def listOfSteps(self,config) :
return ([
supy.steps.printer.progressPrinter()]
### pile-up reweighting
+[supy.calculables.other.Target("pileupTrueNumInteractionsBX0",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/pileup/HT300_Double_R12BCD_true.root","pileup"),
groups=[('H',[])]).onlySim()]
+[supy.calculables.other.Target("HPt",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/H400.root","hpt"),
).onlySim()]
### filters
+[steps.other.genParticleMultiplicity(pdgIds=[6001114,6002114,6003114],collection='XpdgId',min=2,max=2)]
### acceptance filters
#+[supy.steps.filters.value('mygenHT',min=180)]
+self.dijetSteps0()
+[steps.efficiency.NX(pdfweights=None)]
+[steps.efficiency.NXAcc(indicesAcc=self.AccCuts[-1]['name']+'Indices',pdfweights=None)]
+[supy.steps.filters.label('data cleanup'),
supy.steps.filters.value('primaryVertexFilterFlag',min=1),
supy.steps.filters.value('physicsDeclaredFilterFlag',min=1).onlyData(),
supy.steps.filters.value('beamScrapingFilterFlag',min=1),
supy.steps.filters.value('beamHaloTightFilterFlag',min=1),
supy.steps.filters.value('hbheNoiseFilterFlag',min=1),
supy.steps.filters.value('hcalLaserEventFilterFlag',min=1),
supy.steps.filters.value('ecalLaserCorrFilterFlag',min=1),
supy.steps.filters.value('eeBadScFilterFlag',min=1),
supy.steps.filters.value('ecalDeadCellTPFilterFlag',min=1),
supy.steps.filters.value('trackingFailureFilterFlag',min=1),
]
#+[steps.other.genParticleMultiplicity(6003114,min=2)]
### trigger
+[supy.steps.filters.label("hlt trigger"),
steps.trigger.hltFilterWildcard("HLT_HT300_DoubleDisplacedPFJet60_v"),
#steps.trigger.hltFilterWildcard("HLT_HT300_v"),
supy.steps.filters.value('caloHT',min=325),
]
+self.dijetSteps1()
+[steps.event.general()]
+[
steps.efficiency.NXReco(pdfweights=None,
indicesRecoLow=self.IniCuts[-1]['name']+'Indices',
indicesRecoHigh=self.IniCuts[-1]['name']+'Indices')
]
)
def reportCache(self) :
optstat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
r.tdrStyle.SetPadRightMargin(0.2)
r.gStyle.SetPalette(1)
self.setup()
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name])
sigmas = r.TH2D("sigmas","Contours of Integer Sigma, Gaussian Approximation;%s;%s"%self.labelsXY, *(self.binningX+self.binningY))
for iX in range(1,1+sigmas.GetNbinsX()) :
for iY in range(1,1+sigmas.GetNbinsY()) :
xy = (sigmas.GetXaxis().GetBinCenter(iX),
sigmas.GetYaxis().GetBinCenter(iY),
1)
sigmas.SetBinContent(iX, iY, math.sqrt( np.dot(xy, np.dot(self.matrix, xy) ) ) )
sigmas.SetContour(6, np.array([0.1]+range(1,6),'d'))
c = r.TCanvas()
c.Print(fileName+'.pdf[')
sigmas.Draw("cont3")
c.Print(fileName+'.pdf')
if self.xy :
self.xy.UseCurrentStyle()
self.xy.Draw('colzsame')
sigmas.Draw('cont3same')
c.Print(fileName+'.pdf')
if hasattr(self,'xySup') :
self.xySup.UseCurrentStyle()
self.xySup.Draw('colz')
sigmas.Draw('cont3same')
c.Print(fileName+'.pdf')
c.Print(fileName+'.pdf]')
print 'Wrote : %s.pdf'%fileName
r.gStyle.SetOptStat(optstat)
def reportCache(self) :
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
r.gStyle.SetPalette(1)
hists = self.setup()
if not hists :
print '%s.setup() failed'%self.name
return
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName +'[')
for h in hists.values() + [self.LR]:
h.UseCurrentStyle()
h.SetTitle(';'+self.label)
h.SetLineWidth(2)
