTag(g,var,s[0])
if g=="VBF125": continue
elif g=="Data": INTEGRALS["Data"] += float(histos[hg].Integral())
elif g=="TTJets": INTEGRALS["TTJets"] += float(histos[hg].Integral())
else: INTEGRALS["Other"] += float(histos[hg].Integral())
kfactor = (INTEGRALS["Data"]-INTEGRALS["Other"])/INTEGRALS["TTJets"]
l1("K-factor: %.2f"%kfactor)
##################################################
# groups
l1("Group iteration")
can.Clear()
for vn,vi in sorted(Lvariables.iteritems()):
fout.cd()
# set pads
p1,p2 = FormatPads(can)
##################################################
# top pad
p1.cd()
# containers
l2("Variable: %s"%(vn))
DRAW = {}
hs = "s_v%s_c%s"%(vn,s[0])
S = THStack(hs,hs)
L = TLegend(gStyle.GetPadLeftMargin()+0.03,0.5,gStyle.GetPadLeftMargin()+0.03+0.23*3,1.-gStyle.GetPadTopMargin()-0.025)
FormatLegend(L)
# group loop
for ig,g in enumerate(sorted(list(set([x['g'] for (k,x) in Lsamples.iteritems()])),key=lambda y:(not '125' in y,not 'WJets' in y,histos[hTag(y,vn,s[0])].Integral()))):
l3("%s"%(g))
hg = hTag(g,vn,s[0])
Hg = histos[hg]
print Hg.Integral()
# underflow
Hg.SetBinContent(1,0.5*(Hg.GetBinContent(0)+Hg.GetBinContent(1)))
Hg.SetBinError(1,sqrt(pow(Hg.GetBinError(0),2.)+pow(Hg.GetBinError(1),2.)))
# overflow
Hg.SetBinContent(Hg.GetNbinsX(),0.5*(Hg.GetBinContent(Hg.GetNbinsX())+Hg.GetBinContent(Hg.GetNbinsX()+1)))
Hg.SetBinError(Hg.GetNbinsX(),sqrt(pow(Hg.GetBinError(Hg.GetNbinsX()),2.)+pow(Hg.GetBinError(Hg.GetNbinsX()+1),2.)))
# type handling
if g=="Data":
Hg.SetMarkerStyle(20)
Hg.SetMarkerColor(kBlack)
Hg.SetMarkerSize(1.2)
DRAW["Data"] = Hg
elif g=="VBF125":
Hg.SetLineStyle(1)
Hg.SetLineColor(ji['colours'][g])
Hg.SetLineWidth(3)
Hg.Scale(10.)
DRAW["SIG"] = Hg
elif g=="GF125":
Hg.SetLineStyle(7)
Hg.SetLineColor(ji['colours'][g])
Hg.SetLineWidth(3)
Hg.Scale(10.)
DRAW["SIGGF"] = Hg
else:
Hg.SetLineStyle(1)
Hg.SetLineColor(kBlack)
Hg.SetFillStyle(1001)
Hg.SetFillColor(ji['colours'][g])
if g=="QCD" and (not "TP" in t[0]) and "KF" in opts.weight[1]: Hg.Scale(kfactor)
if g=="TTJets" and ("TP" in t[0]) and "KF" in opts.weight[1]: Hg.Scale(kfactor)
if not Hg.GetEntries()==0: S.Add(Hg)
# Full stack (bkg)
DRAW["BKG"] = S
S.Draw()
Sall = FormatStack(S)
# MC err
histos[hTag("MCerr",vn,s[0])] = Sall.Clone(hTag("MCerr",vn,s[0]))
Hg = histos[hTag("MCerr",vn,s[0])]
Hg.SetFillStyle(3004)
Hg.SetFillColor(kGray+2)#kBlack)
Hg.SetMarkerSize(0)
DRAW["MCerr"] = Hg
# Fill legend
L.AddEntry(histos[hTag("Data",vn,s[0])],"Data","P")
L.AddEntry(histos[hTag("QCD",vn,s[0])],"%s%s"%("QCD"," (x%.2f)"%kfactor if ("KF" in opts.weight[1] and not "TP" in t[0]) else ""),"F")
L.AddEntry(histos[hTag("ZJets",vn,s[0])],"%s"%("ZJets"),"F")
L.AddEntry(histos[hTag("VBF125",vn,s[0])],"10x VBF H(125)","L")
if hTag("Tall",vn,s[0]) in histos:
L.AddEntry(histos[hTag("Tall",vn,s[0])],"%s%s"%("T"," (x%.2f)"%kfactor if ("KF" in opts.weight[1] and "TP" in t[0]) else ""),"F")
else:
L.AddEntry(histos[hTag("TTJets",vn,s[0])],"%s%s"%("TTJets"," (x%.2f)"%kfactor if ("KF" in opts.weight[1] and "TP" in t[0]) else ""),"F")
L.AddEntry(histos[hTag("WJets",vn,s[0])],"%s"%("WJets"),"F")
L.AddEntry(histos[hTag("GF125",vn,s[0])],"10x GF H(125)","L")
if not hTag("Tall",vn,s[0]) in histos:
L.AddEntry(histos[hTag("singleT",vn,s[0])],"%s"%("singleT"),"F")
L.AddEntry(histos[hTag("MCerr",vn,s[0])],"MC stat. unc.","F")
# Draw
DRAW["BKG"].Draw("hist")
DRAW["Data"].Draw("PE,same")
DRAW["SIG"].Draw("hist,same")
DRAW["SIGGF"].Draw("hist,same")
DRAW["MCerr"].Draw("E2,same")
# Edit legend
L.SetY1(L.GetY2()-L.GetNRows()*0.04)
L.Draw()
# Draw paves
pcms1.Draw()
pcms2.Draw()
# Edit canvas
gPad.SetLogy(1)
gPad.RedrawAxis()
p1.Write(p1.GetName()+("NOM" if "NOM" in opts.selection[0] else "VBF")+vn)
##################################################
# bottom pad
p2.cd()
# histo = 1
one = DRAW["Data"].Clone("one")
for ibin in range(0,one.GetNbinsX()+2):
one.SetBinContent(ibin,1.)
one.SetBinError(ibin,0.)
# ratio Data/MC - 1
rat = DRAW["Data"].Clone(DRAW["Data"].GetName().replace('h','hRat'))
FormatRatio(rat)
rat.Divide(DRAW["BKG"].GetStack().Last())
rat.Add(one,-1.)
histos[hTag("Data/MC",vn,s[0])] = rat
# ratio MCerr/MC - 1
ratMCerr = histos[hTag("MCerr",vn,s[0])].Clone("ratMCerr")
ratMCerr.Divide(DRAW["BKG"].GetStack().Last())
ratMCerr.Add(one,-1.)
histos[hTag("MCerrDataMC",vn,s[0])] = ratMCerr
# Draw
rat.Draw()
ratMCerr.Draw("E2,same")
# Edit pad
rat.GetYaxis().SetRangeUser(-1.0+eps,1.0-eps)
gPad.SetGridy(1)
gPad.Update()
line = TF1("l1","0.",gPad.GetUxmin(),gPad.GetUxmax())
line.SetLineColor(kBlack)
line.Draw("same")
gPad.RedrawAxis()
##################################################
# save
plotdir = "./plots/%s"%s[0]
if not os.path.exists(plotdir): makeDirs(plotdir)
can.SaveAs("%s/%s_s%s.pdf"%(plotdir,vn,s[0]))
can.SaveAs("%s/%s_s%s.png"%(plotdir,vn,s[0]))
fout.cd()
can.Clear()
##################################################
# clean
can.Close()
closeSamples(Lsamples)
def mkTemplateFunctions():
global paves
mp = parser()
opts, fout, samples = main(mp, False, False, True)
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
TYPE = opts.typetag
samples = INTERNALpicksamples(opts, jsons)
hDat = INTERNALhistograms(opts)
hQcd = INTERNALhistograms(opts)
can = TCanvas('profiles', 'profiles', 900, 750)
#can.Divide(2,1)
ln = INTERNALline("1", float(opts.fBound[0]), float(opts.fBound[1]))
for iTag, Tag in enumerate(opts.catTags):
selsamples = [s for s in samples if s['incarnation'] == Tag]
fins = [x['tfile'] for x in selsamples]
l1('Running for %s' % Tag)
can.cd(1 if 'NOM' in Tag else 2)
leg = TLegend(0.75, 0.5, 1. - gPad.GetRightMargin() - 0.05,
1. - gPad.GetTopMargin() - 0.015)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextSize(0.045)
leg.SetTextFont(42)
leg.SetY1(leg.GetY2() - 2 * leg.GetTextSize() * 1.25)
l2("Running for <mbbReg>")
fout.cd()
hQcd[Tag] = TProfile("hProf_sel%s_%s" % (Tag, TYPE),
"hProf_sel%s_%s" % (Tag, TYPE), 25, -0.15, 0.15)
hDat[Tag] = TProfile("hProf_sel%s_%s" % (Tag, "Data"),
"hProf_sel%s_%s" % (Tag, "Data"), 50, -0.15, 0.15)
h = hDat[Tag]
h = INTERNALstyleHist(h, 0, markers, colours, TYPE)
h = hQcd[Tag]
h = INTERNALstyleHist(h, 0, markers, colours, TYPE)
can.cd()
for ifin, fin in enumerate(fins):
if "QCD" in fin.GetName():
h = hQcd[Tag]
else:
h = hDat[Tag]
if "VBF" in fin.GetName(): continue
fout.cd()
can.cd(1 if 'NOM' in Tag else 2)
l4('Sample: %s' % fin.GetName())
CUT1 = "mbbReg[%d] > %.1f && mbbReg[%d] < %.1f" % (
1 if 'NOM' in Tag else 2, 60, 1 if 'NOM' in Tag else 2, 170)
CUT2, cutlabel = write_cuts(
["None"], ["None"],
reftrig=["None"],
sample=jsons['samp']['files'][os.path.split(
fin.GetName())[1]]['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.complexWghts[(Tag, 'old')],
trigequal=trigTruth(opts.usebool))
l4('Cutting with: (%s)*%s' % (CUT1, CUT2))
tin = fin.Get("Hbb/events")
l3('Drawing mbbReg[%d] --> %s' %
(1 if 'NOM' in Tag else 2, h.GetName()))
tin.Draw(
"mbbReg[%d]:%s>>+%s" %
(1 if 'NOM' in Tag else 2,
"mvaZ" if 'NOM' in Tag else "mvaVBF", h.GetName()),
TCut(CUT1) * TCut(CUT2), "prof")
h.Write(h.GetTitle(), TH1.kOverwrite)
gPad.SetGrid(0, 1)
gPad.RedrawAxis()
hQcd[Tag].SetMarkerSize(1.0)
hQcd[Tag].SetMarkerStyle(20)
hQcd[Tag].SetMarkerColor(kBlack)
hDat[Tag].GetXaxis().SetTitleOffset(1.1)
hDat[Tag].DrawCopy()
hQcd[Tag].DrawCopy("same")
epave("Z selection",
gPad.GetLeftMargin() + 0.01, 1. - 0.5 * gPad.GetTopMargin(),
"left", 1, 0.048)
epave("%.1f fb^{-1} (8 TeV)" % (19.8 if 'NOM' in Tag else 18.3),
1. - gPad.GetRightMargin() - 0.01,
1. - 0.5 * gPad.GetTopMargin(), "right", 0, 0.048)
line = -0.6 if 'NOM' in Tag else -0.1
tl = TLine(line, 70, line, 170)
tl.SetLineStyle(kDashed)
tl.SetLineColor(kGray + 2)
tl.Draw()
paves += [tl]
leg.Clear()
a = leg.AddEntry(hDat[Tag], "Data", "PL")
a.SetTextColor(kBlue + 2)
a = leg.AddEntry(hQcd[Tag], "QCD", "PL")
a.SetTextColor(kBlack)
leg.Draw()
paves += [leg]
gPad.RedrawAxis()
can.SaveAs("mbbRegProfileZ.pdf")
# clean
for f in samples:
if f['tfile']: f['tfile'].Close()
fout.Close()
def getYields(opts, loadedSamples, KFWghts):
jsoninfo = json.loads(filecontent(opts.jsoninfo))
l1("Extracting yields:")
yieldarchive = {}
# selection
for sel in opts.selection:
thissel = '-'.join(sorted(sel))
l1("Running for sel: %s" % thissel)
# trigger
for itrg, trg in enumerate(opts.trigger):
thistrg = '-'.join(trg)
if not opts.datatrigger == []:
thisdatatrg = '-'.join(
opts.datatrigger[opts.trigger.index(trg)])
l1("Running for trg: %s" %
(thistrg if opts.datatrigger == [] else " (data: %s)" %
thisdatatrg))
# KFWght
KFWght = KFWghts[(thissel, thistrg)]
# samples
groupcounts = {}
# category
if any([('VBF' in '-'.join(x) or 'MBBREG2' in '-'.join(x))
for x in opts.selection]):
keys = ['ALL', 'CAT-2', 'CAT4', 'CAT5', 'CAT6']
elif any([('NOM' in '-'.join(x) or 'MBBREG1' in '-'.join(x))
for x in opts.selection]):
keys = ['ALL', 'CAT-1', 'CAT0', 'CAT1', 'CAT2', 'CAT3']
else:
sys.exit(Red +
'Don\'t know how to handle this selection. Exiting.' +
plain)
if any([x in thissel for x in ['NOMC', 'VBFC']]):
cat = 'CAT' + str(
int(re.search('(NOMC|VBFC)([0-9]{1})', thissel).group(2)) -
1)
else:
cat = 'ALL'
if 'VBF' in thissel and cat == "CAT-1": cat = "CAT-2"
if 'VBF' in thissel and 'CAT' in cat and int(
re.search('CAT([0-9+-]*)', cat).group(1)) >= 0:
cat = "CAT%d" % (
int(re.search('CAT([0-9+-]*)', cat).group(1)) + 4)
if any([x in thissel for x in ['NOMC', 'VBFC']]):
print re.search('([+_-]*)(mvaNOMC|mvaVBFC)([0-9]{1})([+_-]*)',
thissel).groups()
selmincat = thissel.replace(
''.join(
re.search(
'([+_-]*)(mvaNOMC|mvaVBFC)([0-9]{1})([+_-]*)',
thissel).groups()), '')
else:
selmincat = thissel
if not (selmincat, '-'.join(trg)) in yieldarchive:
yieldarchive[(selmincat, '-'.join(trg))] = {}
d = dict([(x, {}) for x in keys])
for k, v in d.iteritems():
if not k in yieldarchive[(selmincat, '-'.join(trg))]:
yieldarchive[(selmincat, '-'.join(trg))][k] = v
for sample in loadedSamples:
if opts.debug:
l3("%sSample: %s%s" % (purple, sample['tag'], plain))
trg, trg_orig = trigData(opts, sample, trg)
cut, cutlabel = write_cuts(sel,
trg,
sample=sample['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
trigequal=trigTruth(opts.usebool),
varskip=opts.skip)
if opts.debug:
l3("Cut: %s%s%s: %s" % (blue, cutlabel, plain, cut))
inroot('float nCount = %s.count("%s");' %
(sample['pointer'], cut))
l3("Entries %s%-40s: N=%10.f %s" %
(cyan, "(%s)" % sample['tag'], ROOT.nCount, plain))
yieldarchive[(
selmincat,
'-'.join(trg_orig))][cat][sample['tag']] = ROOT.nCount
if jsoninfo['groups'][sample['tag']] in groupcounts:
groupcounts[jsoninfo['groups'][
sample['tag']]] += ROOT.nCount
else:
groupcounts[jsoninfo['groups'][
sample['tag']]] = ROOT.nCount
trg = dc(trg_orig)
yieldarchive[(selmincat, '-'.join(trg))][cat].update(groupcounts)
for group, groupval in groupcounts.iteritems():
l3("Entries %s%-40s: N=%10.f %s" %
(purple, "(%s)" % group, groupval, plain))
print
allkeys = []
for y in yieldarchive.itervalues():
for tag in y:
allkeys += [str(x) for x in y[tag].keys()]
allkeys = list(set(allkeys))
#print allkeys
printYieldTable(
opts, yieldarchive,
sorted(['Data', 'DataV', 'QCD', 'ZWJets', 'Tall', 'VBF125', 'GF125'],
key=lambda x: (x[0:3], len(x), x)))
printYieldTable(
opts, yieldarchive,
sorted(list(
set(allkeys) - set([
'Data', 'DataV', 'QCD', 'ZJets', 'TTJets', 'singleT', 'WJets',
'VBF125', 'GF125'
])),
key=lambda x: (x[0:3], len(x), x)))
if opts.latex:
printYieldTableLatex(
opts, yieldarchive,
sorted(
['Data', 'DataV', 'QCD', 'ZWJets', 'Tall', 'VBF125', 'GF125'],
key=lambda x: (x[0:3], len(x), x)))
if opts.latex:
printYieldTableLatex(
opts, yieldarchive,
sorted(list(
set(allkeys) - set([
'Data', 'DataV', 'QCD', 'Tall', 'ZWJets', 'VBF125', 'GF125'
])),
key=lambda x: (x[0:3], len(x), x)))
def mkTemplateFunctions():
global paves
mp = parser()
opts,fout,samples = main(mp,False,False,True)
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
TYPE = opts.typetag
samples = INTERNALpicksamples(opts,jsons)
hDat = INTERNALhistograms(opts)
hQcd = INTERNALhistograms(opts)
can = TCanvas('profiles','profiles',900,750)
#can.Divide(2,1)
ln = INTERNALline("1",float(opts.fBound[0]),float(opts.fBound[1]))
for iTag,Tag in enumerate(opts.catTags):
selsamples = [s for s in samples if s['incarnation']==Tag]
fins = [x['tfile'] for x in selsamples]
l1('Running for %s'%Tag)
can.cd(1 if 'NOM' in Tag else 2)
leg = TLegend(0.75,0.5,1.-gPad.GetRightMargin()-0.05,1.-gPad.GetTopMargin()-0.015)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextSize(0.045)
leg.SetTextFont(42)
leg.SetY1(leg.GetY2()-2*leg.GetTextSize()*1.25)
l2("Running for <mbbReg>")
fout.cd()
hQcd[Tag] = TProfile("hProf_sel%s_%s"%(Tag,TYPE),"hProf_sel%s_%s"%(Tag,TYPE),25,-0.15,0.15)
hDat[Tag] = TProfile("hProf_sel%s_%s"%(Tag,"Data"),"hProf_sel%s_%s"%(Tag,"Data"),50,-0.15,0.15)
h = hDat[Tag]
h = INTERNALstyleHist(h,0,markers,colours,TYPE)
h = hQcd[Tag]
h = INTERNALstyleHist(h,0,markers,colours,TYPE)
can.cd()
for ifin,fin in enumerate(fins):
if "QCD" in fin.GetName():
h = hQcd[Tag]
else:
h = hDat[Tag]
if "VBF" in fin.GetName(): continue
fout.cd()
can.cd(1 if 'NOM' in Tag else 2)
l4('Sample: %s'%fin.GetName())
CUT1 = "mbbReg[%d] > %.1f && mbbReg[%d] < %.1f"%(1 if 'NOM' in Tag else 2,60,1 if 'NOM' in Tag else 2,170)
CUT2,cutlabel = write_cuts(["None"],["None"],reftrig=["None"],sample=jsons['samp']['files'][os.path.split(fin.GetName())[1]]['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.complexWghts[(Tag,'old')],trigequal=trigTruth(opts.usebool))
l4('Cutting with: (%s)*%s'%(CUT1,CUT2))
tin = fin.Get("Hbb/events")
l3('Drawing mbbReg[%d] --> %s'%(1 if 'NOM' in Tag else 2,h.GetName()))
tin.Draw("mbbReg[%d]:%s>>+%s"%(1 if 'NOM' in Tag else 2,"mvaZ" if 'NOM' in Tag else "mvaVBF",h.GetName()),TCut(CUT1)*TCut(CUT2),"prof")
h.Write(h.GetTitle(),TH1.kOverwrite)
gPad.SetGrid(0,1)
gPad.RedrawAxis()
hQcd[Tag].SetMarkerSize(1.0)
hQcd[Tag].SetMarkerStyle(20)
hQcd[Tag].SetMarkerColor(kBlack)
hDat[Tag].GetXaxis().SetTitleOffset(1.1)
hDat[Tag].DrawCopy()
hQcd[Tag].DrawCopy("same")
epave("Z selection",gPad.GetLeftMargin()+0.01,1.-0.5*gPad.GetTopMargin(),"left",1,0.048)
epave("%.1f fb^{-1} (8 TeV)"%(19.8 if 'NOM' in Tag else 18.3),1.-gPad.GetRightMargin()-0.01,1.-0.5*gPad.GetTopMargin(),"right",0,0.048)
line = -0.6 if 'NOM' in Tag else -0.1
tl = TLine(line,70,line,170)
tl.SetLineStyle(kDashed)
tl.SetLineColor(kGray+2)
tl.Draw()
paves += [tl]
leg.Clear()
a = leg.AddEntry(hDat[Tag],"Data","PL")
a.SetTextColor(kBlue+2)
a = leg.AddEntry(hQcd[Tag],"QCD","PL")
a.SetTextColor(kBlack)
leg.Draw()
paves += [leg]
gPad.RedrawAxis()
can.SaveAs("mbbRegProfileZ.pdf")
# clean
for f in samples:
if f['tfile']: f['tfile'].Close()
fout.Close()
def mkTemplateFunctions():
mp = parser()
opts, fout, samples = main(mp, False, False, True)
sels = ['NOM', 'VBF']
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
selsamples = INTERNALpicksamples(opts, jsons)
can = TCanvas("main", "main")
hProf = INTERNALhistograms(opts, sels, jsons)
#INTERNALcanvases(opts)
l1("Creating profiles")
if not opts.read:
for isel, sel in enumerate(sels):
ssel = [s for s in selsamples if sel in s['fname']]
for s in ssel:
l2("Running for %s" % s['tag'])
cut, cutlabel = write_cuts(["None"], ["None"],
reftrig=["None"],
sample=s['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.complexWghts[(sel,
'old')],
trigequal=trigTruth(opts.usebool))
cut = re.findall('\*.*',
cut)[0][2:-1].replace('pu', 'ev.pu').replace(
'trig', 'ev.trig')
if opts.debug:
l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s" %
(s['tag'], blue, cutlabel, plain, cut))
nevents = s['tree'].GetEntries()
for iev, ev in enumerate(s['tree']):
if iev % int(nevents / 5) == 0:
l3("%10s/%10s" % (iev, nevents))
wght = eval(cut)
mva = ev.mvaNOM if sel == 'NOM' else ev.mvaVBF
mbb = ev.mbbReg[1] if sel == 'NOM' else ev.mbbReg[2]
if sel == 'NOM':
if mva < -0.6: continue
if mbb < 80. or mbb > 200.: continue
if sel == 'VBF':
if mva < -0.1: continue
if mbb < 80. or mbb > 200.: continue
for v in opts.variable:
if '1' in v and not sel == 'NOM' and not 'Btag' in v and not 'QGL' in v:
continue
if '2' in v and not sel == 'VBF' and not 'Btag' in v and not 'QGL' in v:
continue
if 'mva' in v and not sel in v: continue
v = jsons['vars']['variables'][v]
h = hProf[(sel, v['var'],
'QCD' if 'QCD' in s['fname'] else 'DAT')]
h.Fill(
mva,
eval("ev.%s" %
(v['root'] if not '[btag' in v['root'] else
v['root'].replace('[btag', '[ev.btag'))),
wght)
else:
for k in hProf.iterkeys():
hProf[k] = fout.Get("h%s_sel%s_%s" % (k[2], k[0], k[1]))
k = list(set([x[0:2] for x in hProf.iterkeys()]))
for ik in k:
low = min(
hProf[(ik[0], ik[1],
'QCD')].GetBinContent(hProf[(ik[0], ik[1],
'QCD')].GetMinimumBin()),
hProf[(ik[0], ik[1],
'DAT')].GetBinContent(hProf[(ik[0], ik[1],
'DAT')].GetMinimumBin()))
hig = max(
hProf[(ik[0], ik[1],
'QCD')].GetBinContent(hProf[(ik[0], ik[1],
'QCD')].GetMaximumBin()),
hProf[(ik[0], ik[1],
'DAT')].GetBinContent(hProf[(ik[0], ik[1],
'DAT')].GetMaximumBin()))
med = hProf[(ik[0], ik[1], 'DAT')].GetMean(2)
dif = hig - low
setlow = med - 2 * dif
sethig = med + 2 * dif
if 'mbb' in ik[1]: setlow = 110
if 'mbb' in ik[1]: sethig = 160
hProf[(ik[0], ik[1], 'DAT')].GetYaxis().SetRangeUser(setlow, sethig)
hProf[(ik[0], ik[1], 'DAT')].Draw()
hProf[(ik[0], ik[1], 'QCD')].SetMarkerStyle(25)
hProf[(ik[0], ik[1], 'QCD')].SetMarkerColor(kBlue)
#for ibin in range(1,hProf[(ik[0],ik[1],'QCD')].GetNbinsX()+1): hProf[(ik[0],ik[1],'QCD')].