hists['correct'].SetLineColor(r.kRed)
hists['correct'].Draw('hist')
hists['incorrect'].Draw('hist same')
c.Print(fileName)
self.LR.SetTitle(";%s;Likelihood Ratio, Correct:Incorrect"%self.label)
self.LR.SetMinimum(0)
self.LR.Draw('hist')
c.Print(fileName)
c.Print(fileName +']')
print 'Wrote : %s'%fileName
def plotExpLimit(analysis,n,org):
denom = []
for step in org.steps:
for plotName in sorted(step.keys()):
if plotName == 'NE': denom=step[plotName]
data={'bkg':[],'obs':[]}
for step in org.steps:
for plotName in sorted(step.keys()):
if 'ABCDEFGHcounts' not in plotName : continue
cutsidx=eval(plotName[:plotName.find('ABCDEFGH')])
for j,sample in enumerate(org.samples):
counts = getCounts(step[plotName][j])
name=sample['name'].split('.')[0]
if 'Data' in name: # get background estimate
print cutsidx
data['bkg'].append(getBkg(counts[:n],(analysis.scan[cutsidx],cutsidx)))
data['obs'].append(counts[0])
elif 'H' in name:
if name not in data.keys():
data[name] = []
nEvents = float(sample['nEvents'])*0.09
data[name].append((counts[0][0]/(denom[j].Integral()/4.),counts[0][1]/(denom[j].Integral()/4.)))
import pickle
pickle.dump(data,open(supy.whereami()+'/../results/data/data.pkl','w'))
def setupTdrStyle() :
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
#tweaks
r.tdrStyle.SetPadRightMargin(0.06)
r.tdrStyle.SetErrorX(r.TStyle().GetErrorX())
r.gStyle.SetPalette(1)
def listOfSteps(self,config) :
return ([
supy.steps.printer.progressPrinter(),]
### pile-up reweighting
+[supy.calculables.other.Target("pileupTrueNumInteractionsBX0",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/pileup/HT300_R12BCD_true.root","pileup"),
groups=[('qcd',[]),('H',[])]).onlySim()]
### filters
+[supy.steps.filters.label('data cleanup'),
supy.steps.filters.value('primaryVertexFilterFlag',min=1),
#supy.steps.filters.value('physicsDeclaredFilterFlag',min=1).onlyData(),
supy.steps.filters.value('beamScrapingFilterFlag',min=1),
supy.steps.filters.value('beamHaloTightFilterFlag',min=1),
supy.steps.filters.value('hbheNoiseFilterFlag',min=1),
supy.steps.filters.value('hcalLaserEventFilterFlag',min=1),
supy.steps.filters.value('ecalLaserCorrFilterFlag',min=1),
supy.steps.filters.value('eeBadScFilterFlag',min=1),
supy.steps.filters.value('ecalDeadCellTPFilterFlag',min=1),
supy.steps.filters.value('trackingFailureFilterFlag',min=1),
]
### trigger
+[supy.steps.filters.label("hlt trigger"),
steps.trigger.hltFilterWildcard("HLT_HT300_v"),
supy.steps.filters.value("caloHT",min=325),]
### plots
+[steps.event.general()]
+self.dijetSteps1()
+self.discs()
+self.dijetSteps2()
)
def reportCache(self) :
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
r.tdrStyle.SetPadRightMargin(0.06)
self.setup(None)
if not self.hists :
print '%s.setup() failed'%self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName +'[')
stamp = r.TText()
ssize = stamp.GetTextSize()
for f in 'BQN' :
leg = r.TLegend(0.31,0.65,0.9,0.95)
#leg.SetHeader("#eta range")
leg.SetFillColor(r.kWhite)
leg.SetBorderSize(0)
leg.SetTextFont(42)
for i,(color,style) in enumerate(zip([r.kBlack,r.kRed,r.kBlue],[1,7,8])) :
h = self.hists[f+str(i)]
label = h.GetTitle().split(',')[1].replace("0.000<","").replace("<"," < ")
letter = h.GetTitle().split(',')[0]