hProf[(ik[0], ik[1], 'QCD')].Draw("same L")
leg = TLegend(0.6, 0.6, 0.9, 0.9,
"%s selection" % (ik[0].strip('sel')))
leg.SetFillStyle(-1)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.045)
leg.AddEntry(hProf[(ik[0], ik[1], 'DAT')], 'Data')
leg.AddEntry(hProf[(ik[0], ik[1], 'QCD')], 'QCD')
leg.SetY1(leg.GetY2() - (leg.GetNRows() + 1) * 0.05)
leg.Draw()
can.SaveAs("plots/%s.png" %
hProf[(ik[0], ik[1], 'DAT')].GetName().replace('hDAT', 'h'))
fout.cd()
for h in hProf.itervalues():
h.Write(h.GetName(), TH1.kOverwrite)
# clean
fout.Close()
def do_fill(opts, fout, s, v, sel, trg, ref, KFWght=None, skipWght=None):
# info
l2("Filling for %s" % v['var'])
# containers
cuts = {}
cutlabels = {}
names = {}
canvas = TCanvas("cfill", "cfill", 1200, 1000)
# trg
trg, trg_orig = trigData(opts, s, trg)
# names
jsoninfo = json.loads(filecontent(opts.jsoninfo))
names['global'] = getNames(opts, s, v, sel, trg_orig, ref)
keepMapInfo = None
if skipWght == True:
keepMapInfo = [
x for x in opts.weight[1]
if (x[0:3] == 'MAP' or x[0:3] == 'FUN' or x[0:3] == 'COR')
]
opts.weight[1] = [
dc(x) for x in opts.weight[1]
if not (x[0:3] == 'MAP' or x[0:3] == 'FUN' or x[0:3] == 'COR')
]
wpars = weightInfo(opts.weight, KFWght)
# TEffi object
TEffi = TEffiType(v)
# looping over different tags
for tag in ['Num', 'Den']:
# cuts
cuts[tag], cutlabels[tag] = write_cuts(
sel,
trg if tag == 'Num' else ['None'],
reftrig=ref,
sample=s['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
KFWght=KFWght,
varskip=opts.skip + [v['root']],
trigequal=trigTruth(opts.usebool))
if opts.debug:
l3("Cut %s: %s%s%s: %s" %
(tag, blue, cutlabels[tag], plain, cuts[tag]))
# loading/filling
names[tag] = getNames(opts, s, v, sel,
trg_orig if tag == 'Num' else ['None'], ref, tag)
if not s['tag'] in TEffi.h[tag] or TEffi.h[tag][s['tag']] == None:
fout.Delete(names[tag]['hist'])
TEffi.fill(s['pointer'], s['tag'], tag, names[tag], cuts[tag])
if opts.debug:
l3("%sFilled: %40s(N=%9d, Int=%9d)%s" %
(yellow, TEffi.h[tag][s['tag']].GetName(),
TEffi.h[tag][s['tag']].GetEntries(),
TEffi.h[tag][s['tag']].Integral(), plain))
# consider ratio
tag = 'Rat'
names[tag] = getNames(opts, s, v, sel, trg_orig, ref, tag)
TEffi.effi(names[tag], jsoninfo['colours'][s['tag']],
markerStyle(s['tag'], jsoninfo['markers'][s['tag']], opts))
# write histogram to file
path = "%s/%s/%s" % ('turnonCurves', wpars, names['global']['path-turnon'])
TEffi.write(fout, path)
# clean
#TEffi.delete()
canvas.Close()
trg = dc(trg_orig)
if skipWght == True:
opts.weight[1] += keepMapInfo
def mkTemplateFunctions():
mp = parser()
opts,fout,samples = main(mp,False,False,True)
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
TYPE = opts.typetag
samples = INTERNALpicksamples(opts,jsons)
hDat, hRat, fFit, gUnc, fitter, covariant = INTERNALhistograms(opts)
c1, c2, c = INTERNALcanvases(opts)
can = TCanvas("main","main")
ln = INTERNALline("1",float(opts.fBound[0]),float(opts.fBound[1]))
for iTag,Tag in enumerate(opts.catTags):
nCat = int(opts.mvaBins['mva%s'%Tag][0])-1
rCat = 0 if Tag=='NOM' else 4
selsamples = [s for s in samples if s['incarnation']==Tag]
fins = [x['tfile'] for x in selsamples]
l1('Running for %s - QCD'%Tag)
c2[Tag] = TCanvas('transfer_sel%s_%s'%(Tag,TYPE),'transfer_sel%s_%s'%(Tag,TYPE),600*(nCat-1),600)
c2[Tag].Divide(nCat-1,1)
leg = INTERNALlegend(Tag)
leg.SetX1(0.7)
lleg = dict(((Tag,iCat+1),INTERNALlegend(Tag)) for iCat in range(nCat-1))
for iCat in range(nCat):
jCat = iCat + rCat
if opts.merge:
if iCat==nCat-1: continue
if iCat==nCat-2: jCat = jCat*10+jCat+1
l2('Running for CAT%d'%jCat)
# v = jsons['vars']['variables'][opts.variables[opts.variables.keys()[iTag]][0]]
# regular hists
# if v['xs']: hDat[(Tag,iCat)] = TH1F('hDat_sel%s_CAT%d'%(Tag,iCat),'hDat_sel%s_CAT%d'%(Tag,iCat),int(v['nbins_x']),v['xs'])
# else: hDat[(Tag,iCat)] = TH1F('hDat_sel%s_CAT%d'%(Tag,iCat),'hDat_sel%s_CAT%d'%(Tag,iCat),int(v['nbins_x']),int(v['xmin']),int(v['xmax']))
hDat[(Tag,iCat)] = TH1F('hDat_sel%s_CAT%d_%s'%(Tag,jCat,TYPE),'hDat_sel%s_CAT%d_%s'%(Tag,jCat,TYPE),int(float(opts.fBound[1]) - float(opts.fBound[0]))/(10 if 'Dat' in TYPE else 20),float(opts.fBound[0]),float(opts.fBound[1]))
print hDat[(Tag,iCat)].GetBinWidth(1)
h = hDat[(Tag,iCat)]
h = INTERNALstyleHist(h,iCat,markers,colours,TYPE)
can.cd()
# cut
CUT = TCut("mva%s>%.2f && mva%s<=%.2f"%(Tag,float(opts.mvaBins["mva%s"%Tag][1][iCat+1]),Tag,float(opts.mvaBins["mva%s"%Tag][1][iCat+2])))
if opts.merge:
CUT = TCut("mva%s>%.2f && mva%s<=%.2f"%(Tag,float(opts.mvaBins["mva%s"%Tag][1][iCat+1]),Tag,float(opts.mvaBins["mva%s"%Tag][1][iCat+3])))
###CUT = TCut("mvaNOM>%.2f && mvaNOM<=%.2f"%(float(opts.mvaBins["mva%s"%Tag][1][iCat+1]),float(opts.mvaBins["mva%s"%Tag][1][iCat+2])))
l3('Cutting with: %s'%CUT)
for fin in fins:
l4('Sample: %s'%fin.GetName())
CUT2,cutlabel = write_cuts(["None"],["None"],reftrig=["None"],sample=jsons['samp']['files'][os.path.split(fin.GetName())[1]]['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.complexWghts[(Tag,'old')],trigequal=trigTruth(opts.usebool))
l4('Cutting with: %s'%CUT2)
# drawing
tin = fin.Get("Hbb/events")
l3('Drawing mbbReg[%d] --> %s'%(1 if 'NOM' in Tag else 2,h.GetName()))
tin.Draw("mbbReg[%d]>>+%s"%(1 if 'NOM' in Tag else 2,h.GetName()),TCut(CUT)*TCut(CUT2))
fout.cd()
###tin.Draw("mbbReg[1]>>%s"%(h.GetName()),CUT)
if not opts.unblind: h = INTERNALblind(h,100.,150.)
h.Scale(1./h.Integral())
h.SetDirectory(0)
# ratio hist
hRat[(Tag,iCat)] = h.Clone(h.GetName().replace('hDat','hRat'))
r = hRat[(Tag,iCat)]
r.SetTitle(r.GetName())
r = INTERNALstyleHist(r,iCat,markers,colours,TYPE)
# dividing by control CAT
##print "Divide: ", hDat[(Tag,0)].GetName()
r.Divide(hDat[(Tag,0)])
r.SetDirectory(0)
# fit
fFit[(Tag,iCat)] = TF1(h.GetName().replace('hDat','fitRatio'),'pol1',float(opts.fBound[0]),float(opts.fBound[1]))
f = fFit[(Tag,iCat)]
f.SetLineColor(colours[iCat])
h.Write(h.GetTitle(),TH1.kOverwrite)
if not iCat==0:
r.Fit(f,"RQ")
fitter = TVirtualFitter.GetFitter()
covariant = TMatrixDSym()
covariant.Use(fitter.GetNumberTotalParameters(),fitter.GetCovarianceMatrix())
nBins = 200
dx = (r.GetBinLowEdge(r.GetNbinsX()+1)-r.GetBinLowEdge(1))/float(nBins)
vx = array('f',[r.GetBinLowEdge(1)+(i+1)*dx for i in range(nBins)])
vy = array('f',[f.Eval(vx[i]) for i in range(nBins)])
vex = array('f',[0.0]*nBins)
vey = array('f',[sqrt(pow(vx[i],2)*covariant(1,1)+2.0*vx[i]*covariant(0,1)+covariant(0,0)) for i in range(nBins)])
gUnc[(Tag,iCat)] = TGraphErrors(nBins,vx,vy,vex,vey)
g = gUnc[(Tag,iCat)]
g.SetFillColor(colours[iCat])
g.SetFillStyle(3004)
c1[Tag].cd()
h.Draw('same E')
hDat[(Tag,0)].GetYaxis().SetRangeUser(0.0,max(h.GetMaximum(),hDat[(Tag,0)].GetMaximum())*1.02)
gPad.Update()
leg.AddEntry(h,'CAT%d'%jCat,'P')
c2[Tag].cd(iCat)
ln.Draw()
g.Draw('same E3')
r.Draw('same')
ll = lleg[(Tag,iCat)]
ll.AddEntry(h,'CAT%d / CAT%d'%(jCat,rCat),'P')
ll.SetY1(ll.GetY2()-ll.GetNRows()*0.06)
ll.SetTextSize(0.04)
ll.Draw()
r.GetYaxis().SetRangeUser(0.0,2.0)
r.Write(r.GetTitle(),TH1.kOverwrite)
g.Write(r.GetTitle().replace('hRat','gRat'),TH1.kOverwrite)
else:
c1[Tag] = TCanvas('MbbShape_sel%s_%s'%(Tag,TYPE),'MbbShape_sel%s_%s'%(Tag,TYPE),900,600)
c1[Tag].cd()
gPad.SetLeftMargin(0.12)
gPad.SetRightMargin(0.03)
h.GetYaxis().SetTitleOffset(0.8)
h.SetFillColor(kGray)
h.Draw('hist')
leg.AddEntry(h,'CAT%d'%jCat,'F')
fout.cd()
f.Write(f.GetName(),TH1.kOverwrite)
c1[Tag].cd()
leg.SetY1(leg.GetY2()-leg.GetNRows()*0.06)
leg.Draw()
c1[Tag].SaveAs('plots/transfer/%s%s.png'%(c1[Tag].GetName(),"_merged" if opts.merge else ""))
c1[Tag].SaveAs('plots/transfer/%s%s.pdf'%(c1[Tag].GetName(),"_merged" if opts.merge else ""))
c2[Tag].SaveAs('plots/transfer/%s%s.png'%(c2[Tag].GetName(),"_merged" if opts.merge else ""))
c2[Tag].SaveAs('plots/transfer/%s%s.pdf'%(c2[Tag].GetName(),"_merged" if opts.merge else ""))
#c.SaveAs('plots/transfer/%s.png'%c.GetName())
# clean
for f in samples: f['tfile'].Close()
fout.Close()
def mkSigOverBkg(opts, samples, sel, trg):
# cut
cut, cutlabel = write_cuts(sel,
trg,
reftrig=["None"],
sample="DataA",
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
trigequal=trigTruth(opts.usebool))
if opts.debug:
l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s" %
("DataA", blue, cutlabel, plain, cut))
# category
cat = ''
mbb = ''
print '-'.join(sel)
if 'VBF' in '-'.join(sel):
cat = str(
int(re.search('(mvaVBFC)([0-9]*)', '-'.join(sel)).group(2)) +
3) if int(re.search('(mvaVBFC)([0-9]*)',
'-'.join(sel)).group(2)) > 0 else "-2"
mbb = 'mbbReg[2]'
elif 'NOM' in '-'.join(sel):
cat = str(
int(re.search('(mvaNOMC)([0-9]*)', '-'.join(sel)).group(2)) - 1)
mbb = 'mbbReg[1]'
elif 'None' == '-'.join(sel):
cat = "ALL"
mbb = ''
else:
sys.exit(Red + "Don't know how to handle this selection: %s. Exiting" %
('-'.join(sel)) + plain)
# limited categories
if cat == 'ALL' or not (int(cat) >= 0 and int(cat) < 7): return -99, None
# container
numbers = {}
# input
if not opts.wsig == '':
fin = TFile.Open(opts.wsig, "read")
workspace = fin.Get("w")
mean = workspace.var("mean_m125_CAT%s" % cat).getVal()
fwhm = workspace.var("fwhm_m125_CAT%s" % cat).getVal()
lower = mean - fwhm / 2.
upper = mean + fwhm / 2.
elif not (opts.xmin == '' or opts.xmax == '' or opts.xcen == ''):
mean = opts.xcen
fwhm = 0
lower = opts.xmin
upper = opts.xmax
else:
sys.exit(Red + 'Can\'t continue without boundaries. Exiting.' + plain)
l2("Looking in [%.4f,%.4f] around %.4f" % (lower, upper, mean))
numbers['nlower'] = lower
numbers['nupper'] = upper
numbers['nmean'] = mean
# extra cut
extracut = ["%s>=%.6f" % (mbb, lower), "%s<=%.6f" % (mbb, upper)]
countSig = 0.0
countBkg = 0.0
for s in samples:
cut, cutlabel = write_cuts(sel,
trg,
reftrig=["None"],
sample=s['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
trigequal=trigTruth(opts.usebool),
extra=extracut)
if opts.debug:
l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s" %
(s['tag'], blue, cutlabel, plain, cut))
fsIn = TFile.Open(
opts.globalpath + '/' +
s['fname'].replace('flatTree', '%sFlatTree' % opts.flatprefix).