h.SetTitle(';#lower[0.2]{p_{#lower[-0.25]{T}}^{meas} (GeV)};#lower[-0.15]{Median log(E^{#lower[0.4]{gen}}/E^{#lower[0.4]{meas}})}')
h.SetLineColor(color)
h.SetLineStyle(style)
h.SetLineWidth(3 if style!=1 else 2)
h.SetMaximum(0.2)
h.SetMinimum(-0.2)
h.Draw("histsame" if i else "hist")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.2,0.2, {'B':'Jets from b quark hadronization', 'Q':'Jets from W boson decay', 'N':'Other jets'}[letter])
leg.AddEntry(h,label,'l')
leg.Draw()
r.gPad.RedrawAxis()
stamp.SetTextFont(62)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.16 ,0.96,"CMS")
stamp.SetTextFont(52)
stamp.SetTextSize(0.8 * ssize)
stamp.DrawTextNDC(0.27, 0.96, "Simulation")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.8, 0.96, "(8 TeV)")
c.Print(fileName)
c.Print(fileName +']')
print 'Wrote : %s'%fileName
r.gStyle.SetOptStat(optStat)
def reportCache(self) :
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
self.setup(None)
for hist in filter(None,self.histsBQN) :
hist.Scale(1./hist.Integral(0,hist.GetNbinsX()+1))
if None in self.histsBQN :
print '%s.setup() failed'%self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName +'[')
leg = r.TLegend(0.18,0.45,0.95,0.75)
#leg.SetHeader("jet flavor")
leg.SetFillColor(r.kWhite)
leg.SetBorderSize(0)
leg.SetTextFont(42)
for h in self.histsBQN :
h.Fill(h.GetBinCenter(1), h.GetBinContent(0))
h.SetBinContent(0,0)
height = 1.1 * max(h.GetMaximum() for h in self.histsBQN)
for i,(f,color,style) in enumerate(zip('BQN',[r.kBlack,r.kRed,r.kBlue],[1,7,8])) :
h = self.histsBQN[i]
h.UseCurrentStyle()
h.SetTitle(";%s;Probability / %.2f"%(h.GetXaxis().GetTitle().split()[0].replace('jet',''),(self.binning[2]-self.binning[1]) / self.binning[0]))
h.SetLineColor(color)
h.SetLineWidth(2 if style==1 else 3)
h.SetLineStyle(style)
h.SetMaximum(height)
h.SetMinimum(0)
h.Draw("hist" + ("same" if i else ""))
leg.AddEntry(h,{"B":"Jets from b quark hadronization","Q":"Jets from W boson decay","N":"Other jets"}[f],'l')
leg.Draw()
r.gPad.RedrawAxis()
stamp = r.TText()
ssize = stamp.GetTextSize()
stamp.SetTextFont(62)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.20 ,0.88,"CMS")
stamp.SetTextFont(52)
stamp.SetTextSize(0.8 * ssize)
stamp.DrawTextNDC(0.20, 0.83, "Simulation")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.84, 0.96, "(8 TeV)")
c.Print(fileName)
c.Print(fileName +']')
print 'Wrote : %s'%fileName
r.gStyle.SetOptStat(optStat)
def totalEfficiencies(self,org,dir=None,flavor='') :
recoLow,recoHigh,acceptance,denom=None,None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'NXLow'+flavor == plotName : recoLow=step[plotName]
if 'NXHigh'+flavor == plotName : recoHigh=step[plotName]
if 'NXAcc'+flavor == plotName : acceptance=step[plotName]
if 'NX'+flavor == plotName : denom=step[plotName]
acc = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(acceptance,denom)])
efflow = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoLow,denom)])
effhigh = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoHigh,denom)])
effacclow = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoLow,acceptance)])
effacchigh = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoHigh,acceptance)])
fs = [0.4,0.6,1.,1.4]
allfs = [0.1*a for a in fs]
allfs += fs
allfs += [10*a for a in fs]
allfs = [round(a,5) for a in allfs]
N=len(allfs)
f=1.