replace('.root', '%s.root' % opts.flatsuffix) if not (
opts.flatprefix == "" or opts.flatsuffix == ""
) else opts.globalpath + s['fname'])
tsIn = fsIn.Get("Hbb/events")
h = TH1F("hcount", "hcount", 1, 0, 1)
tsIn.Draw("0.5>>hcount", cut)
count = h.Integral()
numbers[s['tag']] = count
if any([x in s['tag'] for x in ['VBF', 'GluGlu']]):
countSig += count
elif any([x in s['tag'] for x in ['Data']]):
countBkg += count
else:
continue
fsIn.Close()
numbers['bkg'] = countBkg
numbers['sig'] = countSig
numbers['SoB'] = countSig / countBkg
numbers['SosB'] = countSig / sqrt(countBkg)
return cat, numbers
def mkSBSigTrees():
# initialise
global paves
mp = parser()
opts, fout = main.main(mp, True)
fname = fout.GetName()
fout.Close()
os.remove(fname)
prefix = basepath + '/../mvd'
basetree = "flatTree_VBFPowheg125.root"
makeDirs('/'.join([prefix, "rootfiles"]))
makeDirs('/'.join([prefix, "plots"]))
######################################################################################################################################################
######################################################################################################################################################
# step 01: NOM/PRK selection
if opts.step == 1:
fin = TFile.Open('/'.join([opts.globalpath, basetree]), "read")
tin = fin.Get("Hbb/events")
l1("Step 01: %s selection" % opts.sel)
fout = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(".root", "_EvIntStep01_%s.root" % opts.sel)
]), "recreate")
makeDirsRoot(fout, "Hbb")
gDirectory.cd("Hbb")
#cut,label = write_cuts(opts.selection[0],opts.trigger[0],reftrig=[],jsoncuts=opts.jsoncuts,jsonsamp=opts.jsonsamp,sample="VBF125",weight=opts.weight,trigequal=trigTruth(True))
cut, label = write_cuts([],
opts.trigger[0],
reftrig=[],
jsoncuts=opts.jsoncuts,
jsonsamp=opts.jsonsamp,
sample="VBF125",
weight=opts.weight,
trigequal=trigTruth(True))
l2("Cut %s: %s" % (opts.sel, cut))
tout = tin.CopyTree(cut)
fout.Write()
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 2:
fin = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(".root", "_EvIntStep01_%s.root" % opts.sel)
]), "read")
tin = fin.Get("Hbb/events")
l1("Step 02: %s: eta/btag variable only slimming" % (opts.sel))
tin.SetBranchStatus('*', 0)
for b in [
'jetBtag', 'btagIdx', 'jetEta', 'etaIdx', 'partonId',
'partonMatchIdx', 'partonMatchDR', 'jetPt', 'jetPhi',
'jetMass', 'blikNOMIdx', 'blikVBFIdx', 'mqq', 'mbb', 'dEtaqq'
]:
tin.SetBranchStatus(b, 1)
fout = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(".root", "_EvIntStep02_%s.root" % (opts.sel))
]), "recreate")
makeDirsRoot(fout, "Hbb")
gDirectory.cd("Hbb")
tout = tin.CloneTree()
fout.Write(fout.GetName(), TH1.kOverwrite)
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 3:
fin = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(".root", "_EvIntStep02_%s.root" % (opts.sel))
]), "read")
tin = fin.Get("Hbb/events")
nin = tin.GetEntriesFast()
l1("Step 03%s: %s: jets tree transformation" %
(" (Alt)" if opts.alt else "", opts.sel))
fout = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(
".root", "_EvIntStep03%s_%s.root" %
("Alt" if opts.alt else "", opts.sel))
]), "recreate")
makeDirsRoot(fout, "Hbb")
gDirectory.cd("Hbb")
v_eta, v_btag, v_pt, v_phi, v_mass = zeros(1, dtype='float32'), zeros(
1, dtype='float32'), zeros(1, dtype='float32'), zeros(
1, dtype='float32'), zeros(1, dtype='float32')
v_etaIdx, v_btagIdx, v_pid, v_ptIdx = zeros(1, dtype='int32'), zeros(
1, dtype='int32'), zeros(1, dtype='int32'), zeros(1, dtype='int32')
# new branches
tout = TTree("jets", "jets")
tout.Branch("eta", v_eta, "eta/F")
tout.Branch("etaIdx", v_etaIdx, "etaIdx/I")
tout.Branch("btag", v_btag, "btag/F")
tout.Branch("btagIdx", v_btagIdx, "btagIdx/I")
tout.Branch("pid", v_pid, "pid/I")
tout.Branch("ptIdx", v_ptIdx, "ptIdx/I")
tout.Branch("pt", v_pt, "pt/F")
tout.Branch("phi", v_phi, "phi/F")
tout.Branch("mass", v_mass, "mass/F")
# loop over tree
tref = now()
for iEv, Ev in enumerate(tin):
if iEv % 20000 == 0:
[m, s], p = testimate(tref, iEv, nin)
print "%6d/%-10d (est. %dm %ds, %.1f%%)" % (iEv, nin, m, s, p)
if opts.nentries > 0 and iEv > opts.nentries: break
# loop over partons
for pj in range(len(Ev.partonMatchDR)):
if Ev.partonMatchDR[pj] > 0.25: continue
# if Ev.partonMatchIdx[pj] > len(Ev.jetPt): continue
ptIdx = Ev.partonMatchIdx[pj]
v_ptIdx[0] = Ev.partonMatchIdx[pj]
v_pid[0] = Ev.partonId[pj]
v_btag[0] = Ev.jetBtag[ptIdx]
v_pt[0] = Ev.jetPt[ptIdx]
v_eta[0] = Ev.jetEta[ptIdx]
v_phi[0] = Ev.jetPhi[ptIdx]
v_mass[0] = Ev.jetMass[ptIdx]
if opts.alt:
if (ptIdx in list(Ev.btagIdx)) and (ptIdx in list(
Ev.etaIdx)):
v_btagIdx[0] = list(Ev.btagIdx).index(ptIdx)
v_etaIdx[0] = list(Ev.etaIdx).index(ptIdx)
else:
continue
else:
if ptIdx < len(list(Ev.btagIdx)):
v_btagIdx[0] = Ev.btagIdx[ptIdx]
v_etaIdx[0] = Ev.etaIdx[ptIdx]
tout.Fill()
# save
fout.Write(fout.GetName(), TH1.kOverwrite)
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 4:
l1("Step 04%s: %s: blik training" %
(" (Alt)" if opts.alt else "", opts.sel))
fin = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(
".root", "_EvIntStep03%s_%s.root" %
("Alt" if opts.alt else "", opts.sel))
]), "read")
tin = fin.Get("Hbb/jets")
fout = TFile.Open(
"rootfiles/bjetId_%s_MVA%s.root" %
(opts.sel, "Alt" if opts.alt else ""), "recreate")
sigCut = TCut("abs(pid) == 5")
bkgCut = TCut("abs(pid) != 5")
presel = TCut(
"btagIdx<4 && etaIdx<4 && etaIdx>-1 && ptIdx<4 && btagIdx>-1 && ptIdx>-1"
)
Nin = tin.GetEntries()
N = 100000
l1("Input tree: %d events" % Nin)
l1("Using %d events" % N)
factory = TMVA.Factory(
"factory_%s%s_" % (opts.sel, "_Alt" if opts.alt else ""), fout,
"!V:!Silent:Color:DrawProgressBar:Transformations=I;G:AnalysisType=Classification"
)
factory.SetInputTrees(tin, sigCut, bkgCut)
factory.AddVariable("btag", 'F')
factory.AddVariable("eta", 'F')
factory.AddVariable("btagIdx", 'I')
factory.AddVariable("etaIdx", 'I')
factory.PrepareTrainingAndTestTree(
presel,
"nTrain_Signal=%d:nTrain_Background=%d:nTest_Signal=%d:nTest_Background=%d"
% (N, N, N, N))
factory.BookMethod(TMVA.Types.kLikelihood, "Likelihood")
factory.BookMethod(TMVA.Types.kBDT, "BDT_GRAD2",
"NTrees=600:nCuts=25:BoostType=Grad:Shrinkage=0.2")
factory.TrainAllMethods()
factory.TestAllMethods()
factory.EvaluateAllMethods()
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 5:
l1("Step 05%s: %s: Sig/Bkg plots" %
(" (Alt)" if opts.alt else "", opts.sel))
fin = TFile.Open(
prefix + "/rootfiles/flatTree_VBFPowheg125_EvIntStep03%s_%s.root" %
("Alt" if opts.alt else "", opts.sel), "read")
tin = fin.Get("Hbb/jets")
fout = TFile.Open(
prefix + "/rootfiles/flatTree_VBFPowheg125_EvIntStep05%s_%s.root" %
("Alt" if opts.alt else "", opts.sel), "recreate")
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C" % basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.02)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleSize(0.05, "XY")
gStyle.SetLabelSize(0.04, "XY")
gStyle.SetTitleOffset(1.35, "Y")
gStyle.SetGridColor(17)
#
fc = {"sig": kBlue - 9, "bkg": kRed}
fs = {"sig": 1001, "bkg": 3004}
lc = {"sig": kBlue - 7, "bkg": kRed}
Ax = [
"#eta", "#eta rank", "CSV b-tag", "CSV b-tag rank",
"(old) b-likelihood", "(old) b-likelihood rank", "b-likelihood",
"b-likelihood rank"
]
Ay = [
"N / (0.2)", "N / (1)", "N / (0.1)", "N / (1)", "N / (0.04)",
"N / (1)", "N / (0.04)", "N / (1)"
]
AN = [50, 4, 110, 4, 50, 4, 50, 4]
Ami = [-5, -0.5, -10, -0.5, -1, -0.5, -1, -0.5]
Ama = [5, 3.5, 1, 3.5, 1, 3.5, 1, 3.5]
Av = [
"jetEta", "etaIdx", "jetBtag", "btagIdx", "blikNOM", "blikNOMIdx",
"myblikNOM", "myblikNOMIdx"
]
hs = {}
btagbinsinput = [-10, -9, -1, 0]
for i in range(1, int(1. / 0.05) + 1):
btagbinsinput += [round(float(i) * 0.05, 2)]
btagbins = array('f', btagbinsinput)
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate(["eta", "etaIdx", "btag", "btagIdx"]):
x, y, N, mi, ma = Ax[i2], Ay[i2], AN[i2], Ami[i2], Ama[i2]
if not a2 == "btag":
hs["%s_%s" % (a1, a2)] = eval(
'TH1F("h%s_%s","h%s_%s;%s;%s",%d,%f,%f)' %
(a1, a2, a1, a2, x, y, N, mi, ma))
else:
hs["%s_%s" % (a1, a2)] = TH1F(
"h%s_%s" % (a1, a2), "h%s_%s;%s;%s" % (a1, a2, x, y),
len(btagbins) - 1, btagbins)
hs["%s_%s" % (a1, a2)].SetFillColor(fc[a1])
hs["%s_%s" % (a1, a2)].SetFillStyle(fs[a1])
hs["%s_%s" % (a1, a2)].SetLineColor(lc[a1])
#
hs["sig_etaIdx"].GetXaxis().SetNdivisions(4)
hs["sig_btagIdx"].GetXaxis().SetNdivisions(4)
TGaxis.SetMaxDigits(4)
legs = [
TLegend(
1. - gStyle.GetPadRightMargin() - 0.03 - 0.30,
1. - gStyle.GetPadTopMargin() - 0.03,
1. - gStyle.GetPadRightMargin() - 0.03,
1. - gStyle.GetPadTopMargin() - 0.03 - 0.055 * 3,
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B"))
]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(4):
legs += [deepcopy(legs[0])]
#
for var in ["eta", "etaIdx", "btag", "btagIdx"]:
for typ in ["sig", "bkg"]:
tin.Draw("%s>>h%s_%s" % (var, typ, var),
"abs(pid)==5" if typ == "sig" else "abs(pid)!=5")
#
for h in hs.itervalues():
h.Scale(1. / h.Integral())
h.GetYaxis().SetRangeUser(
0.0 if not "Idx" in h.GetName() else 0.1,
h.GetBinContent(h.GetMaximumBin()) * 1.40)
hs["sig_btag"] = btagTrafo(hs["sig_btag"], "sig", fc["sig"], fs["sig"],
lc["sig"])
hs["bkg_btag"] = btagTrafo(hs["bkg_btag"], "bkg", fc["bkg"], fs["bkg"],
lc["bkg"])
c = TCanvas("c", "c", 1800, 1300)
c.Divide(2, 2)
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate(["btag", "btagIdx", "eta", "etaIdx"]):
c.cd(i2 + 1)
h = hs["%s_%s" % (a1, a2)]
h.Draw("" if a1 == "sig" else "same")
gPad.SetGrid(1, 1)
legs[i2].AddEntry(h, "signal" if a1 == "sig" else "background",
"F")
if a1 == "bkg": legs[i2].Draw()
if a2 == "btag":
gPad.SetLogy(1)
epave("-1", -0.08, 0.000306)
epave("-10", -0.135, 0.000306)
#
makeDirs(prefix + "/plots")
c.SaveAs(prefix + "/plots/EvIntDiscriminant_variablesIn%s_%s.pdf" %
("Alt" if opts.alt else "", opts.sel))
fout.Write(fout.GetName(), TH1.kOverwrite)
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 6:
l1("Step 06%s: %s: weights filling & output plots." %
(" (Alt)" if opts.alt else "", opts.sel))
gROOT.SetBatch(1)
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C" % basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleOffset(1.35, "Y")
gStyle.SetPalette(1)
gStyle.SetGridColor(17)
TGaxis.SetMaxDigits(4)
gStyle.SetTitleSize(0.05, "XYZ")
gStyle.SetLabelSize(0.04, "XYZ")
gStyle.SetTitleOffset(1.35, "Y")
gStyle.SetGridColor(17)
#
fc = {"sig": kBlue - 9, "bkg": kRed}
fs = {"sig": 1001, "bkg": 3004}
lc = {"sig": kBlue - 7, "bkg": kRed}
Ax = [
"#eta", "#eta rank", "CSV b-tag", "CSV b-tag rank",
"(old) b-likelihood", "(old) b-likelihood rank", "b-likelihood",
"b-likelihood rank", "|#eta|", "bbtag", "bblik"
]
Ay = [
"N / (0.2)", "N / (1)", "N / (0.1)", "N / (1)", "N / (0.08)",
"N / (1)", "N / (0.08)", "N / (1)", "N / (0.1)", "N / (0.02)",
"N / (0.01)"
]
AN = [50, 4, 110, 4, 25, 4, 25, 4, 100, 550, 200]
Ami = [-5, -0.5, -10, -0.5, -1, -0.5, -1, -0.5, 0, -10, -1]
Ama = [5, 3.5, 1, 3.5, 1, 3.5, 1, 3.5, 5, 1, 1, 1]
Av = [
"jetEta", "etaIdx", "jetBtag", "btagIdx",
"blik%s" % ("NOM" if opts.sel == "NOM" else "VBF"),
"blik%sIdx" % ("NOM" if opts.sel == "NOM" else "VBF"), "blik",
"blikIdx", "abseta", "jetBtag", "blik"
]
hs = {}
btagbinsinput = [-10, -9, -1, 0]
for i in range(1, int(1. / 0.05) + 1):
btagbinsinput += [round(float(i) * 0.05, 2)]
btagbins = array('f', btagbinsinput)
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate([
"eta", "etaIdx", "btag", "btagIdx", "blik", "blikIdx",
"blik2", "blik2Idx", "abseta", "bbtag", "bblik"
]):
x, y, N, mi, ma = Ax[i2], Ay[i2], AN[i2], Ami[i2], Ama[i2]
if not a2 == "btag":
hs["%s_%s" % (a1, a2)] = eval(
'TH1F("h%s_%s","h%s_%s;%s;%s",%d,%f,%f)' %
(a1, a2, a1, a2, x, y, N, mi, ma))
else:
hs["%s_%s" % (a1, a2)] = TH1F(
"h%s_%s" % (a1, a2), "h%s_%s;%s;%s" % (a1, a2, x, y),
len(btagbins) - 1, btagbins)
hs["%s_%s" % (a1, a2)].SetFillColor(fc[a1])
hs["%s_%s" % (a1, a2)].SetFillStyle(fs[a1])
hs["%s_%s" % (a1, a2)].SetLineColor(lc[a1])
#
if not opts.replot:
fglobal = TFile.Open(
'/'.join([
prefix, "rootfiles",
basetree.replace(".root",
"_EvIntStep02_%s.root" % opts.sel)
]), "read")
tglobal = fglobal.Get("Hbb/events")
eta, etaIdx, btag, btagIdx = zeros(1, 'float32'), zeros(
1, 'float32'), zeros(1, 'float32'), zeros(1, 'float32')
pid = ROOT.vector('int')()
reader = TMVA.Reader()
if opts.alttag == "" or not ("Kostas" in opts.alttag
or "CERN" in opts.alttag):
reader.AddVariable("btag", btag)
reader.AddVariable("eta", eta)
reader.AddVariable("btagIdx", btagIdx)
reader.AddVariable("etaIdx", etaIdx)
reader.BookMVA(
opts.tmva, "weights/factory_%s%s__BDT_GRAD2.weights.xml" %
(opts.sel, "_Alt" if opts.alt else ""))
elif "Kostas" in opts.alttag:
reader.AddVariable("btagIdx", btagIdx)
reader.AddVariable("etaIdx", etaIdx)
reader.AddVariable("btag", btag)
reader.AddVariable("eta", eta)
reader.BookMVA(
opts.tmva,
"kostas/weights/factory_%s__BDT_GRAD2.weights.xml" %
opts.sel)
elif "CERN" in opts.alttag:
reader.AddVariable("btagIdx", btagIdx)
reader.AddVariable("etaIdx", etaIdx)
reader.AddVariable("btag", btag)
reader.AddVariable("eta", eta)
reader.BookMVA(
opts.tmva,
"tmpcern/factory_BCanditate_%s_BDT_GRAD.weights.xml" %
opts.sel)
# reader.BookMVA(opts.tmva,"weights/kostas.NOM.xml")
#
blik = ROOT.vector('float')()
blikIdx = ROOT.vector('int')()
blikmqq = zeros(1, 'float32')
blikmbb = zeros(1, 'float32')
blikdetaqq = zeros(1, 'float32')
#
fmvd = TFile.Open(
prefix +
"/rootfiles/flatTree_VBFPowheg125_EvIntStep04%s_%s.root" %
("Alt" if opts.alt else "", opts.sel), "recreate")
makeDirsRoot(fmvd, "Hbb")
gDirectory.cd("Hbb")
tmvd = tglobal.CloneTree(0)
#
tmvd.Branch("blik", blik)
tmvd.Branch("blikIdx", blikIdx)
tmvd.Branch("blikmqq", blikmqq, "blikmqq/F")
tmvd.Branch("blikmbb", blikmbb, "blikmbb/F")
tmvd.Branch("blikdetaqq", blikdetaqq, "blikdetaqq/F")
tmvd.Branch("pid", pid)
#
nentries = tglobal.GetEntriesFast()
tref = now()
for iEv, Ev in enumerate(tglobal):
blik.resize(4, 0)
blikIdx.resize(4, 0)
pid.resize(4, 0)
#
if opts.nentries > 0:
if iEv > opts.nentries: break
if iEv % 5000 == 0:
[m, s], p = testimate(tref, iEv, nentries)
print "%8d/%-10d (est. %dm %ds, %.1f%%)" % (iEv, nentries,
m, s, p)
#
for ijet in range(4):
eta[0] = Ev.jetEta[ijet]
btag[0] = Ev.jetBtag[ijet]
if opts.alt:
etaIdx[0] = list(Ev.etaIdx).index(ijet)
btagIdx[0] = list(Ev.btagIdx).index(ijet)
else:
etaIdx[0] = Ev.etaIdx[ijet]
btagIdx[0] = Ev.btagIdx[ijet]
blik[ijet] = float(reader.EvaluateMVA(opts.tmva))
#
blikIdxPair = sorted([[ijet, blik[ijet]] for ijet in range(4)],
key=lambda (x, y): y,
reverse=True)
#
for ijet in range(4):
blikIdx[ijet] = blikIdxPair[ijet][0]
#
for pj in range(len(Ev.partonMatchDR)):
if Ev.partonMatchDR[pj] > 0.25: continue
ptIdx = Ev.partonMatchIdx[pj]
if ptIdx >= len(Ev.btagIdx): continue
pid[ptIdx] = Ev.partonId[pj]
# for ijet in range(4):
# pidVals = sorted([(x,Ev.partonMatchDR[x]) for x in range(len(Ev.partonMatchIdx)) if (Ev.partonMatchIdx[x]==ijet and Ev.partonMatchDR[x]<0.25)],key=lambda (x,y):(y))
# if len(pidVals)<1: pid[ijet] =-999
# else: pid[ijet] = Ev.partonId[pidVals[0][0]]
# if pid[ijet]!=-999:
for i2, a2 in enumerate([
"eta", "etaIdx", "btag", "btagIdx", "blik",
"blikIdx", "blik2", "blik2Idx", "abseta", "bbtag",
"bblik"
]):
if a2 == "blik": continue
h = hs["%s_%s" %
("sig" if abs(pid[ptIdx]) == 5 else "bkg", a2)]
if not Av[i2] in ["blik", "blikIdx", "abseta"]:
v = eval(
"Ev.%s[%d]" %
(Av[i2], ptIdx)) if not "Idx" in a2 else eval(
"list(Ev.%s).index(%d)" % (Av[i2], ptIdx))
elif Av[i2] == "blik":
v = blik[ptIdx]
elif Av[i2] == "blikIdx":
v = list(blikIdx).index(ptIdx)
elif Av[i2] == "abseta":
v = abs(Ev.jetEta[ptIdx])
elif Av[i2] == "bbtag":
v = Ev.jetBtag[ptIdx]
elif Av[i2] == "bblik":
v = blik[ptIdx]
h.Fill(v)
#
# v = [TLorentzVector(),TLorentzVector(),TLorentzVector(),TLorentzVector()]
# for j in range(4):
# k = blikIdx[j]
# v[j].SetPtEtaPhiM(Ev.jetPt[k],Ev.jetEta[k],Ev.jetPhi[k],Ev.jetMass[k])
v = []
for jid in range(4):
v += [TLorentzVector()]
v[-1].SetPtEtaPhiM(Ev.jetPt[jid], Ev.jetEta[jid],
Ev.jetPhi[jid], Ev.jetMass[jid])
blikmqq[0] = (v[blikIdx[2]] + v[blikIdx[3]]).M()
blikmbb[0] = (v[blikIdx[0]] + v[blikIdx[1]]).M()
blikdetaqq[0] = abs(Ev.jetEta[int(blikIdx[2])] -
Ev.jetEta[int(blikIdx[3])])
tmvd.Fill()
else:
fmvd = TFile.Open(
prefix +
"/rootfiles/flatTree_VBFPowheg125_EvIntStep04%s_%s.root" %
("Alt" if opts.alt else "", opts.sel), "update")
gDirectory.cd("Hbb")
tmvd = fmvd.Get("Hbb/events")
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate([
"eta", "etaIdx", "btag", "btagIdx", "blik", "blikIdx",
"blik2", "blik2Idx"
]):
eval('h%s_%s = fmvd.Get("Hbb/h%s_%s")' % (a1, a2, a1, a2))
#
c = TCanvas("c", "c", 1800, 1500)
c.Divide(4, 4)
Bv = [
"blikNOM" if opts.sel == "NOM" else "blikVBF",
"blikNOMIdx" if opts.sel == "NOM" else "blikVBFIdx", "blik",
"blikIdx", "mqq[0]",
"mqq[%d]" % (1 if opts.sel == "NOM" else 2), "blikmqq", "NONE",
"dEtaqq[0]",
"dEtaqq[%d]" % (1 if opts.sel == "NOM" else 2), "blikdetaqq",
"NONE", "mbb[0]",
"mbb[%d]" % (1 if opts.sel == "NOM" else 2), "blikmbb", "NONE"
]
Bx = [
"(old) b-likelihood", "(old) b-likelihood rank", "b-likelihood",
"b-likelihood rank", "(CSV) m_{qq'} (GeV)", "(old) m_{qq'} (GeV)",
"(new) m_{qq'} (GeV)", "", "(CSV) #Delta#eta_{qq'}",
"(old) #Delta#eta_{qq'}", "(new) #Delta#eta_{qq'}", "",
"(CSV) m_{b#bar{b}} (GeV)", "(old) m_{b#bar{b}} (GeV)",
"(new) m_{b#bar{b}} (GeV)", ""
]
By = [
"N / (0.08)", "N / (1)", "N / (0.08)", "N / (1)", "N / (20 GeV)",
"N / (20 GeV)", "N / (20 GeV)", "", "N / (0.1)", "N / (0.1)",
"N / (0.1)", "", "N / (10 GeV)", "N / (10 GeV)", "N / (10 GeV)", ""
]
BN = [25, 4, 25, 4, 100, 100, 100, 0, 50, 50, 50, 0, 30, 30, 30, 0]
Bmi = [-1, -0.5, -1, -0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
Bma = [
1, 3.5, 1, 3.5, 2000, 2000, 2000, 0, 5, 5, 5, 0, 300, 300, 300, 0
]
Bt = [
"(existing)", "(existing)", "(new)", "(new)", "(existing)",
"(existing)", "(new)", "", "(existing)", "(existing)", "(new)", "",
"(existing)", "(existing)", "(new)", ""
]
for iv, v in enumerate(Bv):
if v == "blikNOM" or v == "blikVBF": continue
if v == "NONE": continue
c.cd(iv + 1)
gPad.SetGrid(1, 1)
tmvd.Draw("%s>>h%d(%d,%f,%f)" %
(v, iv + 1, BN[iv], Bmi[iv], Bma[iv]))
eval('h%d.GetXaxis().SetTitle("%s")' % (iv + 1, Bx[iv]))
eval('h%d.GetYaxis().SetTitle("%s")' % (iv + 1, By[iv]))
trpave(Bt[iv])
makeDirs(prefix + "/plots")
c.SaveAs(prefix +
"/plots/EvIntDiscriminant_variablesOut%s%s-1_%s.pdf" %
("Alt" if opts.alt else "",
opts.alttag if not opts.alttag == "" else "", opts.sel))
c.Close()
ci = TCanvas("ci", "ci", 900, 750)
# c.Divide(2,1)
Bv = [
"blikmbb:mbb[0]",
"mbb[%d]:mbb[0]" % (1 if opts.sel == "NOM" else 2)
]
Bx = ["CSV b-tag m_{b#bar{b}} (GeV)", "CSV b-tag m_{b#bar{b}} (GeV)"]
By = [
"b-likelihood m_{b#bar{b}} (GeV)",
"b-likelihood m_{b#bar{b}} (GeV)"
]
BN = [[140, 140], [140, 140]]
Bmi = [[0, 0], [0, 0]]
Bma = [[700, 700], [700, 700]]
Bt = ["(new)", "(existing)"]
for iv, v in enumerate(Bv):
if v == "NONE": continue
# c.cd(iv+1)
ci.cd()
tmvd.Draw(
"%s>>h%d(%d,%f,%f,%d,%f,%f)" %
(v, iv + 1 + 12, BN[iv][0], Bmi[iv][0], Bma[iv][0], BN[iv][1],
Bmi[iv][1], Bma[iv][1]), "", "colz")
gPad.SetRightMargin(0.14)
gPad.SetTopMargin(0.06)
gPad.SetBottomMargin(0.14)
eval('ROOT.h%d.GetXaxis().SetTitle("%s")' % (iv + 1 + 12, Bx[iv]))
eval('ROOT.h%d.GetYaxis().SetTitle("%s")' % (iv + 1 + 12, By[iv]))
eval('ROOT.h%d.GetXaxis().SetTitleOffset(%.2f)' %
(iv + 1 + 12, 1.1))
#trpave(Bt[iv])
tlpave("Set %s selection" % ("A" if opts.sel == "NOM" else "B"),
0.85, 1)
eval('ROOT.h%d.GetZaxis().SetRangeUser(1,4000)' % (iv + 1 + 12))
gPad.SetLogz(1)
ci.SaveAs(prefix +
"/plots/EvIntDiscriminant_variablesOut%s%s-2%s_%s.pdf" %
("Alt" if opts.alt else "",
opts.alttag if not opts.alttag == "" else "",
"-new" if iv == 0 else "-existing", opts.sel))
#ci.Close()
cb = TCanvas("cb", "cb", 1800, 750)
cb.Divide(2, 1)
c = TCanvas("c", "c", 2700, 1950)
c.Divide(3, 3)
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate([
"eta", "etaIdx", "btag", "btagIdx", "blik", "blikIdx",
"blik2", "blik2Idx", "abseta", "bbtag", "bblik"
]):
h = hs["%s_%s" % (a1, a2)]
if "Idx" in a2: h.GetXaxis().SetNdivisions(4)
if not h.Integral() == 0: h.Scale(1. / h.Integral())
h.GetYaxis().SetRangeUser(
0.001 if a2 in ["btag", "blik", "blik2", "bbtag", "bblik"
] else 0.0,
h.GetBinContent(h.GetMaximumBin()) *
(75 if a2 in ["btag", "blik", "blik2", "bbtag", "bblik"]
else 1.4))
legs = [
TLegend(
1. - gStyle.GetPadRightMargin() - 0.03 - 0.30,
1. - gStyle.GetPadTopMargin() - 0.03,
1. - gStyle.GetPadRightMargin() - 0.03,
1. - gStyle.GetPadTopMargin() - 0.03 - 0.055 * 3,
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B"))
]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(8):
legs += [deepcopy(legs[0])]
hsigbtagnew = btagTrafo(hs["sig_btag"], "sig", fc["sig"], fs["sig"],
lc["sig"])
hbkgbtagnew = btagTrafo(hs["bkg_btag"], "bkg", fc["bkg"], fs["bkg"],
lc["bkg"])
for i2, a2 in enumerate([
"blik2", "blik2Idx", "blikIdx", "btag", "btagIdx", "NONE",
"eta", "etaIdx", "NONE"
]):
if a2 == "blik2": cb.cd(1)
elif a2 == "blik2Idx": cb.cd(2)
else: c.cd(i2 + 1)
for a1 in ["sig", "bkg"]:
gPad.SetRightMargin(0.02)
gPad.SetBottomMargin(0.12)
if a2 == "NONE": continue
h = hs["%s_%s" % (a1, a2)]
if a2 == "btag" and a1 == "sig": h = hsigbtagnew
elif a2 == "btag" and a1 == "bkg": h = hbkgbtagnew
gPad.SetGrid(1, 1)
if a2 in ["btag", "blik", "blik2"]: gPad.SetLogy(1)
else: gPad.SetLogy(0)
h.Draw("" if a1 == "sig" else "same")
legs[i2].AddEntry(h, "signal" if a1 == "sig" else "background",
"F")
if a1 == "bkg": legs[i2].Draw()
h.GetXaxis().SetTitleSize(0.05)
h.GetYaxis().SetTitleSize(0.05)
h.GetXaxis().SetTitleOffset(1.1)
h.GetYaxis().SetTitleOffset(1.35)
h.GetXaxis().SetLabelSize(0.04)
h.GetYaxis().SetLabelSize(0.04)
if a2 == "btag":
epave("-1", -0.08, 0.000306)
epave("-10", -0.13, 0.000306)
gPad.Update()
if "blik2" in a2 and a1 == "bkg":
cb.SaveAs(
prefix +
"/plots/EvIntDiscriminant_variablesOut%s%s-3a_%s.pdf" %
("Alt" if opts.alt else "", opts.
alttag if not opts.alttag == "" else "", opts.sel))
c.SaveAs(prefix +
"/plots/EvIntDiscriminant_variablesOut%s%s-3_%s.pdf" %
("Alt" if opts.alt else "",
opts.alttag if not opts.alttag == "" else "", opts.sel))
c = TCanvas("c", "c", 900, 750)
c.cd()
legs = [
TLegend(
gStyle.GetPadLeftMargin() + 0.05,
gStyle.GetPadBottomMargin() + 0.05,
gStyle.GetPadLeftMargin() + 0.3,
gStyle.GetPadBottomMargin() + 0.05 + 0.050 * 4,
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B"))
]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.045)
legs[0].SetFillStyle(0)
legs[0].SetBorderSize(0)
gs = {}
for i2, a2 in enumerate(["bblik", "bbtag", "abseta"]):
hsig = hs["sig_%s" % a2]
hbkg = hs["bkg_%s" % a2]
g = makeGraph(hsig, hbkg,
"right" if not a2 == "abseta" else "left")
g.Write()
gs[a2] = g
legs[0].AddEntry(
g, "b-likelihood" if "blik" in a2 else
("CSV b-tag" if a2 == "bbtag" else "|#eta|"), "L")
g.Draw("A,L" if i2 == 0 else "same,L")
legs[0].Draw()
legs[0].SetY2(legs[0].GetY1() + legs[0].GetNRows() * 0.050 + 0.05)
gPad.Update()
c.SaveAs(prefix +
"/plots/EvIntDiscriminant_variablesOut%s%s-4_%s.pdf" %
("Alt" if opts.alt else "",
opts.alttag if not opts.alttag == "" else "", opts.sel))
if opts.replot:
for i in range(20):
h = eval("ROOT.h%d" % (i))
if h: h.Write(h.GetName(), TH1.kOverwrite)
for a1 in ["sig", "bkg"]:
for i2, a2 in enumerate([
"blik2", "blik2Idx", "blikIdx", "btag", "btagIdx",
"NONE", "eta", "etaIdx", "NONE"
]):
if a2 == "NONE": continue
h = hs["%s_%s" % (a1, a2)]
if h: h.Write(h.GetName(), TH1.kOverwrite)
for g in gs.itervalues():
if g: g.Write(g.GetName(), TH1.kOverwrite)
else:
fmvd.Write()
#
fmvd.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step == 7:
l1("Step 07%s: %s: more plots." %
(" (Alt)" if opts.alt else "", opts.sel))
gROOT.SetBatch(1)
gStyle.SetOptStat(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C" % basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleOffset(1.35, "Y")
gStyle.SetTitleSize(0.05, "XYZ")
gStyle.SetLabelSize(0.04, "XYZ")
gStyle.SetPalette(1)
gStyle.SetGridColor(17)
TGaxis.SetMaxDigits(4)
fin = TFile.Open(
"rootfiles/bjetId_%s_MVA%s.root" %
(opts.sel, "Alt" if opts.alt else ""), "read")
tin = fin.Get("TestTree")
fout = TFile.Open(
prefix + "/rootfiles/flatTree_VBFPowheg125_EvIntStep07%s_%s.root" %
("Alt" if opts.alt else "", opts.sel), "recreate")
NTrue = float(tin.GetEntries("classID==0"))
NFake = float(tin.GetEntries("classID==1"))
V = ["btag", "btag", "abs(eta)", "abs(eta)", "BDT_GRAD2", "BDT_GRAD2"]
Av = [
"btagTrue", "btagFake", "etaTrue", "etaFake", "blikTrue",
"blikFake"
]
Ax = [
"CSV b-tag", "CSV b-tag", "|#eta|", "|#eta|", "b-likelihood",
"b-likelihood"
]
Ay = [
"N / (0.05)", "N / (0.05)", "N / (0.2)", "N / (0.2)", "N / (0.08)",
"N / (0.08)"
]
Ami = [0, 0, 0, 0, -1, -1]
Ama = [1, 1, 5, 5, 1, 1]
AN = [20, 20, 25, 25, 25, 25]
hs = {}
for a in range(len(Av)):
hs["%s" % Av[a]] = TH1F("h%s" % Av[a],
"h%s;%s;%s" % (Av[a], Ax[a], Ay[a]), AN[a],
Ami[a], Ama[a])
h = hs["%s" % Av[a]]
if "True" in Av[a]:
h.SetLineColor(kBlue)
h.SetFillColor(kBlue - 9)
h.SetFillStyle(1001)
elif "Fake" in Av[a]:
h.SetLineColor(kRed)
h.SetFillColor(kRed)
h.SetFillStyle(3004)
for v in range(len(V)):
tin.Draw("%s>>h%s" % (V[v], Av[v]),
"classID==0" if "True" in Av[v] else "classID==1")
if "True" in Av[v]: hs[Av[v]].Scale(1. / NTrue)
elif "Fake" in Av[v]: hs[Av[v]].Scale(1. / NFake)
c = TCanvas("c", "c", 900, 1950)
c.Divide(1, 3)
legs = [
TLegend(
1. - gStyle.GetPadRightMargin() - 0.03 - 0.30,
1. - gStyle.GetPadTopMargin() - 0.03,
1. - gStyle.GetPadRightMargin() - 0.03,
1. - gStyle.GetPadTopMargin() - 0.03 - 0.055 * 3,
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B"))
]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(20):
legs += [deepcopy(legs[0])]
for a in range(len(Av)):
c.cd(divmod(a + 2, 2)[0])
h = hs["%s" % Av[a]]
h.Draw("" if "True" in Av[a] else "same")
legs[divmod(a + 2, 2)[0]].AddEntry(
h, "signal" if "True" in Av[a] else "background", "F")
if "Fake" in Av[a]: legs[divmod(a + 2, 2)[0]].Draw()
if "btag" in Av[a] or "blik" in Av[a]:
if "True" in Av[a]:
h.GetYaxis().SetRangeUser(
0.001,
h.GetBinContent(h.GetMaximumBin()) * 75)
gPad.SetLogy(1)
else:
if "True" in Av[a]:
h.GetYaxis().SetRangeUser(
0.0,
h.GetBinContent(h.GetMaximumBin()) * 1.4)
gPad.SetLogy(0)
c.SaveAs("plots/performance%s-1_%s.pdf" %
("Alt" if opts.alt else "", opts.sel))
c.Close()
xtrue = [0.] * 1000
yfake = [0.] * 1000
c = TCanvas("c", "c", 900, 750)
c.cd()
legs = [
TLegend(
gStyle.GetPadLeftMargin() + 0.05,
gStyle.GetPadBottomMargin() + 0.05,
gStyle.GetPadLeftMargin() + 0.3,
gStyle.GetPadBottomMargin() + 0.05 + 0.050 * 4,
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B"))
]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.045)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(20):
legs += [deepcopy(legs[0])]
gs = {}
for a in range(len(Av)):
if "True" in Av[a]:
xtrue = [0.] * 1000
yfake = [0.] * 1000
for i in range(hs[Av[a]].GetNbinsX()):
xtrue[i] = hs[Av[a]].Integral(i, hs[Av[a]].GetNbinsX())
if "eta" in Av[a]: xtrue[i] = 1. - xtrue[i]
elif "Fake" in Av[a]:
for i in range(hs[Av[a]].GetNbinsX()):
yfake[i] = 1. - hs[Av[a]].Integral(i,
hs[Av[a]].GetNbinsX())
if "eta" in Av[a]: yfake[i] = -yfake[i] + 1.
gs[Av[a][0:-4]] = TGraph(
hs[Av[a]].GetNbinsX(),
array('f', xtrue[0:hs[Av[a]].GetNbinsX()]),
array('f', yfake[0:hs[Av[a]].GetNbinsX()]))
g = gs[Av[a][0:-4]]
g.SetLineColor(kRed if "btag" in Av[a] else (
kGreen + 2 if "eta" in Av[a] else kBlue))
gPad.SetGrid(1, 1)
gs["btag"].GetXaxis().SetLimits(0.7, 1.05)
gs["btag"].GetYaxis().SetRangeUser(0.0, 1.1)
gs["btag"].GetXaxis().SetTitle("Efficiency of matched b-jets")
gs["btag"].GetYaxis().SetTitle("Rejection of matched non b-jets")
gs["btag"].GetXaxis().SetNdivisions(504)
gs["btag"].Draw("AL")
gs["eta"].Draw("sameL")
gs["blik"].Draw("sameL")
legs[-1].AddEntry(gs["btag"], "CSV b-tag", "L")
legs[-1].AddEntry(gs["eta"], "|#eta|", "L")
legs[-1].AddEntry(gs["blik"], "b-likelihood", "L")
legs[-1].Draw()
c.SaveAs("plots/performance%s-2_%s.pdf" %
("Alt" if opts.alt else "", opts.sel))
c.Close()
c1s = fin.Get("CorrelationMatrixS")
c1b = fin.Get("CorrelationMatrixB")
gStyle.SetGridColor(kBlack)
c = TCanvas("c", "c", 900 * 2, 850 * 1)
c.Divide(2, 1)
c.cd(1)
gPad.SetGrid(1, 1)
gPad.SetTopMargin(0.14)
gPad.SetRightMargin(0.13)
c1s.SetMarkerColor(kBlack)
c1s.Draw("colz,text")
epavetext([
"Correlation matrix (signal)",
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B")
], 0.03, 0.88, 0.5, 0.97)
epavetext(["Linear correlation coefficients in %"], 0.52, 0.85, 0.99,
0.89, 0.025, 0)
gPad.Update()
gPad.RedrawAxis()
c.cd(2)
gPad.SetGrid(1, 1)
gPad.SetTopMargin(0.14)
gPad.SetRightMargin(0.13)
c1b.SetMarkerColor(kBlack)
c1b.Draw("colz,text")
epavetext([
"Correlation matrix (background)",
"%s selection" % ("Set A" if opts.sel == "NOM" else "Set B")
], 0.03, 0.88, 0.5, 0.97)
epavetext(["Linear correlation coefficients in %"], 0.52, 0.85, 0.99,
0.89, 0.025, 0)
gPad.Update()
gPad.RedrawAxis()
c.SaveAs("plots/performance%s-3_%s.pdf" %
("Alt" if opts.alt else "", opts.sel))
c.Close()
gStyle.SetGridColor(17)
fout.Write(fout.GetName(), TH1.kOverwrite)
fin.Close()
fout.Close()
def mkTemplateFunctions():
mp = parser()
opts, fout, samples = main(mp, False, False, True)
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
TYPE = opts.typetag
samples = INTERNALpicksamples(opts, jsons)
hDat, hRat, fFit, gUnc, fitter, covariant = INTERNALhistograms(opts)
c1, c2, c = INTERNALcanvases(opts)
can = TCanvas("main", "main")
ln = INTERNALline("1", float(opts.fBound[0]), float(opts.fBound[1]))
for iTag, Tag in enumerate(opts.catTags):
nCat = int(opts.mvaBins['mva%s' % Tag][0]) - 1
rCat = 0 if Tag == 'NOM' else 4
selsamples = [s for s in samples if s['incarnation'] == Tag]
fins = [x['tfile'] for x in selsamples]
l1('Running for %s - QCD' % Tag)
c2[Tag] = TCanvas('transfer_sel%s_%s' % (Tag, TYPE),
'transfer_sel%s_%s' % (Tag, TYPE), 600 * (nCat - 1),
600)
c2[Tag].Divide(nCat - 1, 1)
leg = INTERNALlegend(Tag)
leg.SetX1(0.7)
lleg = dict(
((Tag, iCat + 1), INTERNALlegend(Tag)) for iCat in range(nCat - 1))
for iCat in range(nCat):
jCat = iCat + rCat
if opts.merge:
if iCat == nCat - 1: continue
if iCat == nCat - 2: jCat = jCat * 10 + jCat + 1
l2('Running for CAT%d' % jCat)
# v = jsons['vars']['variables'][opts.variables[opts.variables.keys()[iTag]][0]]
# regular hists
# if v['xs']: hDat[(Tag,iCat)] = TH1F('hDat_sel%s_CAT%d'%(Tag,iCat),'hDat_sel%s_CAT%d'%(Tag,iCat),int(v['nbins_x']),v['xs'])
# else: hDat[(Tag,iCat)] = TH1F('hDat_sel%s_CAT%d'%(Tag,iCat),'hDat_sel%s_CAT%d'%(Tag,iCat),int(v['nbins_x']),int(v['xmin']),int(v['xmax']))
hDat[(Tag, iCat)] = TH1F(
'hDat_sel%s_CAT%d_%s' % (Tag, jCat, TYPE),
'hDat_sel%s_CAT%d_%s' % (Tag, jCat, TYPE),
int(float(opts.fBound[1]) - float(opts.fBound[0])) /
(10 if 'Dat' in TYPE else 20), float(opts.fBound[0]),
float(opts.fBound[1]))
print hDat[(Tag, iCat)].GetBinWidth(1)
h = hDat[(Tag, iCat)]
h = INTERNALstyleHist(h, iCat, markers, colours, TYPE)
can.cd()
# cut
CUT = TCut("mva%s>%.2f && mva%s<=%.2f" %
(Tag, float(opts.mvaBins["mva%s" % Tag][1][iCat + 1]),
Tag, float(opts.mvaBins["mva%s" % Tag][1][iCat + 2])))
if opts.merge:
CUT = TCut(
"mva%s>%.2f && mva%s<=%.2f" %
(Tag, float(opts.mvaBins["mva%s" % Tag][1][iCat + 1]), Tag,
float(opts.mvaBins["mva%s" % Tag][1][iCat + 3])))
###CUT = TCut("mvaNOM>%.2f && mvaNOM<=%.2f"%(float(opts.mvaBins["mva%s"%Tag][1][iCat+1]),float(opts.mvaBins["mva%s"%Tag][1][iCat+2])))
l3('Cutting with: %s' % CUT)
for fin in fins:
l4('Sample: %s' % fin.GetName())
CUT2, cutlabel = write_cuts(
["None"], ["None"],
reftrig=["None"],
sample=jsons['samp']['files'][os.path.split(
fin.GetName())[1]]['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.complexWghts[(Tag, 'old')],
trigequal=trigTruth(opts.usebool))
l4('Cutting with: %s' % CUT2)
# drawing
tin = fin.Get("Hbb/events")
l3('Drawing mbbReg[%d] --> %s' %
(1 if 'NOM' in Tag else 2, h.GetName()))
tin.Draw(
"mbbReg[%d]>>+%s" %
(1 if 'NOM' in Tag else 2, h.GetName()),
TCut(CUT) * TCut(CUT2))
fout.cd()
###tin.Draw("mbbReg[1]>>%s"%(h.GetName()),CUT)
if not opts.unblind: h = INTERNALblind(h, 100., 150.)