sysmap={'1000350':0.08,'1000150':0.08,'400150':0.1,'40050':0.08,'20050':0.22}
import pickle,math
for i,sample in enumerate(org.samples):
name = sample['name'].split('.')[0]
H,X=name.split('_')[1],name.split('_')[3]
sys=sysmap[H+X]
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
x,y=r.Double(0),r.Double(0)
eff = effhigh
effacc = effacchigh
if j<N/3:
eff = efflow
effacc = effacclow
eff[i].GetPoint(j,x,y)
e = f*float(y)
eErr = f*eff[i].GetErrorY(j)
effacc[i].GetPoint(j,x,y)
ea = f*float(y)
eaErr = f*effacc[i].GetErrorY(j)
acc[i].GetPoint(j,x,y)
a = float(y)
aErr = acc[i].GetErrorY(j)
#if e > 0. : eErr = e*math.sqrt(sys*sys+pow(eErr/e,2))
#else : eErr = 0.
#if ea > 0. : eaErr = ea*math.sqrt(sys*sys+pow(eaErr/ea,2))
#else : eaErr = 0.
factor=allfs[j]
print H,X,factor,a,aErr,e,eErr,ea,eaErr
data=[(a,aErr),(e,eErr),[ea,eaErr]]
pickle.dump(data,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def totalEfficiencies(self,org,dir=None,flavor='') :
recoLow,recoHigh,acceptance,denom=None,None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'LowNX'+flavor == plotName : recoLow=step[plotName]
if 'HighNX'+flavor == plotName : recoHigh=step[plotName]
if 'AccNX'+flavor == plotName : acceptance=step[plotName]
if 'NX'+flavor == plotName : denom=step[plotName]
acc = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(acceptance,denom)])
efflow = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoLow,denom)])
effhigh = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoHigh,denom)])
effacclow = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoLow,acceptance)])
effacchigh = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoHigh,acceptance)])
fs = [0.01,0.02,0.03,0.06,0.1,0.2,0.3,0.6,1.,2.,3.,6.,10.,20.,30.,60.,100.]
fs = [round(a,5) for a in fs]
N=len(fs)
f=0.89
sysmap={'1500494':0.10,'1000148':0.10,'350148':0.10,'12048':0.10}
import pickle,math,re
for i,sample in enumerate(org.samples):
digits = re.findall(r'\d+',sample['name'])
SQ,CHI=digits[0],digits[2]
name='SQ_'+str(SQ)+"_CHI_"+str(CHI)
sys=0.10
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
x,y=r.Double(0),r.Double(0)
eff = efflow
effacc = effacclow
eff[i].GetPoint(j,x,y)
e = f*float(y)
eErr = f*eff[i].GetErrorY(j)
effacc[i].GetPoint(j,x,y)
ea = f*float(y)
eaErr = f*effacc[i].GetErrorY(j)
acc[i].GetPoint(j,x,y)
a = float(y)
aErr = acc[i].GetErrorY(j)
if e > 0. : eErr = e*math.sqrt(sys*sys+pow(eErr/e,2))
else : eErr = 0.
if ea > 0. : eaErr = ea*math.sqrt(sys*sys+pow(eaErr/ea,2))
else : eaErr = 0.