h.Scale(1. / h.Integral())
h.SetDirectory(0)
# ratio hist
hRat[(Tag, iCat)] = h.Clone(h.GetName().replace('hDat', 'hRat'))
r = hRat[(Tag, iCat)]
r.SetTitle(r.GetName())
r = INTERNALstyleHist(r, iCat, markers, colours, TYPE)
# dividing by control CAT
##print "Divide: ", hDat[(Tag,0)].GetName()
r.Divide(hDat[(Tag, 0)])
r.SetDirectory(0)
# fit
fFit[(Tag, iCat)] = TF1(h.GetName().replace('hDat', 'fitRatio'),
'pol1', float(opts.fBound[0]),
float(opts.fBound[1]))
f = fFit[(Tag, iCat)]
f.SetLineColor(colours[iCat])
h.Write(h.GetTitle(), TH1.kOverwrite)
if not iCat == 0:
r.Fit(f, "RQ")
fitter = TVirtualFitter.GetFitter()
covariant = TMatrixDSym()
covariant.Use(fitter.GetNumberTotalParameters(),
fitter.GetCovarianceMatrix())
nBins = 200
dx = (r.GetBinLowEdge(r.GetNbinsX() + 1) -
r.GetBinLowEdge(1)) / float(nBins)
vx = array(
'f',
[r.GetBinLowEdge(1) + (i + 1) * dx for i in range(nBins)])
vy = array('f', [f.Eval(vx[i]) for i in range(nBins)])
vex = array('f', [0.0] * nBins)
vey = array('f', [
sqrt(
pow(vx[i], 2) * covariant(1, 1) +
2.0 * vx[i] * covariant(0, 1) + covariant(0, 0))
for i in range(nBins)
])
gUnc[(Tag, iCat)] = TGraphErrors(nBins, vx, vy, vex, vey)
g = gUnc[(Tag, iCat)]
g.SetFillColor(colours[iCat])
g.SetFillStyle(3004)
c1[Tag].cd()
h.Draw('same E')
hDat[(Tag, 0)].GetYaxis().SetRangeUser(
0.0,
max(h.GetMaximum(), hDat[(Tag, 0)].GetMaximum()) * 1.02)
gPad.Update()
leg.AddEntry(h, 'CAT%d' % jCat, 'P')
c2[Tag].cd(iCat)
ln.Draw()
g.Draw('same E3')
r.Draw('same')
ll = lleg[(Tag, iCat)]
ll.AddEntry(h, 'CAT%d / CAT%d' % (jCat, rCat), 'P')
ll.SetY1(ll.GetY2() - ll.GetNRows() * 0.06)
ll.SetTextSize(0.04)
ll.Draw()
r.GetYaxis().SetRangeUser(0.0, 2.0)
r.Write(r.GetTitle(), TH1.kOverwrite)
g.Write(r.GetTitle().replace('hRat', 'gRat'), TH1.kOverwrite)
else:
c1[Tag] = TCanvas('MbbShape_sel%s_%s' % (Tag, TYPE),
'MbbShape_sel%s_%s' % (Tag, TYPE), 900, 600)
c1[Tag].cd()
gPad.SetLeftMargin(0.12)
gPad.SetRightMargin(0.03)
h.GetYaxis().SetTitleOffset(0.8)
h.SetFillColor(kGray)
h.Draw('hist')
leg.AddEntry(h, 'CAT%d' % jCat, 'F')
fout.cd()
f.Write(f.GetName(), TH1.kOverwrite)
c1[Tag].cd()
leg.SetY1(leg.GetY2() - leg.GetNRows() * 0.06)
leg.Draw()
c1[Tag].SaveAs('plots/transfer/%s%s.png' %
(c1[Tag].GetName(), "_merged" if opts.merge else ""))
c1[Tag].SaveAs('plots/transfer/%s%s.pdf' %
(c1[Tag].GetName(), "_merged" if opts.merge else ""))
c2[Tag].SaveAs('plots/transfer/%s%s.png' %
(c2[Tag].GetName(), "_merged" if opts.merge else ""))
c2[Tag].SaveAs('plots/transfer/%s%s.pdf' %
(c2[Tag].GetName(), "_merged" if opts.merge else ""))
#c.SaveAs('plots/transfer/%s.png'%c.GetName())
# clean
for f in samples:
f['tfile'].Close()
fout.Close()
def mkBDTcorrelations():
mp = parser()
opts, fout, samples = main(mp, False, False, True)
sels = ['NOM', 'VBF']
jsons = INTERNALprepare(opts)
markers, colours = INTERNALstyle()
selsamples = INTERNALpicksamples(opts, jsons)
can = TCanvas("main", "main", 650, 600)
hProf = INTERNALhistograms(opts, sels, jsons)
#INTERNALcanvases(opts)
l1("Creating profiles")
if not opts.read:
for isel, sel in enumerate(sels):
ssel = [s for s in selsamples if sel in s['fname']]
for s in ssel:
l2("Running for %s" % s['tag'])
cut, cutlabel = write_cuts(["None"], ["None"],
reftrig=["None"],
sample=s['tag'],
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.complexWghts[(sel,
'old')],
trigequal=trigTruth(opts.usebool))
#cut = re.findall('\*.*',cut)[0][2:-1].replace('pu','ev.pu').replace('trig','ev.trig')
if opts.debug:
l3("Cut %s: \n\t\t\t%s%s%s: \n\t\t\t%s" %
(s['tag'], blue, cutlabel, plain, cut))
cutextra = "mbbReg[%d]>=80. && mbbReg[%d]<=200." % (
1 if sel == 'NOM' else 2, 1 if sel == 'NOM' else 2)
for v in [
jsons['vars']['variables'][vv] for vv in opts.variable
]:
if sel == 'NOM' and '[2]' in v['root']: continue
if sel == 'VBF' and '[1]' in v['root']: continue
if 'mva' in v and not sel in v: continue
s['tree'].Draw(
"%s:%s>>+%s" %
(v['root'], "mva%s" % sel,
hProf[(sel, v['var'], 'BDT', 'QCD'
if 'QCD' in s['fname'] else 'DAT')].GetName()),
TCut(cutextra) * TCut(cut), "prof")
if 'mbbReg' in v['var']: continue
s['tree'].Draw(
"%s:%s>>+%s" %
(v['root'], "mbbReg[%d]" % (1 if sel == 'NOM' else 2),
hProf[(sel, v['var'], 'mbbReg', 'QCD'
if 'QCD' in s['fname'] else 'DAT')].GetName()),
TCut(cutextra) * TCut(cut), "prof")
else:
for k in hProf.iterkeys():
hProf[k] = fout.Get("h%s_sel%s_%s_%s" % (k[3], k[0], k[1], k[2]))
k = list(set([x[0:3] for x in hProf.iterkeys()]))
for ik in k:
low = min(
hProf[(ik[0], ik[1], ik[2],
'QCD')].GetBinContent(hProf[(ik[0], ik[1], ik[2],
'QCD')].GetMinimumBin()),
hProf[(ik[0], ik[1], ik[2],
'DAT')].GetBinContent(hProf[(ik[0], ik[1], ik[2],
'DAT')].GetMinimumBin()))
hig = max(
hProf[(ik[0], ik[1], ik[2],
'QCD')].GetBinContent(hProf[(ik[0], ik[1], ik[2],
'QCD')].GetMaximumBin()),
hProf[(ik[0], ik[1], ik[2],
'DAT')].GetBinContent(hProf[(ik[0], ik[1], ik[2],
'DAT')].GetMaximumBin()))
med = hProf[(ik[0], ik[1], ik[2], 'DAT')].GetMean(2)
dif = hig - low
setlow = med - 1.6 * dif
sethig = med + 1.6 * dif
if not 'cos' in ik[1]:
setlow = max(setlow, 0)
limits = {
'dEtaqq1': [2, 7, 2, 7],
'dPhiqq1': [0, 3, 0, 3],
'jetBtag00': [0.5, 1.2, 0.8, 1.0],
'jetBtag01': [0.0, 1.2, 0.55, 0.75],
'jetQGLNOM0': [0, 1, 0.5, 0.65],
'jetQGLNOM1': [0, 1, 0.35, 0.55],
'jetQGLNOM2': [0, 1, 0.5, 0.7],
'jetQGLNOM3': [0, 1, 0.5, 0.7],
'mqq1': [0, 2500, 500, 800],
'mbbReg1': [115, 145, 115, 145],
'cosTheta1': [-0.35, 0.35, -0.2, 0.2],
'jetQGLVBF0': [0, 1, 0.4, 0.55],
'jetQGLVBF1': [0, 1, 0.3, 0.5],
'jetQGLVBF2': [0, 1, 0.55, 0.75],
'jetQGLVBF3': [0, 1, 0.5, 0.7],
'mqq2': [0, 2500, 1000, 1300],
'mbbReg2': [115, 145, 115, 145],
'cosTheta2': [-0.35, 0.35, -0.2, 0.2],
'dEtaqq2': [2, 7, 2, 7],
'dPhiqq2': [0, 3, 0, 3],
'softHt': [0, 100, 25, 50],
'softN2': [0, 10, 4, 7]
} #[3,7,4,6], [0,3,1,2] [0,3,1.5,2.5]
if ik[1] in limits:
if ik[2] == 'BDT':
setlow = limits[ik[1]][0]
sethig = limits[ik[1]][1]
else:
setlow = limits[ik[1]][0] #2]
sethig = limits[ik[1]][1] #3]
# if 'jetBtag01' in ik[1] and ik[0]=='VBF' and ik[2]=='mbbReg':
# setlow = 0.4
# sethig = 0.55
hProf[(ik[0], ik[1], ik[2],
'DAT')].GetYaxis().SetRangeUser(setlow, sethig)
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetYaxis().SetTitleOffset(1.4)
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetXaxis().SetTitleOffset(1.0)
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetYaxis().SetNdivisions(507)
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetXaxis().SetNdivisions(507)
hProf[(ik[0], ik[1], ik[2], 'DAT')].Draw("axis")
h = INTERNALgraph(hProf[(ik[0], ik[1], ik[2], 'DAT')])
h.SetMarkerStyle(20)
h.SetMarkerSize(0.8)
h.SetMarkerColor(kBlack)
h.SetLineColor(kBlack)
h.SetFillStyle(0)
h.Draw("same pz")
g = INTERNALgraph(hProf[(ik[0], ik[1], ik[2], 'QCD')])
# hProf[(ik[0],ik[1],ik[2],'QCD')].SetMarkerStyle(25)
# hProf[(ik[0],ik[1],ik[2],'QCD')].SetMarkerColor(kBlue)
# hProf[(ik[0],ik[1],ik[2],'QCD')].Draw("same e")
g.SetMarkerStyle(25)
g.SetMarkerColor(kBlue)
g.SetLineColor(kBlue)
g.SetFillStyle(0)
g.Draw("same pz")
leg = TLegend(0.62, 0.75, 0.9, 0.92,
"%s selection" % (ik[0].strip('sel')))
leg.SetFillStyle(-1)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.045)
#leg.AddEntry(hProf[(ik[0],ik[1],ik[2],'DAT')],'Data')
#leg.AddEntry(hProf[(ik[0],ik[1],ik[2],'QCD')],'QCD')
leg.AddEntry(h, 'Data', 'LP')
leg.AddEntry(g, 'QCD', 'LP')
leg.SetY1(leg.GetY2() - (leg.GetNRows() + 1) * 0.05)
leg.Draw()
can.SaveAs(
"plots/%s.png" %
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetName().replace('hDAT', 'h'))
can.SaveAs(
"plots/%s.pdf" %
hProf[(ik[0], ik[1], ik[2], 'DAT')].GetName().replace('hDAT', 'h'))
fout.cd()
for h in hProf.itervalues():
h.Write(h.GetName(), TH1.kOverwrite)
# clean
fout.Close()
def get2DMap(opts,fout,samples,variables,sel,trg,ref,vx,vy):
# info
l1("Creating 2D maps for (%s,%s):"%(vx[0],vy[0]))
print "+ (sel,trg,ref): (%s,%s,%s)"%(sel,trg,ref)
jsoninfo = json.loads(filecontent(opts.jsoninfo))
groups = list(set([jsoninfo['groups'][x['tag']] for x in samples]))
samplesbygroup = {}
paves = []
for group in groups:
samplesbygroup[group] = [sample for sample in samples if jsoninfo['groups'][sample['tag']]==group]
ratios = []
if 'JetMon' in groups and 'QCD' in groups:
ratios += ['JetMon-QCD']
# storage
gDirectory.cd("%s:/"%fout.GetName())
for group in groups:
makeDirsRoot(fout,'2DMaps/%s'%group)
# calculate
xvals = array('f',[float(x) for x in vx[1].split("#")])
yvals = array('f',[float(x) for x in vy[1].split("#")])
maps = {}
cuts = {}
inroot('TTree *t = 0;')
# style
gStyle.SetPalette(20) #13
gStyle.SetPaintTextFormat("7.2f")
# To Save
if opts.notext: canvas = TCanvas("cmap","cmap",1600,1200)
else: canvas = TCanvas("cmap","cmap",1800,1200)
gStyle.SetLineScalePS(2.2)
canvas.cd()
set_palette()
gPad.SetGrid(0,0)
if not opts.notext: gPad.SetRightMargin(0.25)
else: gPad.SetRightMargin(0.12)
print gPad.GetTopMargin()
gPad.SetTopMargin(0.065)
# LOOP over ALL GROUPS
itest = 0
for group in groups:
l2("Filling for group: %s%s%s"%(purple,group,plain))
maps[group] = {}
cuts[group] = {}
for tag in ['Num','Den','Rat']:
if opts.numonly and not tag=='Num': continue
trg,trg_orig = trigData(opts,'',trg)
mapname = "2DMap_%s-%s_s%s-t%s-r%s-d%s_%s-%s"%(group,tag,'-'.join(sorted(sel)),'-'.join(trg_orig),'-'.join(ref),'-'.join(trg),vx[0],vy[0])
maptitle = "%s;%s;%s"%(mapname,variables[vx[0]]['title_x'],variables[vy[0]]['title_x'])
trg = dc(trg_orig)
maps[group][tag] = fout.FindObjectAny(mapname)
if (not maps[group][tag]) or (not len(xvals)-1==maps[group][tag].GetXaxis().GetNbins()) or (not len(yvals)-1==maps[group][tag].GetYaxis().GetNbins()) or opts.redo:
maps[group][tag] = TH2F(mapname,maptitle,len(xvals)-1,xvals,len(yvals)-1,yvals)
maps[group][tag].Sumw2()
## LOOP over ALL SAMPLES
for s in sorted(samplesbygroup[group],key=lambda x:('QCD' in x['tag'],not 'WJets' in x['tag'],jsoninfo['crosssections'][x['tag']])):
if tag=='Rat': continue
l3("Filling for sample: %s%s (%s)%s"%(cyan,s['tag'],tag,plain))
trg,trg_orig = trigData(opts,s,trg)
inroot('t = (TTree*)%s.gett();'%s['pointer'])
cuts[group][tag] = write_cuts(sel,trg if tag=='Num' else [],sample=s['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,reftrig=ref,trigequal=trigTruth(opts.usebool),weight=opts.weight)[0] #,varskip=[variables[vx[0]]['root'],variables[vy[0]]['root']]
if opts.debug: print yellow,cuts[group][tag],plain
inroot('t->Draw("%s:%s>>+%s",TCut("%s"));'%(variables[vy[0]]['root'],variables[vx[0]]['root'],maps[group][tag].GetName(),cuts[group][tag]))
trg = dc(trg_orig)
else:
l3("Loaded from file for group: %s%s%s"%(cyan,group,plain))
## END LOOP over ALL SAMPLES
# to save
path = '%s/../trigger/plots/%s/2DMaps/%s'%(basepath,fout.GetName().split('/')[-1][:-5],group)
makeDirs(path)
if not opts.numonly:
# ratio
##CHECK THIS!!!##
maps[group]['Rat'].Divide(maps[group]['Num'],maps[group]['Den'],1.0,1.0,'B')
##ALTERNATIVE# for ix in range(0,maps[group]['Num'].GetNbinsX()+1):
##ALTERNATIVE# for iy in range(0,maps[group]['Num'].GetNbinsX()+1):
##ALTERNATIVE# v1 = maps[group]['Num'].GetBinContent(ix,iy)
##ALTERNATIVE# ev1 = maps[group]['Num'].GetBinError(ix,iy)
##ALTERNATIVE# v2 = maps[group]['Den'].GetBinContent(ix,iy)
##ALTERNATIVE# ev2 = maps[group]['Den'].GetBinError(ix,iy)
##ALTERNATIVE# if not v2 == 0:
##ALTERNATIVE# div = v1/v2
##ALTERNATIVE# ediv = sqrt(div*(1.-div)/v2)*ev2/sqrt(v2)
##ALTERNATIVE# else:
##ALTERNATIVE# div = 0
##ALTERNATIVE# ediv = 0
##ALTERNATIVE# maps[group]['Rat'].SetBinContent(ix,iy,div)
##ALTERNATIVE# maps[group]['Rat'].SetBinError(ix,iy,ediv)
#$ maps[group]['Rat'] = TEfficiency(maps[group]['Num'],maps[group]['Den'])
maps[group]['Rat'].SetName(mapname)
maps[group]['Rat'].SetTitle(maptitle)
# save
gDirectory.cd('%s:/2DMaps/%s'%(fout.GetName(),group))
for tag in ['Num','Den','Rat']:
if opts.numonly and not tag=='Num': continue
if not tag in maps[group]: continue
#$ if tag=='Rat':
#$ maps[group][tag].Paint("colz,text90,error")
#$ maps[group][tag].GetPaintedHistogram().SetTitleOffset(1.0,"Y")
#$ else: maps[group][tag].SetTitleOffset(1.0,"Y")
#maps[group][tag].GetXaxis().SetTitle(variables[vx[0]]['title_x'])
#maps[group][tag].GetYaxis().SetTitle(variables[vy[0]]['title_x'])
maps[group][tag].SetTitleSize(maps[group][tag].GetTitleSize("X")*1.1,"XY")
maps[group][tag].SetTitleOffset(maps[group][tag].GetTitleOffset()*1.0 if not opts.notext else maps[group][tag].GetTitleOffset()*1.05,"X")
maps[group][tag].SetTitleOffset(maps[group][tag].GetTitleOffset()*1.0 if not opts.notext else maps[group][tag].GetTitleOffset()*(1.14 if not "VBF" in trg else 1.00),"Y")
if "VBF" in trg: maps[group][tag].SetLabelSize(maps[group][tag].GetLabelSize("X")*0.95,"X")
#maps[group][tag].SetTitleOffset(maps[group][tag].GetTitleOffset()*0.8,"Z")
maps[group][tag].SetMarkerSize((1.25 if not ('mqq' in vx[0] or 'mqq' in vy[0]) else 0.85) if not (group=='QCD' and not tag=='Rat') else 1.0)
if "VBF" in trg: maps[group][tag].SetMarkerSize(maps[group][tag].GetMarkerSize()*0.95)
maps[group][tag].GetXaxis().SetTickLength(0.03)
maps[group][tag].GetYaxis().SetTickLength(0.016)
maps[group][tag].GetZaxis().SetRangeUser(0,0.8 if not "VBF" in trg else 1.0)
maps[group][tag].GetYaxis().SetNdivisions(505 if not 'VBF' in trg else 507)
maps[group][tag].SetTitle("")
if 'VBF' in trg:
gPad.SetLogx(1)
maps[group][tag].GetXaxis().SetMoreLogLabels()
maps[group][tag].SetMarkerSize(maps[group][tag].GetMarkerSize()*0.75)
gStyle.SetHistMinimumZero(kFALSE)
if maps[group][tag].GetEntries()==0: maps[group][tag].SetBinContent(0,0,-1e-16)
maps[group][tag].SetMinimum(0.0 if not "VBF" in trg else 0.0)
maps[group][tag].SetMaximum(0.8 if not "VBF" in trg else 1.0)
maps[group][tag].SetContour(999)
set_palette()
maps[group][tag].Draw("colz,text,error")
grid = mapgrid(maps[group][tag],2,2 if not "VBF" in trg else 1,5)
gPad.Update()
try:
palette = maps[group][tag].GetListOfFunctions().FindObject("palette")
palette.SetX1NDC(0.89 - (0.13 if not opts.notext else 0.0))
palette.SetX2NDC(0.93 - (0.13 if not opts.notext else 0.0))
palette.SetY1NDC(0.1)
palette.SetY2NDC(0.935)
maps[group][tag].GetZaxis().SetTickLength(0.02)
gPad.Update()
except:
continue
canvas.Modified()
canvas.Update()
if not opts.notext:
text,selleg = addText(opts,group,tag,vx,vy,sel,trg,ref)
text.Draw("same")
selleg.Draw("same")
ttl = topleft("Set %s trigger efficiency (%s)"%("A" if not "VBF" in trg else "B","data" if not "QCD" in group else "simulation"))
ttr = topright("%.1f fb^{-1} (8 TeV)"%(19.8 if not "VBF" in trg else 18.3))
maps[group][tag].Write(maps[group][tag].GetName(),TH1.kOverwrite)
canvas.SaveAs('%s/%s%s.png'%(path,maps[group][tag].GetName(),'' if not opts.notext else '_noleg'))
canvas.SaveAs('%s/%s%s.pdf'%(path,maps[group][tag].GetName(),'' if not opts.notext else '_noleg'))
gStyle.SetHistMinimumZero(kTRUE)
l3("Written %s map to (eog %s/%s%s.png)"%(tag,path,maps[group][tag].GetName(),'' if not opts.notext else '_noleg'))
# END LOOP over ALL GROUPS
# FOCUS ON RATIO MAPS JetMon / QCD
gDirectory.cd("%s:/"%fout.GetName())
for ratio in ratios:
if opts.numonly: continue
# store
makeDirsRoot(fout,'2DMaps/%s'%ratio)
maps[ratio] = {}
l2("Getting ratio for: %s%s%s"%(purple,ratio,plain))
# create
trg,trg_orig = trigData(opts,'',trg)
mapname = "2DMap_%s-%s_s%s-t%s-r%s-d%s_%s-%s"%(ratio,'Rat','-'.join(sorted(sel)),'-'.join(trg_orig),'-'.join(ref),'-'.join(trg),vx[0],vy[0])
maptitle = "%s;%s;%s"%("",variables[vx[0]]['title_x'],variables[vy[0]]['title_x']) #mapname
trg = dc(trg_orig)
maps[ratio]['Rat'] = TH2F(mapname,maptitle,len(xvals)-1,xvals,len(yvals)-1,yvals)
maps[ratio]['Rat'].Sumw2()
#$ maps[ratio]['Rat'].Divide(maps[ratio.split('-')[0]]['Rat'].GetPaintedHistogram(),maps[ratio.split('-')[1]]['Rat'].GetPaintedHistogram())
maps[ratio]['Rat'].Divide(maps[ratio.split('-')[0]]['Rat'],maps[ratio.split('-')[1]]['Rat'])
###### CORRECTION FACTOR
##### for ix in range(maps[ratio]['Rat'].GetNbinsX()+1):
##### for iy in range(maps[ratio]['Rat'].GetNbinsY()+1):
##### x = maps[ratio]['Rat'].GetXaxis().GetBinCenter(ix)
##### y = maps[ratio]['Rat'].GetYaxis().GetBinCenter(iy)
##### if y >= 3.5 and y < 4.0: maps[ratio]['Rat'].SetBinContent(ix,iy,maps[ratio]['Rat'].GetBinContent(ix,iy)*1.0/0.8)
##### elif y >= 4.0 and y < 4.5: maps[ratio]['Rat'].SetBinContent(ix,iy,maps[ratio]['Rat'].GetBinContent(ix,iy)*1.0/0.92)
##### elif y >= 4.5 and y < 5.0: maps[ratio]['Rat'].SetBinContent(ix,iy,maps[ratio]['Rat'].GetBinContent(ix,iy)*1.0/1.0)
##### elif y >= 5.0 and y < 5.5: maps[ratio]['Rat'].SetBinContent(ix,iy,maps[ratio]['Rat'].GetBinContent(ix,iy)*1.0/1.15)
# plot
canvas.cd()
#maps[ratio]['Rat'].GetXaxis().SetTitle(variables[vx[0]]['title_x'])
#maps[ratio]['Rat'].GetYaxis().SetTitle(variables[vy[0]]['title_x'])
maps[ratio]['Rat'].SetMarkerSize(1.25 if not ('mqq' in vx[0] or 'mqq' in vy[0]) else 0.85)
maps[ratio]['Rat'].SetTitleSize(maps[ratio]['Rat'].GetTitleSize("X")*1.1,"XY")
maps[ratio]['Rat'].SetTitleOffset(maps[ratio]['Rat'].GetTitleOffset()*1.0 if not opts.notext else maps[ratio]['Rat'].GetTitleOffset()*1.05,"X")
maps[ratio]['Rat'].SetTitleOffset(maps[ratio]['Rat'].GetTitleOffset()*1.0 if not opts.notext else maps[ratio]['Rat'].GetTitleOffset()*(1.14 if not "VBF" in trg else 1.00),"Y")
if "VBF" in trg: maps[ratio]['Rat'].SetLabelSize(maps[ratio]['Rat'].GetLabelSize("X")*0.95,"X")
if "VBF" in trg: maps[ratio]['Rat'].SetMarkerSize(maps[ratio]['Rat'].GetMarkerSize()*0.95)
maps[ratio]['Rat'].GetXaxis().SetTickLength(0.03)
maps[ratio]['Rat'].GetYaxis().SetTickLength(0.016)
maps[ratio]['Rat'].GetZaxis().SetRangeUser(0,1.4 if not "VBF" in trg else 2.0)
maps[ratio]['Rat'].GetYaxis().SetNdivisions(505 if not 'VBF' in trg else 507)
if 'VBF' in trg:
gPad.SetLogx(1)
maps[ratio]['Rat'].GetXaxis().SetMoreLogLabels()
maps[ratio]['Rat'].SetMarkerSize(maps[ratio]['Rat'].GetMarkerSize()*0.75)
gStyle.SetHistMinimumZero(kFALSE)
set_palette()
maps[ratio]['Rat'].Draw('colz,error,text')
maps[ratio]['Rat'].SetMinimum(0.6 if not "VBF" in trg else 0.0)
maps[ratio]['Rat'].SetMaximum(1.4 if not "VBF" in trg else 1.6)
grid = mapgrid(maps[ratio]['Rat'],2,2 if not "VBF" in trg else 1,4)
#for ix in range(1,maps[ratio]['Rat'].GetNbinsX()+1):
# for iy in range(1,maps[ratio]['Rat'].GetNbinsY()+1):
# if maps[ratio]['Rat'].GetBinContent(ix,iy)==0:
# pave = TPave(maps[ratio]['Rat'].GetXaxis().GetBinCenter(ix)-0.033,maps[ratio]['Rat'].GetYaxis().GetBinCenter(iy)-0.03,maps[ratio]['Rat'].GetXaxis().GetBinCenter(ix)+0.033,maps[ratio]['Rat'].GetYaxis().GetBinCenter(iy)+0.03,0)
# pave.SetFillColor(kWhite)
# pave.SetFillStyle(1001)
# canvas.cd()
# pave.Draw()
# paves += [pave]
gPad.Update()
maps[ratio]['Rat'].GetZaxis().SetTickLength(0.02)
palette = maps[ratio]['Rat'].GetListOfFunctions().FindObject("palette")
palette.SetX1NDC(0.89 - (0.11 if not opts.notext else 0.0))
palette.SetX2NDC(0.93 - (0.11 if not opts.notext else 0.0))
palette.SetY1NDC(0.1)
palette.SetY2NDC(0.935)
gPad.Update()
canvas.Modified()
canvas.Update()
if not opts.notext:
text,selleg = addText(opts,'Data / QCD','SF',vx,vy,sel,trg,ref)
text.Draw("same")
selleg.Draw("same")
ttl = topleft("Set %s trigger efficiency (data/simulation)"%("A" if not "VBF" in trg else "B"))
ttr = topright("%.1f fb^{-1} (8 TeV)"%(19.8 if not "VBF" in trg else 18.3))
# save
gDirectory.cd('%s:/2DMaps/%s'%(fout.GetName(),ratio))
maps[ratio]['Rat'].Write(maps[ratio]['Rat'].GetName(),TH1.kOverwrite)
path = "%s/../trigger/plots/%s/2DMaps/%s"%(basepath,fout.GetName().split('/')[-1][:-5],ratio)
makeDirs(path)
for tag in ['Num','Den','Rat']:
if not tag in maps[ratio]: continue
canvas.SaveAs("%s/%s%s.png"%(path,maps[ratio][tag].GetName(),'' if not opts.notext else '_noleg'))
canvas.SaveAs("%s/%s%s.pdf"%(path,maps[ratio][tag].GetName(),'' if not opts.notext else '_noleg'))
gStyle.SetHistMinimumZero(kTRUE)
l2("Written map to (eog %s/%s%s.png)"%(path,maps[ratio]['Rat'].GetName(),'' if not opts.notext else '_noleg'))
# canvas.Close()
# clean
canvas.Close()
def datamc():
# options
mp = parser()
opts, fout, samples, variables = main.main(mp, False, True, True)
# root setup
ROOTsetup()
eps = 0.0001
# samples / variables
ji, jv, js, Lsamples = loadSamples(opts, samples)
Lvariables = {
k: v
for (k, v) in variables.iteritems() if k in opts.variable
}
# canvas
can = TCanvas("c", "c", 900, 750)
can.cd()
# histos
histos = hists(Lsamples, Lvariables, opts.selection)
stacks = {}
##################################################
l1("Filling histograms")
for s in opts.selection:
for t in opts.trigger:
# cms paves
pcms1, pcms2 = FormatCMSPaves(opts, s)
#### # cuts
#### cut,cutlabel = write_cuts(s,t,reftrig=["None"],sample=Lsamples[Lsamples.keys()[0]]['i']['tag'],jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal=trigTruth(opts.usebool))
#### cut1,cut2 = cut.split(' * ')[0][1:],cut.split(' * ')[1][:-1]
##################################################
# sample loop
for sn, si in sorted(Lsamples.iteritems()):
l2("Sample: %s" % sn)
st = si['i']['tag']
sg = si['g']
ca, calabel = write_cuts(s,
t,
reftrig=["None"],
sample=st,
jsonsamp=opts.jsonsamp,
jsoncuts=opts.jsoncuts,
weight=opts.weight,
trigequal=trigTruth(opts.usebool))
ca1, ca2 = ca.split(' * ')[0][1:], ca.split(' * ')[1][:-1]
n = si['t'].GetEntries()
print ca2
# variable loop
for vn, vi in sorted(Lvariables.iteritems()):
l3(vn)
ht = hTag(st, vn, s[0])
si['t'].Draw("%s>>%s" % (vi['root'], ht), "%s" % ca2)
##################################################
# stacking
for sn, si in sorted(Lsamples.iteritems()):
sg = si['g']
st = si['i']['tag']
for vn, vi in sorted(Lvariables.iteritems()):
hg = hTag(sg, vn, s[0])
ht = hTag(st, vn, s[0])
Hg = histos[hg]
Ht = histos[ht]
Hg.Add(Ht)
##################################################
# k-factor
INTEGRALS = {"Data": 0.0, "QCD": 0.0, "Other": 0.0, "TTJets": 0.0}
if "KF" in opts.weight[1] and not ('TP' in t[0]):
#print "if"
for ig, g in enumerate(
list(set([x['g']
for (k, x) in Lsamples.iteritems()]))):
var = Lvariables.keys()[0]
hg = hTag(g, var, s[0])
if g == "VBF125": continue
elif g == "Data":
INTEGRALS["Data"] += float(histos[hg].Integral())
elif g == "QCD":
INTEGRALS["QCD"] += float(histos[hg].Integral())
else:
INTEGRALS["Other"] += float(histos[hg].Integral())
kfactor = (INTEGRALS["Data"] -
INTEGRALS["Other"]) / INTEGRALS["QCD"]
l1("K-factor: %.2f" % kfactor)
elif "KF" in opts.weight[1]:
#print "elif"
for ig, g in enumerate(
list(set([x['g']
for (k, x) in Lsamples.iteritems()]))):
var = Lvariables.keys()[0]
hg = hTag(g, var, s[0])
if g == "VBF125": continue
elif g == "Data":
INTEGRALS["Data"] += float(histos[hg].Integral())
elif g == "TTJets":
INTEGRALS["TTJets"] += float(histos[hg].Integral())
else:
INTEGRALS["Other"] += float(histos[hg].Integral())
kfactor = (INTEGRALS["Data"] -
INTEGRALS["Other"]) / INTEGRALS["TTJets"]
l1("K-factor: %.2f" % kfactor)
##################################################
# groups
l1("Group iteration")
can.Clear()
for vn, vi in sorted(Lvariables.iteritems()):
fout.cd()
# set pads
p1, p2 = FormatPads(can)
##################################################
# top pad
p1.cd()
# containers
l2("Variable: %s" % (vn))
DRAW = {}
hs = "s_v%s_c%s" % (vn, s[0])
S = THStack(hs, hs)
L = TLegend(gStyle.GetPadLeftMargin() + 0.03, 0.5,
gStyle.GetPadLeftMargin() + 0.03 + 0.23 * 3,
1. - gStyle.GetPadTopMargin() - 0.025)
FormatLegend(L)
# group loop
for ig, g in enumerate(
sorted(list(
set([x['g'] for (k, x) in Lsamples.iteritems()])),
key=lambda y:
(not '125' in y, not 'WJets' in y, histos[hTag(
y, vn, s[0])].Integral()))):
l3("%s" % (g))
hg = hTag(g, vn, s[0])
Hg = histos[hg]
print Hg.Integral()
# underflow
Hg.SetBinContent(
1, 0.5 * (Hg.GetBinContent(0) + Hg.GetBinContent(1)))
Hg.SetBinError(
1,
sqrt(
pow(Hg.GetBinError(0), 2.) +
pow(Hg.GetBinError(1), 2.)))
# overflow
Hg.SetBinContent(
Hg.GetNbinsX(),
0.5 * (Hg.GetBinContent(Hg.GetNbinsX()) +
Hg.GetBinContent(Hg.GetNbinsX() + 1)))
Hg.SetBinError(
Hg.GetNbinsX(),
sqrt(
pow(Hg.GetBinError(Hg.GetNbinsX()), 2.) +
pow(Hg.GetBinError(Hg.GetNbinsX() + 1), 2.)))
# type handling
if g == "Data":
Hg.SetMarkerStyle(20)
Hg.SetMarkerColor(kBlack)
Hg.SetMarkerSize(1.2)
DRAW["Data"] = Hg
elif g == "VBF125":
Hg.SetLineStyle(1)
Hg.SetLineColor(ji['colours'][g])
Hg.SetLineWidth(3)
Hg.Scale(10.)
DRAW["SIG"] = Hg
elif g == "GF125":
Hg.SetLineStyle(7)
Hg.SetLineColor(ji['colours'][g])
Hg.SetLineWidth(3)
Hg.Scale(10.)
DRAW["SIGGF"] = Hg
else:
Hg.SetLineStyle(1)
Hg.SetLineColor(kBlack)
Hg.SetFillStyle(1001)
Hg.SetFillColor(ji['colours'][g])
if g == "QCD" and (not "TP"
in t[0]) and "KF" in opts.weight[1]:
Hg.Scale(kfactor)
if g == "TTJets" and (
"TP" in t[0]) and "KF" in opts.weight[1]:
Hg.Scale(kfactor)
if not Hg.GetEntries() == 0: S.Add(Hg)
# Full stack (bkg)
DRAW["BKG"] = S
S.Draw()
Sall = FormatStack(S)
# MC err
histos[hTag("MCerr", vn,
s[0])] = Sall.Clone(hTag("MCerr", vn, s[0]))
Hg = histos[hTag("MCerr", vn, s[0])]
Hg.SetFillStyle(3004)
Hg.SetFillColor(kGray + 2) #kBlack)
Hg.SetMarkerSize(0)
DRAW["MCerr"] = Hg
# Fill legend
L.AddEntry(histos[hTag("Data", vn, s[0])], "Data", "P")
L.AddEntry(
histos[hTag("QCD", vn, s[0])], "%s%s" %
("QCD", " (x%.2f)" % kfactor if
("KF" in opts.weight[1] and not "TP" in t[0]) else ""),
"F")
L.AddEntry(histos[hTag("ZJets", vn, s[0])], "%s" % ("ZJets"),
"F")
L.AddEntry(histos[hTag("VBF125", vn, s[0])], "10x VBF H(125)",
"L")
if hTag("Tall", vn, s[0]) in histos:
L.AddEntry(
histos[hTag("Tall", vn, s[0])], "%s%s" %
("T", " (x%.2f)" % kfactor if
("KF" in opts.weight[1] and "TP" in t[0]) else ""),
"F")
else:
L.AddEntry(
histos[hTag("TTJets", vn, s[0])], "%s%s" %
("TTJets", " (x%.2f)" % kfactor if
("KF" in opts.weight[1] and "TP" in t[0]) else ""),
"F")
L.AddEntry(histos[hTag("WJets", vn, s[0])], "%s" % ("WJets"),
"F")
L.AddEntry(histos[hTag("GF125", vn, s[0])], "10x GF H(125)",
"L")
if not hTag("Tall", vn, s[0]) in histos:
L.AddEntry(histos[hTag("singleT", vn, s[0])],
"%s" % ("singleT"), "F")
L.AddEntry(histos[hTag("MCerr", vn, s[0])], "MC stat. unc.",
"F")
# Draw
DRAW["BKG"].Draw("hist")
DRAW["Data"].Draw("PE,same")
DRAW["SIG"].Draw("hist,same")
DRAW["SIGGF"].Draw("hist,same")
DRAW["MCerr"].Draw("E2,same")
# Edit legend
L.SetY1(L.GetY2() - L.GetNRows() * 0.04)
L.Draw()
# Draw paves
pcms1.Draw()
pcms2.Draw()
# Edit canvas
gPad.SetLogy(1)
gPad.RedrawAxis()
p1.Write(p1.GetName() +
("NOM" if "NOM" in opts.selection[0] else "VBF") + vn)
##################################################
# bottom pad
p2.cd()
# histo = 1
one = DRAW["Data"].Clone("one")
for ibin in range(0, one.GetNbinsX() + 2):
one.SetBinContent(ibin, 1.)
one.SetBinError(ibin, 0.)
# ratio Data/MC - 1
rat = DRAW["Data"].Clone(DRAW["Data"].GetName().replace(
'h', 'hRat'))
FormatRatio(rat)
rat.Divide(DRAW["BKG"].GetStack().Last())
rat.Add(one, -1.)
histos[hTag("Data/MC", vn, s[0])] = rat
# ratio MCerr/MC - 1
ratMCerr = histos[hTag("MCerr", vn, s[0])].Clone("ratMCerr")
ratMCerr.Divide(DRAW["BKG"].GetStack().Last())
ratMCerr.Add(one, -1.)
histos[hTag("MCerrDataMC", vn, s[0])] = ratMCerr
# Draw
rat.Draw()
ratMCerr.Draw("E2,same")
# Edit pad
rat.GetYaxis().SetRangeUser(-1.0 + eps, 1.0 - eps)
gPad.SetGridy(1)
gPad.Update()
line = TF1("l1", "0.", gPad.GetUxmin(), gPad.GetUxmax())
line.SetLineColor(kBlack)
line.Draw("same")
gPad.RedrawAxis()
##################################################
# save
plotdir = "./plots/%s" % s[0]
if not os.path.exists(plotdir): makeDirs(plotdir)
can.SaveAs("%s/%s_s%s.pdf" % (plotdir, vn, s[0]))
can.SaveAs("%s/%s_s%s.png" % (plotdir, vn, s[0]))
fout.cd()
can.Clear()
##################################################
# clean
can.Close()
closeSamples(Lsamples)
def mkSBSigTrees():
# initialise
global paves
mp = parser()
opts,fout = main.main(mp,True)
fname = fout.GetName()
fout.Close()
os.remove(fname)
prefix = basepath+'/../mvd'
basetree = "flatTree_VBFPowheg125.root"
makeDirs('/'.join([prefix,"rootfiles"]))
makeDirs('/'.join([prefix,"plots"]))
######################################################################################################################################################
######################################################################################################################################################
# step 01: NOM/PRK selection
if opts.step==1:
fin = TFile.Open('/'.join([opts.globalpath,basetree]),"read")
tin = fin.Get("Hbb/events")
l1("Step 01: %s selection"%opts.sel)
fout = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep01_%s.root"%opts.sel)]),"recreate")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("Hbb")
#cut,label = write_cuts(opts.selection[0],opts.trigger[0],reftrig=[],jsoncuts=opts.jsoncuts,jsonsamp=opts.jsonsamp,sample="VBF125",weight=opts.weight,trigequal=trigTruth(True))
cut,label = write_cuts([],opts.trigger[0],reftrig=[],jsoncuts=opts.jsoncuts,jsonsamp=opts.jsonsamp,sample="VBF125",weight=opts.weight,trigequal=trigTruth(True))
l2("Cut %s: %s"%(opts.sel,cut))
tout = tin.CopyTree(cut)
fout.Write()
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step==2:
fin = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep01_%s.root"%opts.sel)]),"read")
tin = fin.Get("Hbb/events")
l1("Step 02: %s: eta/btag variable only slimming"%(opts.sel))
tin.SetBranchStatus('*',0)
for b in ['jetBtag','btagIdx','jetEta','etaIdx','partonId','partonMatchIdx','partonMatchDR','jetPt','jetPhi','jetMass','blikNOMIdx','blikVBFIdx','mqq','mbb','dEtaqq']:
tin.SetBranchStatus(b,1)
fout = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep02_%s.root"%(opts.sel))]),"recreate")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("Hbb")
tout = tin.CloneTree()
fout.Write(fout.GetName(),TH1.kOverwrite)
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step==3:
fin = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep02_%s.root"%(opts.sel))]),"read")
tin = fin.Get("Hbb/events")
nin = tin.GetEntriesFast()
l1("Step 03%s: %s: jets tree transformation"%(" (Alt)" if opts.alt else "",opts.sel))
fout = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep03%s_%s.root"%("Alt" if opts.alt else "",opts.sel))]),"recreate")
makeDirsRoot(fout,"Hbb")
gDirectory.cd("Hbb")
v_eta,v_btag,v_pt,v_phi,v_mass = zeros(1,dtype='float32'),zeros(1,dtype='float32'),zeros(1,dtype='float32'),zeros(1,dtype='float32'),zeros(1,dtype='float32')
v_etaIdx,v_btagIdx,v_pid,v_ptIdx = zeros(1,dtype='int32'),zeros(1,dtype='int32'),zeros(1,dtype='int32'),zeros(1,dtype='int32')
# new branches
tout = TTree("jets","jets")
tout.Branch("eta",v_eta,"eta/F")
tout.Branch("etaIdx",v_etaIdx,"etaIdx/I")
tout.Branch("btag",v_btag,"btag/F")
tout.Branch("btagIdx",v_btagIdx,"btagIdx/I")
tout.Branch("pid",v_pid,"pid/I")
tout.Branch("ptIdx",v_ptIdx,"ptIdx/I")
tout.Branch("pt",v_pt,"pt/F")
tout.Branch("phi",v_phi,"phi/F")
tout.Branch("mass",v_mass,"mass/F")
# loop over tree
tref = now()
for iEv,Ev in enumerate(tin):
if iEv%20000==0:
[m,s],p = testimate(tref,iEv,nin)
print "%6d/%-10d (est. %dm %ds, %.1f%%)"%(iEv,nin,m,s,p)
if opts.nentries>0 and iEv>opts.nentries: break
# loop over partons
for pj in range(len(Ev.partonMatchDR)):
if Ev.partonMatchDR[pj] > 0.25: continue
# if Ev.partonMatchIdx[pj] > len(Ev.jetPt): continue
ptIdx = Ev.partonMatchIdx[pj]
v_ptIdx[0] = Ev.partonMatchIdx[pj]
v_pid[0] = Ev.partonId[pj]
v_btag[0] = Ev.jetBtag[ptIdx]
v_pt[0] = Ev.jetPt[ptIdx]
v_eta[0] = Ev.jetEta[ptIdx]
v_phi[0] = Ev.jetPhi[ptIdx]
v_mass[0] = Ev.jetMass[ptIdx]
if opts.alt:
if (ptIdx in list(Ev.btagIdx)) and (ptIdx in list(Ev.etaIdx)):
v_btagIdx[0] = list(Ev.btagIdx).index(ptIdx)
v_etaIdx[0] = list(Ev.etaIdx).index(ptIdx)
else: continue
else:
if ptIdx < len(list(Ev.btagIdx)):
v_btagIdx[0] = Ev.btagIdx[ptIdx]
v_etaIdx[0] = Ev.etaIdx[ptIdx]
tout.Fill()
# save
fout.Write(fout.GetName(),TH1.kOverwrite)
######################################################################################################################################################
######################################################################################################################################################
if opts.step==4:
l1("Step 04%s: %s: blik training"%(" (Alt)" if opts.alt else "",opts.sel))
fin = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep03%s_%s.root"%("Alt" if opts.alt else "",opts.sel))]),"read")
tin = fin.Get("Hbb/jets")
fout = TFile.Open("rootfiles/bjetId_%s_MVA%s.root"%(opts.sel,"Alt" if opts.alt else ""),"recreate")
sigCut = TCut("abs(pid) == 5")
bkgCut = TCut("abs(pid) != 5")
presel = TCut("btagIdx<4 && etaIdx<4 && etaIdx>-1 && ptIdx<4 && btagIdx>-1 && ptIdx>-1")
Nin = tin.GetEntries()
N = 100000
l1("Input tree: %d events"%Nin)
l1("Using %d events"%N)
factory = TMVA.Factory("factory_%s%s_"%(opts.sel,"_Alt" if opts.alt else ""),fout,"!V:!Silent:Color:DrawProgressBar:Transformations=I;G:AnalysisType=Classification")
factory.SetInputTrees(tin,sigCut,bkgCut)
factory.AddVariable("btag" ,'F');
factory.AddVariable("eta" ,'F');
factory.AddVariable("btagIdx",'I');
factory.AddVariable("etaIdx" ,'I');
factory.PrepareTrainingAndTestTree(presel,"nTrain_Signal=%d:nTrain_Background=%d:nTest_Signal=%d:nTest_Background=%d"%(N,N,N,N))
factory.BookMethod(TMVA.Types.kLikelihood,"Likelihood");
factory.BookMethod(TMVA.Types.kBDT,"BDT_GRAD2","NTrees=600:nCuts=25:BoostType=Grad:Shrinkage=0.2");
factory.TrainAllMethods();
factory.TestAllMethods();
factory.EvaluateAllMethods();
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step==5:
l1("Step 05%s: %s: Sig/Bkg plots"%(" (Alt)" if opts.alt else "",opts.sel))
fin = TFile.Open(prefix+"/rootfiles/flatTree_VBFPowheg125_EvIntStep03%s_%s.root"%("Alt" if opts.alt else "",opts.sel),"read")
tin = fin.Get("Hbb/jets")
fout = TFile.Open(prefix+"/rootfiles/flatTree_VBFPowheg125_EvIntStep05%s_%s.root"%("Alt" if opts.alt else "",opts.sel),"recreate")
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C"%basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.02)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleSize(0.05,"XY")
gStyle.SetLabelSize(0.04,"XY")
gStyle.SetTitleOffset(1.35,"Y")
gStyle.SetGridColor(17)
#
fc = {"sig":kBlue-9,"bkg":kRed}
fs = {"sig":1001,"bkg":3004}
lc = {"sig":kBlue-7,"bkg":kRed}
Ax = ["#eta","#eta rank","CSV b-tag","CSV b-tag rank","(old) b-likelihood","(old) b-likelihood rank","b-likelihood","b-likelihood rank"]
Ay = ["N / (0.2)","N / (1)","N / (0.1)","N / (1)","N / (0.04)","N / (1)","N / (0.04)","N / (1)"]
AN = [50,4,110,4,50,4,50,4]
Ami = [-5,-0.5,-10,-0.5,-1,-0.5,-1,-0.5]
Ama = [5,3.5,1,3.5,1,3.5,1,3.5]
Av = ["jetEta","etaIdx","jetBtag","btagIdx","blikNOM","blikNOMIdx","myblikNOM","myblikNOMIdx"]
hs = {}
btagbinsinput = [-10,-9,-1,0]
for i in range(1,int(1./0.05)+1): btagbinsinput += [round(float(i)*0.05,2)]
btagbins = array('f',btagbinsinput)
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["eta","etaIdx","btag","btagIdx"]):
x,y,N,mi,ma = Ax[i2],Ay[i2],AN[i2],Ami[i2],Ama[i2]
if not a2=="btag": hs["%s_%s"%(a1,a2)] = eval('TH1F("h%s_%s","h%s_%s;%s;%s",%d,%f,%f)'%(a1,a2,a1,a2,x,y,N,mi,ma))
else: hs["%s_%s"%(a1,a2)] = TH1F("h%s_%s"%(a1,a2),"h%s_%s;%s;%s"%(a1,a2,x,y),len(btagbins)-1,btagbins)
hs["%s_%s"%(a1,a2)].SetFillColor(fc[a1])
hs["%s_%s"%(a1,a2)].SetFillStyle(fs[a1])
hs["%s_%s"%(a1,a2)].SetLineColor(lc[a1])
#
hs["sig_etaIdx"].GetXaxis().SetNdivisions(4)
hs["sig_btagIdx"].GetXaxis().SetNdivisions(4)
TGaxis.SetMaxDigits(4)
legs = [TLegend(1.-gStyle.GetPadRightMargin()-0.03-0.30,1.-gStyle.GetPadTopMargin()-0.03,1.-gStyle.GetPadRightMargin()-0.03,1.-gStyle.GetPadTopMargin()-0.03-0.055*3,"%s selection"%("Set A" if opts.sel=="NOM" else "Set B"))]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(4): legs += [deepcopy(legs[0])]
#
for var in ["eta","etaIdx","btag","btagIdx"]:
for typ in ["sig","bkg"]:
tin.Draw("%s>>h%s_%s"%(var,typ,var),"abs(pid)==5" if typ=="sig" else "abs(pid)!=5")
#
for h in hs.itervalues():
h.Scale(1./h.Integral())
h.GetYaxis().SetRangeUser(0.0 if not "Idx" in h.GetName() else 0.1,h.GetBinContent(h.GetMaximumBin())*1.40)
hs["sig_btag"] = btagTrafo(hs["sig_btag"],"sig",fc["sig"],fs["sig"],lc["sig"])
hs["bkg_btag"] = btagTrafo(hs["bkg_btag"],"bkg",fc["bkg"],fs["bkg"],lc["bkg"])
c = TCanvas("c","c",1800,1300)
c.Divide(2,2)
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["btag","btagIdx","eta","etaIdx"]):
c.cd(i2+1)
h = hs["%s_%s"%(a1,a2)]
h.Draw("" if a1=="sig" else "same")
gPad.SetGrid(1,1)
legs[i2].AddEntry(h,"signal" if a1=="sig" else "background","F")
if a1=="bkg": legs[i2].Draw()
if a2=="btag":
gPad.SetLogy(1)
epave("-1",-0.08,0.000306)
epave("-10",-0.135,0.000306)
#
makeDirs(prefix+"/plots")
c.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesIn%s_%s.pdf"%("Alt" if opts.alt else "",opts.sel))
fout.Write(fout.GetName(),TH1.kOverwrite)
fin.Close()
fout.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step==6:
l1("Step 06%s: %s: weights filling & output plots."%(" (Alt)" if opts.alt else "",opts.sel))
gROOT.SetBatch(1)
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C"%basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleOffset(1.35,"Y")
gStyle.SetPalette(1)
gStyle.SetGridColor(17)
TGaxis.SetMaxDigits(4)
gStyle.SetTitleSize(0.05,"XYZ")
gStyle.SetLabelSize(0.04,"XYZ")
gStyle.SetTitleOffset(1.35,"Y")
gStyle.SetGridColor(17)
#
fc = {"sig":kBlue-9,"bkg":kRed}
fs = {"sig":1001,"bkg":3004}
lc = {"sig":kBlue-7,"bkg":kRed}
Ax = ["#eta","#eta rank","CSV b-tag","CSV b-tag rank","(old) b-likelihood","(old) b-likelihood rank","b-likelihood","b-likelihood rank","|#eta|","bbtag","bblik"]
Ay = ["N / (0.2)","N / (1)","N / (0.1)","N / (1)","N / (0.08)","N / (1)","N / (0.08)","N / (1)","N / (0.1)","N / (0.02)","N / (0.01)"]
AN = [50,4,110,4,25,4,25,4,100,550,200]
Ami = [-5,-0.5,-10,-0.5,-1,-0.5,-1,-0.5,0,-10,-1]
Ama = [5,3.5,1,3.5,1,3.5,1,3.5,5,1,1,1]
Av = ["jetEta","etaIdx","jetBtag","btagIdx","blik%s"%("NOM" if opts.sel=="NOM" else "VBF"),"blik%sIdx"%("NOM" if opts.sel=="NOM" else "VBF"),"blik","blikIdx","abseta","jetBtag","blik"]
hs = {}
btagbinsinput = [-10,-9,-1,0]
for i in range(1,int(1./0.05)+1): btagbinsinput += [round(float(i)*0.05,2)]
btagbins = array('f',btagbinsinput)
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["eta","etaIdx","btag","btagIdx","blik","blikIdx","blik2","blik2Idx","abseta","bbtag","bblik"]):
x,y,N,mi,ma = Ax[i2],Ay[i2],AN[i2],Ami[i2],Ama[i2]
if not a2=="btag": hs["%s_%s"%(a1,a2)] = eval('TH1F("h%s_%s","h%s_%s;%s;%s",%d,%f,%f)'%(a1,a2,a1,a2,x,y,N,mi,ma))
else: hs["%s_%s"%(a1,a2)] = TH1F("h%s_%s"%(a1,a2),"h%s_%s;%s;%s"%(a1,a2,x,y),len(btagbins)-1,btagbins)
hs["%s_%s"%(a1,a2)].SetFillColor(fc[a1])
hs["%s_%s"%(a1,a2)].SetFillStyle(fs[a1])
hs["%s_%s"%(a1,a2)].SetLineColor(lc[a1])
#
if not opts.replot:
fglobal = TFile.Open('/'.join([prefix,"rootfiles",basetree.replace(".root","_EvIntStep02_%s.root"%opts.sel)]),"read")
tglobal = fglobal.Get("Hbb/events")
eta,etaIdx,btag,btagIdx = zeros(1,'float32'),zeros(1,'float32'),zeros(1,'float32'),zeros(1,'float32')
pid = ROOT.vector('int')()
reader = TMVA.Reader()
if opts.alttag=="" or not ("Kostas" in opts.alttag or "CERN" in opts.alttag):
reader.AddVariable("btag",btag)
reader.AddVariable("eta",eta)
reader.AddVariable("btagIdx",btagIdx)
reader.AddVariable("etaIdx",etaIdx)
reader.BookMVA(opts.tmva,"weights/factory_%s%s__BDT_GRAD2.weights.xml"%(opts.sel,"_Alt" if opts.alt else ""))
elif "Kostas" in opts.alttag:
reader.AddVariable("btagIdx",btagIdx)
reader.AddVariable("etaIdx",etaIdx)
reader.AddVariable("btag",btag)
reader.AddVariable("eta",eta)
reader.BookMVA(opts.tmva,"kostas/weights/factory_%s__BDT_GRAD2.weights.xml"%opts.sel)
elif "CERN" in opts.alttag:
reader.AddVariable("btagIdx",btagIdx)
reader.AddVariable("etaIdx",etaIdx)
reader.AddVariable("btag",btag)
reader.AddVariable("eta",eta)
reader.BookMVA(opts.tmva,"tmpcern/factory_BCanditate_%s_BDT_GRAD.weights.xml"%opts.sel)
# reader.BookMVA(opts.tmva,"weights/kostas.NOM.xml")
#
blik = ROOT.vector('float')()
blikIdx = ROOT.vector('int')()
blikmqq = zeros(1,'float32')
blikmbb = zeros(1,'float32')
blikdetaqq = zeros(1,'float32')
#
fmvd = TFile.Open(prefix+"/rootfiles/flatTree_VBFPowheg125_EvIntStep04%s_%s.root"%("Alt" if opts.alt else "",opts.sel),"recreate")
makeDirsRoot(fmvd,"Hbb")
gDirectory.cd("Hbb")
tmvd = tglobal.CloneTree(0)
#
tmvd.Branch("blik",blik)
tmvd.Branch("blikIdx",blikIdx)
tmvd.Branch("blikmqq",blikmqq,"blikmqq/F")
tmvd.Branch("blikmbb",blikmbb,"blikmbb/F")
tmvd.Branch("blikdetaqq",blikdetaqq,"blikdetaqq/F")
tmvd.Branch("pid",pid)
#
nentries = tglobal.GetEntriesFast()
tref = now()
for iEv,Ev in enumerate(tglobal):
blik.resize(4,0)
blikIdx.resize(4,0)
pid.resize(4,0)
#
if opts.nentries>0:
if iEv>opts.nentries: break
if iEv%5000==0:
[m,s],p = testimate(tref,iEv,nentries)
print "%8d/%-10d (est. %dm %ds, %.1f%%)"%(iEv,nentries,m,s,p)
#
for ijet in range(4):
eta[0] = Ev.jetEta[ijet]
btag[0] = Ev.jetBtag[ijet]
if opts.alt:
etaIdx[0] = list(Ev.etaIdx).index(ijet)
btagIdx[0] = list(Ev.btagIdx).index(ijet)
else:
etaIdx[0] = Ev.etaIdx[ijet]
btagIdx[0] = Ev.btagIdx[ijet]
blik[ijet] = float(reader.EvaluateMVA(opts.tmva))
#
blikIdxPair = sorted([[ijet,blik[ijet]] for ijet in range(4)],key=lambda (x,y):y,reverse=True)
#
for ijet in range(4): blikIdx[ijet] = blikIdxPair[ijet][0]
#
for pj in range(len(Ev.partonMatchDR)):
if Ev.partonMatchDR[pj] > 0.25: continue
ptIdx = Ev.partonMatchIdx[pj]
if ptIdx >= len(Ev.btagIdx): continue
pid[ptIdx] = Ev.partonId[pj]
# for ijet in range(4):
# pidVals = sorted([(x,Ev.partonMatchDR[x]) for x in range(len(Ev.partonMatchIdx)) if (Ev.partonMatchIdx[x]==ijet and Ev.partonMatchDR[x]<0.25)],key=lambda (x,y):(y))
# if len(pidVals)<1: pid[ijet] =-999
# else: pid[ijet] = Ev.partonId[pidVals[0][0]]
# if pid[ijet]!=-999:
for i2,a2 in enumerate(["eta","etaIdx","btag","btagIdx","blik","blikIdx","blik2","blik2Idx","abseta","bbtag","bblik"]):
if a2=="blik": continue
h = hs["%s_%s"%("sig" if abs(pid[ptIdx])==5 else "bkg",a2)]
if not Av[i2] in ["blik","blikIdx","abseta"]:
v = eval("Ev.%s[%d]"%(Av[i2],ptIdx)) if not "Idx" in a2 else eval("list(Ev.%s).index(%d)"%(Av[i2],ptIdx))
elif Av[i2] == "blik": v = blik[ptIdx]
elif Av[i2] == "blikIdx": v = list(blikIdx).index(ptIdx)
elif Av[i2] == "abseta": v = abs(Ev.jetEta[ptIdx])
elif Av[i2] == "bbtag": v = Ev.jetBtag[ptIdx]
elif Av[i2] == "bblik": v = blik[ptIdx]
h.Fill(v)
#
# v = [TLorentzVector(),TLorentzVector(),TLorentzVector(),TLorentzVector()]
# for j in range(4):
# k = blikIdx[j]
# v[j].SetPtEtaPhiM(Ev.jetPt[k],Ev.jetEta[k],Ev.jetPhi[k],Ev.jetMass[k])
v = []
for jid in range(4):
v += [TLorentzVector()]
v[-1].SetPtEtaPhiM(Ev.jetPt[jid],Ev.jetEta[jid],Ev.jetPhi[jid],Ev.jetMass[jid])
blikmqq[0] = (v[blikIdx[2]]+v[blikIdx[3]]).M()
blikmbb[0] = (v[blikIdx[0]]+v[blikIdx[1]]).M()
blikdetaqq[0] = abs(Ev.jetEta[int(blikIdx[2])]-Ev.jetEta[int(blikIdx[3])])
tmvd.Fill()
else:
fmvd = TFile.Open(prefix+"/rootfiles/flatTree_VBFPowheg125_EvIntStep04%s_%s.root"%("Alt" if opts.alt else "",opts.sel),"update")
gDirectory.cd("Hbb")
tmvd = fmvd.Get("Hbb/events")
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["eta","etaIdx","btag","btagIdx","blik","blikIdx","blik2","blik2Idx"]):
eval('h%s_%s = fmvd.Get("Hbb/h%s_%s")'%(a1,a2,a1,a2))
#
c = TCanvas("c","c",1800,1500)
c.Divide(4,4)
Bv = ["blikNOM" if opts.sel=="NOM" else "blikVBF","blikNOMIdx" if opts.sel=="NOM" else "blikVBFIdx","blik","blikIdx","mqq[0]","mqq[%d]"%(1 if opts.sel=="NOM" else 2),"blikmqq","NONE","dEtaqq[0]","dEtaqq[%d]"%(1 if opts.sel=="NOM" else 2),"blikdetaqq","NONE","mbb[0]","mbb[%d]"%(1 if opts.sel=="NOM" else 2),"blikmbb","NONE"]
Bx = ["(old) b-likelihood","(old) b-likelihood rank","b-likelihood","b-likelihood rank","(CSV) m_{qq'} (GeV)","(old) m_{qq'} (GeV)","(new) m_{qq'} (GeV)","","(CSV) #Delta#eta_{qq'}","(old) #Delta#eta_{qq'}","(new) #Delta#eta_{qq'}","","(CSV) m_{b#bar{b}} (GeV)","(old) m_{b#bar{b}} (GeV)","(new) m_{b#bar{b}} (GeV)",""]
By = ["N / (0.08)","N / (1)","N / (0.08)","N / (1)","N / (20 GeV)","N / (20 GeV)","N / (20 GeV)","","N / (0.1)","N / (0.1)","N / (0.1)","","N / (10 GeV)","N / (10 GeV)","N / (10 GeV)",""]
BN = [25,4,25,4,100,100,100,0,50,50,50,0,30,30,30,0]
Bmi = [-1,-0.5,-1,-0.5,0,0,0,0,0,0,0,0,0,0,0,0]
Bma = [1,3.5,1,3.5,2000,2000,2000,0,5,5,5,0,300,300,300,0]
Bt = ["(existing)","(existing)","(new)","(new)","(existing)","(existing)","(new)","","(existing)","(existing)","(new)","","(existing)","(existing)","(new)",""]
for iv,v in enumerate(Bv):
if v == "blikNOM" or v == "blikVBF": continue
if v == "NONE": continue
c.cd(iv+1)
gPad.SetGrid(1,1)
tmvd.Draw("%s>>h%d(%d,%f,%f)"%(v,iv+1,BN[iv],Bmi[iv],Bma[iv]))
eval('h%d.GetXaxis().SetTitle("%s")'%(iv+1,Bx[iv]))
eval('h%d.GetYaxis().SetTitle("%s")'%(iv+1,By[iv]))
trpave(Bt[iv])
makeDirs(prefix+"/plots")
c.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesOut%s%s-1_%s.pdf"%("Alt" if opts.alt else "",opts.alttag if not opts.alttag=="" else "",opts.sel))
c.Close()
ci = TCanvas("ci","ci",900,750)
# c.Divide(2,1)
Bv = ["blikmbb:mbb[0]","mbb[%d]:mbb[0]"%(1 if opts.sel=="NOM" else 2)]
Bx = ["CSV b-tag m_{b#bar{b}} (GeV)","CSV b-tag m_{b#bar{b}} (GeV)"]
By = ["b-likelihood m_{b#bar{b}} (GeV)","b-likelihood m_{b#bar{b}} (GeV)"]
BN = [[140,140],[140,140]]
Bmi = [[0,0],[0,0]]
Bma = [[700,700],[700,700]]
Bt = ["(new)","(existing)"]
for iv,v in enumerate(Bv):
if v == "NONE": continue
# c.cd(iv+1)
ci.cd()
tmvd.Draw("%s>>h%d(%d,%f,%f,%d,%f,%f)"%(v,iv+1+12,BN[iv][0],Bmi[iv][0],Bma[iv][0],BN[iv][1],Bmi[iv][1],Bma[iv][1]),"","colz")
gPad.SetRightMargin(0.14)
gPad.SetTopMargin(0.06)
gPad.SetBottomMargin(0.14)
eval('ROOT.h%d.GetXaxis().SetTitle("%s")'%(iv+1+12,Bx[iv]))
eval('ROOT.h%d.GetYaxis().SetTitle("%s")'%(iv+1+12,By[iv]))
eval('ROOT.h%d.GetXaxis().SetTitleOffset(%.2f)'%(iv+1+12,1.1))
#trpave(Bt[iv])
tlpave("Set %s selection"%("A" if opts.sel=="NOM" else "B"),0.85,1)
eval('ROOT.h%d.GetZaxis().SetRangeUser(1,4000)'%(iv+1+12))
gPad.SetLogz(1)
ci.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesOut%s%s-2%s_%s.pdf"%("Alt" if opts.alt else "",opts.alttag if not opts.alttag=="" else "","-new" if iv==0 else "-existing",opts.sel))
#ci.Close()
cb = TCanvas("cb","cb",1800,750)
cb.Divide(2,1)
c = TCanvas("c","c",2700,1950)
c.Divide(3,3)
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["eta","etaIdx","btag","btagIdx","blik","blikIdx","blik2","blik2Idx","abseta","bbtag","bblik"]):
h = hs["%s_%s"%(a1,a2)]
if "Idx" in a2: h.GetXaxis().SetNdivisions(4)
if not h.Integral()==0: h.Scale(1./h.Integral())
h.GetYaxis().SetRangeUser(0.001 if a2 in ["btag","blik","blik2","bbtag","bblik"] else 0.0,h.GetBinContent(h.GetMaximumBin())*(75 if a2 in ["btag","blik","blik2","bbtag","bblik"] else 1.4))
legs = [TLegend(1.-gStyle.GetPadRightMargin()-0.03-0.30,1.-gStyle.GetPadTopMargin()-0.03,1.-gStyle.GetPadRightMargin()-0.03,1.-gStyle.GetPadTopMargin()-0.03-0.055*3,"%s selection"%("Set A" if opts.sel=="NOM" else "Set B"))]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(8): legs += [deepcopy(legs[0])]
hsigbtagnew = btagTrafo(hs["sig_btag"],"sig",fc["sig"],fs["sig"],lc["sig"])
hbkgbtagnew = btagTrafo(hs["bkg_btag"],"bkg",fc["bkg"],fs["bkg"],lc["bkg"])
for i2,a2 in enumerate(["blik2","blik2Idx","blikIdx","btag","btagIdx","NONE","eta","etaIdx","NONE"]):
if a2=="blik2": cb.cd(1)
elif a2=="blik2Idx": cb.cd(2)
else: c.cd(i2+1)
for a1 in ["sig","bkg"]:
gPad.SetRightMargin(0.02)
gPad.SetBottomMargin(0.12)
if a2=="NONE": continue
h = hs["%s_%s"%(a1,a2)]
if a2=="btag" and a1=="sig": h = hsigbtagnew
elif a2=="btag" and a1=="bkg": h = hbkgbtagnew
gPad.SetGrid(1,1)
if a2 in ["btag","blik","blik2"]: gPad.SetLogy(1)
else: gPad.SetLogy(0)
h.Draw("" if a1=="sig" else "same")
legs[i2].AddEntry(h,"signal" if a1=="sig" else "background","F")
if a1=="bkg": legs[i2].Draw()
h.GetXaxis().SetTitleSize(0.05)
h.GetYaxis().SetTitleSize(0.05)
h.GetXaxis().SetTitleOffset(1.1)
h.GetYaxis().SetTitleOffset(1.35)
h.GetXaxis().SetLabelSize(0.04)
h.GetYaxis().SetLabelSize(0.04)
if a2=="btag":
epave("-1",-0.08,0.000306)
epave("-10",-0.13,0.000306)
gPad.Update()
if "blik2" in a2 and a1=="bkg": cb.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesOut%s%s-3a_%s.pdf"%("Alt" if opts.alt else "",opts.alttag if not opts.alttag=="" else "",opts.sel))
c.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesOut%s%s-3_%s.pdf"%("Alt" if opts.alt else "",opts.alttag if not opts.alttag=="" else "",opts.sel))
c = TCanvas("c","c",900,750)
c.cd()
legs = [TLegend(gStyle.GetPadLeftMargin()+0.05,gStyle.GetPadBottomMargin()+0.05,gStyle.GetPadLeftMargin()+0.3,gStyle.GetPadBottomMargin()+0.05+0.050*4,"%s selection"%("Set A" if opts.sel=="NOM" else "Set B"))]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.045)
legs[0].SetFillStyle(0)
legs[0].SetBorderSize(0)
gs = {}
for i2,a2 in enumerate(["bblik","bbtag","abseta"]):
hsig = hs["sig_%s"%a2]
hbkg = hs["bkg_%s"%a2]
g = makeGraph(hsig,hbkg,"right" if not a2=="abseta" else "left")
g.Write()
gs[a2] = g
legs[0].AddEntry(g,"b-likelihood" if "blik" in a2 else ("CSV b-tag" if a2=="bbtag" else "|#eta|"),"L")
g.Draw("A,L" if i2==0 else "same,L")
legs[0].Draw()
legs[0].SetY2(legs[0].GetY1()+legs[0].GetNRows()*0.050+0.05)
gPad.Update()
c.SaveAs(prefix+"/plots/EvIntDiscriminant_variablesOut%s%s-4_%s.pdf"%("Alt" if opts.alt else "",opts.alttag if not opts.alttag=="" else "",opts.sel))
if opts.replot:
for i in range(20):
h = eval("ROOT.h%d"%(i))
if h: h.Write(h.GetName(),TH1.kOverwrite)
for a1 in ["sig","bkg"]:
for i2,a2 in enumerate(["blik2","blik2Idx","blikIdx","btag","btagIdx","NONE","eta","etaIdx","NONE"]):
if a2=="NONE": continue
h = hs["%s_%s"%(a1,a2)]
if h: h.Write(h.GetName(),TH1.kOverwrite)
for g in gs.itervalues():
if g: g.Write(g.GetName(),TH1.kOverwrite)
else:
fmvd.Write()
#
fmvd.Close()
######################################################################################################################################################
######################################################################################################################################################
if opts.step==7:
l1("Step 07%s: %s: more plots."%(" (Alt)" if opts.alt else "",opts.sel))
gROOT.SetBatch(1)
gStyle.SetOptStat(0)
gStyle.SetLineScalePS(2)
gROOT.ProcessLineSync(".x %s/styleCMSTDR.C"%basepath)
gStyle.SetPadRightMargin(0.02)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.12)
gROOT.SetBatch(1)
gStyle.SetTitleOffset(1.35,"Y")
gStyle.SetTitleSize(0.05,"XYZ")
gStyle.SetLabelSize(0.04,"XYZ")
gStyle.SetPalette(1)
gStyle.SetGridColor(17)
TGaxis.SetMaxDigits(4)
fin = TFile.Open("rootfiles/bjetId_%s_MVA%s.root"%(opts.sel,"Alt" if opts.alt else ""),"read")
tin = fin.Get("TestTree")
fout = TFile.Open(prefix+"/rootfiles/flatTree_VBFPowheg125_EvIntStep07%s_%s.root"%("Alt" if opts.alt else "",opts.sel),"recreate")
NTrue = float(tin.GetEntries("classID==0"))
NFake = float(tin.GetEntries("classID==1"))
V = ["btag","btag","abs(eta)","abs(eta)","BDT_GRAD2","BDT_GRAD2"]
Av = ["btagTrue","btagFake","etaTrue","etaFake","blikTrue","blikFake"]
Ax = ["CSV b-tag","CSV b-tag","|#eta|","|#eta|","b-likelihood","b-likelihood"]
Ay = ["N / (0.05)","N / (0.05)","N / (0.2)","N / (0.2)","N / (0.08)","N / (0.08)"]
Ami = [0,0,0,0,-1,-1]
Ama = [1,1,5,5,1,1]
AN = [20,20,25,25,25,25]
hs = {}
for a in range(len(Av)):
hs["%s"%Av[a]] = TH1F("h%s"%Av[a],"h%s;%s;%s"%(Av[a],Ax[a],Ay[a]),AN[a],Ami[a],Ama[a])
h = hs["%s"%Av[a]]
if "True" in Av[a]:
h.SetLineColor(kBlue)
h.SetFillColor(kBlue-9)
h.SetFillStyle(1001)
elif "Fake" in Av[a]:
h.SetLineColor(kRed)
h.SetFillColor(kRed)
h.SetFillStyle(3004)
for v in range(len(V)):
tin.Draw("%s>>h%s"%(V[v],Av[v]),"classID==0" if "True" in Av[v] else "classID==1")
if "True" in Av[v]: hs[Av[v]].Scale(1./NTrue)
elif "Fake" in Av[v]: hs[Av[v]].Scale(1./NFake)
c = TCanvas("c","c",900,1950)
c.Divide(1,3)
legs = [TLegend(1.-gStyle.GetPadRightMargin()-0.03-0.30,1.-gStyle.GetPadTopMargin()-0.03,1.-gStyle.GetPadRightMargin()-0.03,1.-gStyle.GetPadTopMargin()-0.03-0.055*3,"%s selection"%("Set A" if opts.sel=="NOM" else "Set B"))]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.05)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(20): legs += [deepcopy(legs[0])]
for a in range(len(Av)):
c.cd(divmod(a+2,2)[0])
h = hs["%s"%Av[a]]
h.Draw("" if "True" in Av[a] else "same")
legs[divmod(a+2,2)[0]].AddEntry(h,"signal" if "True" in Av[a] else "background","F")
if "Fake" in Av[a]: legs[divmod(a+2,2)[0]].Draw()
if "btag" in Av[a] or "blik" in Av[a]:
if "True" in Av[a]: h.GetYaxis().SetRangeUser(0.001,h.GetBinContent(h.GetMaximumBin())*75)
gPad.SetLogy(1)
else:
if "True" in Av[a]: h.GetYaxis().SetRangeUser(0.0,h.GetBinContent(h.GetMaximumBin())*1.4)
gPad.SetLogy(0)
c.SaveAs("plots/performance%s-1_%s.pdf"%("Alt" if opts.alt else "",opts.sel))
c.Close()
xtrue = [0.]*1000
yfake = [0.]*1000
c = TCanvas("c","c",900,750)
c.cd()
legs = [TLegend(gStyle.GetPadLeftMargin()+0.05,gStyle.GetPadBottomMargin()+0.05,gStyle.GetPadLeftMargin()+0.3,gStyle.GetPadBottomMargin()+0.05+0.050*4,"%s selection"%("Set A" if opts.sel=="NOM" else "Set B"))]
legs[0].SetTextFont(42)
legs[0].SetTextSize(0.045)
legs[0].SetFillStyle(-1)
legs[0].SetBorderSize(0)
for i in range(20): legs += [deepcopy(legs[0])]
gs = {}
for a in range(len(Av)):
if "True" in Av[a]:
xtrue = [0.]*1000
yfake = [0.]*1000
for i in range(hs[Av[a]].GetNbinsX()):
xtrue[i] = hs[Av[a]].Integral(i,hs[Av[a]].GetNbinsX())
if "eta" in Av[a]: xtrue[i] = 1. - xtrue[i]
elif "Fake" in Av[a]:
for i in range(hs[Av[a]].GetNbinsX()):
yfake[i] = 1. - hs[Av[a]].Integral(i,hs[Av[a]].GetNbinsX())
if "eta" in Av[a]: yfake[i] = -yfake[i] + 1.