factor=fs[j]
print SQ,CHI,factor,a,aErr,e,eErr,ea,eaErr
data=[(a,aErr),(e,eErr),[ea,eaErr]]
pickle.dump(data,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def reportCache(self):
if not self.activated:
print '%s: Not activated' % self.name
return
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C" % whereami())
r.setTDRStyle()
self.setup(None)
if None in self.histsBN:
print '%s.setup() failed' % self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1] +
[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName + '[')
histlist = [
self.histsBN, self.cdfBN, self.cdfBN_d, self.sfBN, self.funcsBN
]
titles = [
";CSV';pdf", ";CSV';cdf", ";CSV;cdf",
";CSV Working Point;Scale Factor", ";CSV';CSV\""
]
for hists, title in zip(histlist, titles):
leg = r.TLegend(0.36, 0.55, 0.6, 0.7)
leg.SetHeader("jet flavor")
height = 1.1 * max(h.GetMaximum() for h in hists)
if height < 0: height = 1.1 * max(sum(self.sfPointsBN, []))
for i, (f,
color) in enumerate(zip('BN',
[r.kRed, r.kBlue, r.kGreen])):
h = hists[i]
h.SetTitle(title)
h.UseCurrentStyle()
h.SetLineColor(color)
h.SetLineWidth(2)
h.SetMarkerColor(color)
h.SetMaximum(height)
h.SetMinimum(0)
h.Draw("hist" + ("same" if i else "")) if type(
h) != r.TGraph else h.Draw("APL"[1 if i else None:])
leg.AddEntry(h, {"B": "B jets", "N": "other jets"}[f], 'l')
leg.Draw()
c.Print(fileName)
c.Print(fileName + ']')
print 'Wrote : %s' % fileName
r.gStyle.SetOptStat(optStat)
def totEvtEff(self,org,dir=None):
high1,low1,denom=None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'HighNE1' == plotName : high1=step[plotName]
if 'LowNE1' == plotName : low1=step[plotName]
if 'NE' == plotName : denom=step[plotName]
efflow1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(low1,denom)])
effhigh1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(high1,denom)])
fs = [0.4,0.6,1.,1.4]# old factors for the record if not approved
#fs = [0.1,0.2,0.3,0.6,1.,2.,3.,6.,10.]
allfs = [0.1*a for a in fs] + fs + [10*a for a in fs]
allfs = [round(a,5) for a in allfs]
N=len(allfs)
forbidden=[7,8,9,16,17,18]
sysmap={'1000350':0.075,'1000150':0.075,'400150':0.096,'40050':0.091,'20050':0.10}
f=0.89
for i,sample in enumerate(org.samples):
digits=re.findall(r'\d+',sample['name'])
H,X=digits[1],digits[4]
sys=sysmap[H+X]
name='H_'+str(H)+'_X_'+str(X)
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
#if j in forbidden: continue
x,y=r.Double(0),r.Double(0)
efflow1[i].GetPoint(j,x,y)
e1 = f*float(y)
e1Err = f*efflow1[i].GetErrorY(j)
if j>N/3:
effhigh1[i].GetPoint(j,x,y)
e1p = f*float(y)
e1pErr = f*effhigh1[i].GetErrorY(j)
if e1 > 0. : e1Err = e1*math.sqrt(sys*sys+pow(e1Err/e1,2))
factor=allfs[j]
#if factor in [0.1,1,10]:
objects=[ H,X,factor*ctau,rnd(100*e1,3)]
print " & ".join(str(a) for a in objects ) + ' \\\\'
output=[(e1,e1Err),(e1,e1Err),[e1,e1Err]]
pickle.dump(output,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def listOfSteps(self,config) :
return ([
supy.steps.printer.progressPrinter(),]
### pile-up reweighting
+[supy.calculables.other.Target("pileupTrueNumInteractionsBX0",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/pileup/HT300_Double_R12BCD_true.root","pileup"),
groups=[('qcd',[]),('H',[])]).onlySim()]
### signal filters
+[steps.other.genParticleMultiplicity(pdgIds=[6002114],collection='XpdgId',min=2,max=2).onlySim()]
+[steps.efficiency.NE(pdfweights=None).onlySim()]
### filters
+[supy.steps.filters.label('data cleanup'),
supy.steps.filters.value('primaryVertexFilterFlag',min=1),
supy.steps.filters.value('physicsDeclaredFilterFlag',min=1).onlyData(),
supy.steps.filters.value('beamScrapingFilterFlag',min=1),
supy.steps.filters.value('beamHaloTightFilterFlag',min=1),
supy.steps.filters.value('hbheNoiseFilterFlag',min=1),
supy.steps.filters.value('hcalLaserEventFilterFlag',min=1),
supy.steps.filters.value('ecalLaserCorrFilterFlag',min=1),
supy.steps.filters.value('eeBadScFilterFlag',min=1),
supy.steps.filters.value('ecalDeadCellTPFilterFlag',min=1),
supy.steps.filters.value('trackingFailureFilterFlag',min=1),
]
### trigger
+[supy.steps.filters.label("hlt trigger"),
steps.trigger.hltFilterWildcard("HLT_HT300_DoubleDisplacedPFJet60_v"),
supy.steps.filters.value("caloHT",min=325),
#steps.event.runModulo(modulo=11,inverted=True).onlyData(),
]
### plots
+[steps.event.general()]
+self.dijetSteps1()
+[supy.steps.histos.multiplicity(self.Cuts[-2]['name']+'Indices')]
+[supy.steps.histos.multiplicity(self.Cuts[-1]['name']+'Indices')]
+self.discs()
+self.dijetSteps2()
)
def totalEfficiencies(self,org,dir=None,flavor='') :
recoLow,recoHigh,acceptance,denom=None,None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'LowNE1+'+flavor == plotName : recoLow=step[plotName]
if 'HighNE1+'+flavor == plotName : recoHigh=step[plotName]
if 'NE'+flavor == plotName : denom=step[plotName]
print recoLow
print denom
efflow = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoLow,denom)])
effhigh = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(recoHigh,denom)])
fs = [0.4,0.6,1.,1.4]
allfs = [0.1*a for a in fs]
allfs += fs
allfs += [10*a for a in fs]
allfs = [round(a,5) for a in allfs]
N=len(allfs)
f=1.
import pickle,math
for i,sample in enumerate(org.samples):
name = sample['name'].split('.')[0]
H,X=name.split('_')[1],name.split('_')[3]
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
x,y=r.Double(0),r.Double(0)
eff = effhigh
if j<N/3:
eff = efflow
eff[i].GetPoint(j,x,y)
e = f*float(y)
eErr = f*eff[i].GetErrorY(j)
factor=allfs[j]
print H,X,factor,e,eErr
data=[(e,eErr),(e,eErr),[e,eErr]]
pickle.dump(data,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def reportCache(self) :
if not self.activated:
print '%s: Not activated' % self.name
return
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
self.setup(None)
if None in self.histsBN :
print '%s.setup() failed'%self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName +'[')
histlist = [self.histsBN, self.cdfBN, self.cdfBN_d, self.sfBN, self.funcsBN]
titles = [";CSV';pdf",";CSV';cdf",";CSV;cdf",";CSV Working Point;Scale Factor",";CSV';CSV\""]
for hists,title in zip(histlist, titles):
leg = r.TLegend(0.36,0.55,0.6,0.7)
leg.SetHeader("jet flavor")
height = 1.1 * max(h.GetMaximum() for h in hists)
if height<0: height = 1.1 * max(sum(self.sfPointsBN,[]))
for i,(f,color) in enumerate(zip('BN',[r.kRed,r.kBlue,r.kGreen])) :
h = hists[i]
h.SetTitle(title)
h.UseCurrentStyle()
h.SetLineColor(color)
h.SetLineWidth(2)
h.SetMarkerColor(color)
h.SetMaximum(height)
h.SetMinimum(0)
h.Draw("hist" + ("same" if i else "")) if type(h)!=r.TGraph else h.Draw("APL"[1 if i else None:])
leg.AddEntry(h,{"B":"B jets","N":"other jets"}[f],'l')
leg.Draw()
c.Print(fileName)
c.Print(fileName +']')
print 'Wrote : %s'%fileName
r.gStyle.SetOptStat(optStat)
def totEvtEff(self,org,dir=None):
low1p,low1,low2p,denom,lowNX,denomX=None,None,None,None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'LowNE1' == plotName : low1=step[plotName]
if 'NE' == plotName : denom=step[plotName]
if 'NX' == plotName: denomX=step[plotName]
efflow1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(low1,denom)])
#fs = [0.01,0.02,0.03,0.06,0.1,0.2,0.3,0.6,1.,2.,3.,6.,10.,20.,30.,60.,100.]