gs[Av[a][0:-4]] = TGraph(hs[Av[a]].GetNbinsX(),array('f',xtrue[0:hs[Av[a]].GetNbinsX()]),array('f',yfake[0:hs[Av[a]].GetNbinsX()]))
g = gs[Av[a][0:-4]]
g.SetLineColor(kRed if "btag" in Av[a] else (kGreen+2 if "eta" in Av[a] else kBlue))
gPad.SetGrid(1,1)
gs["btag"].GetXaxis().SetLimits(0.7,1.05)
gs["btag"].GetYaxis().SetRangeUser(0.0,1.1)
gs["btag"].GetXaxis().SetTitle("Efficiency of matched b-jets")
gs["btag"].GetYaxis().SetTitle("Rejection of matched non b-jets")
gs["btag"].GetXaxis().SetNdivisions(504)
gs["btag"].Draw("AL")
gs["eta"].Draw("sameL")
gs["blik"].Draw("sameL")
legs[-1].AddEntry(gs["btag"],"CSV b-tag","L")
legs[-1].AddEntry(gs["eta"],"|#eta|","L")
legs[-1].AddEntry(gs["blik"],"b-likelihood","L")
legs[-1].Draw()
c.SaveAs("plots/performance%s-2_%s.pdf"%("Alt" if opts.alt else "",opts.sel))
c.Close()
c1s = fin.Get("CorrelationMatrixS")
c1b = fin.Get("CorrelationMatrixB")
gStyle.SetGridColor(kBlack)
c = TCanvas("c","c",900*2,850*1)
c.Divide(2,1)
c.cd(1)
gPad.SetGrid(1,1)
gPad.SetTopMargin(0.14)
gPad.SetRightMargin(0.13)
c1s.SetMarkerColor(kBlack)
c1s.Draw("colz,text")
epavetext(["Correlation matrix (signal)","%s selection"%("Set A" if opts.sel=="NOM" else "Set B")],0.03,0.88,0.5,0.97)
epavetext(["Linear correlation coefficients in %"],0.52,0.85,0.99,0.89,0.025,0)
gPad.Update()
gPad.RedrawAxis()
c.cd(2)
gPad.SetGrid(1,1)
gPad.SetTopMargin(0.14)
gPad.SetRightMargin(0.13)
c1b.SetMarkerColor(kBlack)
c1b.Draw("colz,text")
epavetext(["Correlation matrix (background)","%s selection"%("Set A" if opts.sel=="NOM" else "Set B")],0.03,0.88,0.5,0.97)
epavetext(["Linear correlation coefficients in %"],0.52,0.85,0.99,0.89,0.025,0)
gPad.Update()
gPad.RedrawAxis()
c.SaveAs("plots/performance%s-3_%s.pdf"%("Alt" if opts.alt else "",opts.sel))
c.Close()
gStyle.SetGridColor(17)
fout.Write(fout.GetName(),TH1.kOverwrite)
fin.Close()
fout.Close()
def mkUncJEx():
##################################################
# initialising
#print gSystem.Load("../fitbias/fitTF1")
# gSystem.AddIncludePath("-I/opt/Software/include")
# gROOT.ProcessLine(".L ../fitbias/fitTF1.C++")
opts,fout,variables = main.main(parser(),False,True,False)
gDirectory.cd("%s:/"%fout.GetName())
jsoninfo = json.loads(filecontent(opts.jsoninfo))
jsonsamp = json.loads(filecontent(opts.jsonsamp))
jsonvars = json.loads(filecontent(opts.jsonvars))
jsoncuts = json.loads(filecontent(opts.jsoncuts))
global SEL
global TRG
global DTG
global REF
global CUT
global LAB
global colours
global offset
catbounds = {}
for tag in opts.tag: catbounds[tag] = array('f',opts.categoryboundaries[0]) if tag=="NOM" else array('f',opts.categoryboundaries[1])
if (not len(opts.selection) == len(opts.trigger)) or (not len(opts.selection) == len(opts.tag)): sys.exit("Selection/trigger/tag options are broken. Exiting.")
for i in range(len(opts.selection)):
s = opts.selection[i]
t = opts.trigger[i]
d = opts.datatrigger[i] if opts.datatrigger and len(opts.datatrigger)>1 else opts.datatrigger[0] if opts.datatrigger else t
r = opts.reftrig[i] if opts.reftrig and len(opts.reftrig)>1 else opts.reftrig[0] if opts.reftrig else 'None'
w = opts.weight[1] if opts.weight else "???"
tag = opts.tag[i]
SEL[tag] = s
TRG[tag] = t
DTG[tag] = d
REF[tag] = r
WGT[tag] = w
CUT[tag],LAB[tag] = write_cuts(s,t,reftrig=["None"],sample="VBF125",jsonsamp=opts.jsonsamp,jsoncuts=opts.jsoncuts,weight=opts.weight,trigequal='1')
##################################################
# some ROOT settings
gStyle.SetOptStat(0)
gROOT.SetBatch(1)
TH1.SetDefaultSumw2(1)
ROOT.gErrorIgnoreLevel = kWarning
gROOT.ProcessLine("TH1::SetDefaultSumw2(1);")
gStyle.SetPadTopMargin(0.02)
gStyle.SetPadBottomMargin(0.23)
gStyle.SetPadLeftMargin(0.11)
gStyle.SetLabelFont(43,"XYZ")
gStyle.SetLabelSize(25,"XYZ")
gStyle.SetTitleFont(43,"XYZ")
gStyle.SetTitleSize(30,"XYZ")
gStyle.SetTitleOffset(3.0,"X")
gStyle.SetTitleOffset(1.6,"Y")
gStyle.SetLabelOffset(0.015,"X")
gStyle.SetTitleColor(kBlack,"XYZ")#kBlue+2
gStyle.SetLabelColor(kBlack,"XYZ")
gStyle.SetTickLength(0.02)
##################################################
# reading sample properties
friends = ["HbbJERUp","HbbJERCl","HbbJESDn","HbbJESUp"]#HbbJERDn,#"HbbJESUp","HbbJESDn",
sampleproperties = {}
for s in opts.sample:
sampleproperties[s] = {}
sprops = sampleproperties[s]
# load sample properties
sprops['tag'] = s
sprops['group'] = jsoninfo['groups'][s]
sprops['file'] = [k for (k,v) in jsonsamp['files'].iteritems() if v['tag']==s][0]
sprops['scale'] = jsonsamp['files'][sprops['file']]['scale']
sprops['colour'] = jsonsamp['files'][sprops['file']]['colour']
sprops['tfile'] = TFile(opts.globalpath+'/'+sprops['file'],"read")
sprops['ttree'] = {}
for f in ["%s"%x for x in ['Hbb']+friends]:
if sprops['tfile'].Get("%s/events"%f): sprops['ttree'][f] = sprops['tfile'].Get("%s/events"%f)
else: sprops['ttree'][f] = None
sprops['th1'] = {}
sprops['tf1'] = {}
for tag in opts.tag:
for incat,ncat in enumerate(["%s"%x for x in ['Hbb']+friends]):
for inh,nh in enumerate(opts.variable):
key = (tag,ncat,nh)
sprops[key] = {'th1':None,'tf1':{'ful':None,'bkg':None,'params':None}}
if incat==0:
sprops[(tag,'JES',nh)] = {'tca':None}
sprops[(tag,'JER',nh)] = {'tca':None}
if catveto(tag,nh): continue
if 'jetUnsPt' in nh:
variables[nh]['xmin'] = '-0.4'
variables[nh]['xmax'] = '0.4'
variables[nh]['nbins_x'] = '41'
v = variables[nh]['root']
n = variables[nh]['var']
xmin = float(variables[nh]['xmin'])
xmax = float(variables[nh]['xmax'])
bins = int(variables[nh]['nbins_x'])
tx = variables[nh]['title_x']
ty = variables[nh]['title_y']
f1,f2,f3,hname = gethname(WGT[tag],variables[nh],sprops['group'],sprops['tag'],SEL[tag],TRG[tag],DTG[tag],REF[tag])
hname = hname.replace('hNum','h%s'%ncat)
if "mva" in v: sprops[key]['th1'] = TH1F(hname,"%s;%s;%s"%(hname,tx,ty),len(catbounds[tag])-1,catbounds[tag])
else: sprops[key]['th1'] = TH1F(hname,"%s;%s;%s"%(hname,tx,ty),bins,xmin,xmax)
sprops[key]['th1'].Sumw2()
if incat==0:
sprops[(tag,'JES',nh)]['tca'] = TCanvas(hname.replace('h%s'%ncat,'cJES'),hname.replace('h%s'%ncat,'cJES'),1200,1200)
sprops[(tag,'JER',nh)]['tca'] = TCanvas(hname.replace('h%s'%ncat,'cJER'),hname.replace('h%s'%ncat,'cJER'),1200,1200)
# summarize load block
l1("Loaded properties for:")
print "%s%12s | %12s | %8s | %15s | %40s | %15s | %15s | %55s |%s"%(blue,"tag","group","colour","scale","file","tree name","object type","alternatives",plain)
print "-"*(15*2 + 11 + 18 + 43 + 36 + 58 - 1)
for sp in sampleproperties.itervalues():
print "%12s | %12s | %8s | %15s | %40s | %15s | %15s | %55s |"%( \
sp["tag"],sp["group"],sp["colour"],sp["scale"],sp["file"], \
sp["ttree"]["Hbb"].GetName() if not sp["ttree"]["Hbb"]==None else "%s%15s%s"%(Red,"None",plain), \
sp["ttree"]["Hbb"].IsA().GetName() if not sp["ttree"]["Hbb"]==None else "%s%15s%s"%(Red,"None",plain), \
", ".join([x for x in sprops["ttree"].keys()]) if len(sprops["ttree"].keys())>0 else "%s%30s%s"%(Red,"None",plain) \
)
# summarize selections & triggers:
l1("Running these selections:")
for tag in opts.tag:
print "%s%s%s: %s\n\t%s%s%s"%(Black,tag,plain,LAB[tag],grey,CUT[tag],plain)
##################################################
# loop
makeDirs("plots/uncertainties")
f0 = "histos"
for isp,sp in enumerate(sampleproperties.itervalues()):
# start
stag = sp['tag']
l1("Working with sample: %s"%stag)
sp['tfile'].cd()
tarray = []
for tag in opts.tag:
for incat,ncat in enumerate(["%s"%x for x in ["Hbb"]+friends]):
l2("Category %s (%s)"%(ncat,tag))
tree = sp['ttree'][ncat]
treedraw = tree.Draw
for inh,(nhf,nhr,nh) in enumerate([(variables[x],variables[x]['root'],variables[x]['var']) for x in opts.variable]):
if 'jetUnsPt' in nh and 'JES' in ncat: continue
f1,f2,f3,hname = gethname(WGT[tag],nhf,sp['group'],sp['tag'],SEL[tag],TRG[tag],DTG[tag],REF[tag])
hname = hname.replace('hNum','h%s'%ncat)
makeDirs("plots/uncertainties/%s%s"%(f1,'' if not opts.noleg else '_noleg'))
makeDirsRoot(fout,'%s/%s/%s/%s'%(f0,f1,f2,f3))
sp['tfile'].cd()
if catveto(tag,nh): continue
# tstart = time()
# if (isp==0 and incat==len(["%s"%x for x in ["Hbb"]+friends])-1 and inh==len(variables)-1): average = tarray[-1]
# l3("%-40s %-40s"%("Variable %s"%nh,"(time expected %.fs + %d modules)"%(tarray[-1]*((5-inh)+(4-incat)*5) if len(tarray)>0 else -999,len(sampleproperties)-isp-1)))
l3("%-40s"%("Variable %s"%nh))
if "JER" in ncat: sp[(tag,'JER',nh)]['tca'].cd()
else: sp[(tag,'JES',nh)]['tca'].cd()
if fout.Get("%s/%s/%s/%s/%s;1"%(f0,f1,f2,f3,hname)):
l4('%sLoading%s: %s \n%s%s(%s/%s/%s/%s)%s'%(red,plain,hname,grey,' '*9,f0,f1,f2,f3,plain))
sp[(tag,ncat,nh)]['th1'] = fout.Get("%s/%s/%s/%s/%s;1"%(f0,f1,f2,f3,hname)).Clone()
# sp[(tag,ncat,nh)]['th1'].Sumw2()
else:
l4('%sCreating%s: %s \n%s%s(%s/%s/%s/%s)%s'%(red,plain,hname,grey,' '*9,f0,f1,f2,f3,plain))
if not 'jetUnsPt' in nh: treedraw("%s>>%s"%(nhr,sp[(tag,ncat,nh)]['th1'].GetName()),CUT[tag])
else: treedraw("((%s - %s)/(%s))>>%s"%(nhr.replace('Uns',''),nhr,nhr.replace('Uns',''),sp[(tag,ncat,nh)]['th1'].GetName()),CUT[tag])
oldwd = gDirectory.GetPath()
gDirectory.cd("%s:/%s/%s/%s/%s/"%(fout.GetName(),f0,f1,f2,f3))
sp[(tag,ncat,nh)]['th1'].Write(sp[(tag,ncat,nh)]['th1'].GetName(),TH1.kOverwrite)
gDirectory.cd(oldwd)
#tnow = time()
#tarray += [time01(tstart,tnow,tarray)]
if 'mbb' in nh:
# gROOT.ProcessLineSync('TCanvas *can = new TCanvas("%s","%s",1800,1800)'%(sp[(tag,ncat,nh)]['th1'].GetName()[:100],sp[(tag,ncat,nh)]['th1'].GetName()[:100]))
# gROOT.ProcessLineSync('TH1F hroot = (TH1F)gDirectory->FindObjectAny("%s").Clone("%s")'%(sp[(tag,ncat,nh)]['th1'].GetName(),sp[(tag,ncat,nh)]['th1'].GetName()[:100]))
# gROOT.ProcessLineSync('double params[8] = {0.,0.,0.,0.,0.,0.,0.,0.}')
# gROOT.ProcessLineSync('fitTF1(can,hroot,%.2f,%.2f,%.2f,params,%i)'%(90.+offset[ncat],160.+offset[ncat],(float(variables[nh]['xmax'])-float(variables[nh]['xmin']))/float(variables[nh]['nbins_x']),colours[ncat]))
# sp[(tag,ncat,nh)]['tf1']['params'] = dc(list(ROOT.params))
# count = 0
# for i in ROOT.can.GetListOfPrimitives():
# if i.IsA().GetName() == "RooCurve" and count==0:
# sp[(tag,ncat,nh)]['tf1']['ful'] = i.Clone()
# count += 1
# elif i.IsA().GetName() == "RooCurve" and count==1:
# sp[(tag,ncat,nh)]['tf1']['bkg'] = i.Clone()
# count += 1
# break
# gROOT.ProcessLineSync('can.Close()')
sp[(tag,ncat,nh)]['th1'].Scale(1./float(sp[(tag,ncat,nh)]['th1'].Integral()))
c = TCanvas("%s"%(sp[(tag,ncat,nh)]['th1'].GetName()[:100]),"%s"%(sp[(tag,ncat,nh)]['th1'].GetName()[:100]),1800,1800)
h = sp[(tag,ncat,nh)]['th1'].Clone(sp[(tag,ncat,nh)]['th1'].GetName()[:100])
params = [0.]*9
fitTF1(c,h,50,200,(float(variables[nh]['xmax'])-float(variables[nh]['xmin']))/float(variables[nh]['nbins_x']),params,colours[ncat])
#print params
sp[(tag,ncat,nh)]['tf1']['params'] = dc(list(params))
count = 0
for i in c.GetListOfPrimitives():
if i.IsA().GetName() == "RooCurve" and count==0:
sp[(tag,ncat,nh)]['tf1']['ful'] = i.Clone()
count += 1
elif i.IsA().GetName() == "RooCurve" and count==1:
sp[(tag,ncat,nh)]['tf1']['bkg'] = i.Clone()
count += 1
break
c.Close()
for inh,nh in enumerate([variables[x]['var'] for x in opts.variable]):
if catveto(tag,nh): continue
# JES Up/Dn
if 'HbbJESUp' in friends:
sp[(tag,'Hbb',nh)]['th1'] = style01(sp[(tag,'Hbb',nh)]['th1'],kBlack,kGray)
sp[(tag,'HbbJESUp',nh)]['th1'] = style01(sp[(tag,'HbbJESUp',nh)]['th1'],kBlue+1,None,1)#7
sp[(tag,'HbbJESDn',nh)]['th1'] = style01(sp[(tag,'HbbJESDn',nh)]['th1'],kRed+1,None,1)#10
sp[(tag,'JES',nh)]['tca'],numbersJES = func01(opts,tag,sp[(tag,'JES',nh)]['tca'],dict((y,(sp[(tag,y,nh)]['th1'],sp[(tag,y,nh)]['tf1'],None)) for y in ['Hbb','HbbJESUp','HbbJESDn']),SEL[tag],TRG[tag])
# JER Up/Dn
if 'HbbJERCl' in friends:
sp[(tag,'HbbJERUp',nh)]['th1'] = style01(sp[(tag,'HbbJERUp',nh)]['th1'],kViolet+1,None,1)#7
sp[(tag,'HbbJERCl',nh)]['th1'] = style01(sp[(tag,'HbbJERCl',nh)]['th1'],kSpring-1,None,1)#7
#sp[(tag,'HbbJERDn',nh)]['th1'] = style01(sp[(tag,'HbbJERDn',nh)]['th1'],kMagenta+1,None,9)#10
sp[(tag,'JER',nh)]['tca'],numbersJER = func01(opts,tag,sp[(tag,'JER',nh)]['tca'],dict((y,(sp[(tag,y,nh)]['th1'],sp[(tag,y,nh)]['tf1'],sp[(tag,y,nh[0:3]+'Uns'+nh[3:])]['th1'] if 'jetPt' in nh else None)) for y in ['Hbb','HbbJERUp','HbbJERCl']),SEL[tag],TRG[tag]) #,'HbbJERDn'
# table
numbers = {}
if not numbersJES=={}:
for k,v in sorted(numbersJES.iteritems()): numbers[k] = v
if not numbersJER=={}:
for k,v in sorted(numbersJER.iteritems()): numbers[k] = v
if 'mva' in nh:
labels = ['Categories','JES Up','JES Down','JER','JER$^{+}$ wrt. JER']
print "\\begin{table}\n\t\\caption{Jet-energy scale and resolution uncertainty values per category.}\\centering \\small\n\t\\begin{tabular}{|*{%d}{c|}} \\hline"%(len(labels))
print "\t",
for il,l in enumerate(labels):
print "%20s%s"%("\makebox[2.2cm]{%s}"%l," &" if not il==len(labels)-1 else ""),
print "\\\\ \\hline\\hline"
for i,(cl,cu) in enumerate(sorted(list(set([(cl,cu) for (n,cl,cu) in numbers.iterkeys()])))):
print "\t%20d &"%(i-1 if not 'VBF' in tag else (i+3 if not i==0 else -2)),
for j,n in enumerate(['HbbJESUp','HbbJESDn','HbbJERCl','HbbJERUp']):
if n=='HbbJERUp': print "%20.4f"%(1-numbers[(n,cl,cu)]),
elif not n=='HbbJERCl': print "%20.3f &"%(1+numbers[(n,cl,cu)]),
else: print "%20.3f &"%numbers[(n,cl,cu)],
print "\\\\ \\hline"
if 'NOM' in tag: print "\t\\hline"
else: print ""
print "\\end{tabular}\n\\end{table}"