fs = [0.4,0.6,1.,1.4]
fs = [round(a,5) for a in fs]
N=len(fs)
sysmap={'1500494':0.10,'1000148':0.10,'350148':0.10,'12048':0.10}
f=0.89
for i,sample in enumerate(org.samples):
digits=re.findall(r'\d+',sample['name'])
SQ,CHI=digits[0],digits[1]
name='SQ_'+str(SQ)+"_CHI_"+str(CHI) + ('_priv' if 'priv' in sample['name'] else '')
sys=0.1
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
x,y=r.Double(0),r.Double(0)
efflow1[i].GetPoint(j,x,y)
e1 = f*float(y)
e1Err = f*efflow1[i].GetErrorY(j)
if e1 > 0. : e1Err = e1*math.sqrt(sys*sys+pow(e1Err/e1,2))
factor=fs[j]
#if factor in [0.1,1,10]:
objects=[ SQ,CHI,factor*ctau,rnd(100*e1,3),rnd(100*e1Err,3)]
print " & ".join(str(a) for a in objects ) + ' \\\\'
output=[(e1,e1Err),(e1,e1Err),[e1,e1Err]]
name = name.replace('_priv','')
pickle.dump(output,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def listOfSteps(self,config) :
return ([
supy.steps.printer.progressPrinter()]
### filters
+[supy.steps.filters.label('data cleanup'),
supy.steps.filters.value('primaryVertexFilterFlag',min=1),
supy.steps.filters.value('physicsDeclaredFilterFlag',min=1).onlyData(),
supy.steps.filters.value('beamScrapingFilterFlag',min=1),
supy.steps.filters.value('beamHaloTightFilterFlag',min=1),
supy.steps.filters.value('hbheNoiseFilterFlag',min=1),
supy.steps.filters.value('hcalLaserEventFilterFlag',min=1),
supy.steps.filters.value('ecalLaserCorrFilterFlag',min=1),
supy.steps.filters.value('eeBadScFilterFlag',min=1),
supy.steps.filters.value('ecalDeadCellTPFilterFlag',min=1),
supy.steps.filters.value('trackingFailureFilterFlag',min=1),
]
### pile-up reweighting
+[supy.calculables.other.Target("pileupTrueNumInteractionsBX0",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/pileup/HT250_R12BCD_true.root","pileup"),
groups=[('qcd',[]),('H',[])]).onlySim()]
### trigger
+[supy.steps.filters.label("hlt trigger"),
steps.trigger.hltFilterWildcard("HLT_HT250_v"),
#steps.trigger.hltFilterWildcard("HLT_HT300_DoubleDisplacedPFJet60_v",veto=True),
steps.trigger.hltIsPresent("HLT_HT300_v"),]
+self.dijetSteps()
+[steps.event.general(),
supy.steps.histos.generic('pfHT',60,250,550,suffix="lower",title='; pfHT [GeV] ; events / bin'),
supy.steps.histos.generic('caloHT',60,250,550,suffix="lower",title='; caloHT [GeV] ; events / bin'),
steps.trigger.hltFilterWildcard("HLT_HT300_v"),
steps.event.general(),
supy.steps.histos.generic('pfHT',60,250,550,suffix="higher",title='; pfHT [GeV] ; events / bin'),
supy.steps.histos.generic('caloHT',60,250,550,suffix="higher",title='; caloHT [GeV] ; events / bin'),]
)
def listOfSteps(self, config):
return (
[
supy.steps.printer.progressPrinter(),
### filters
supy.steps.filters.label("data cleanup"),
supy.steps.filters.value("primaryVertexFilterFlag", min=1),
supy.steps.filters.value("physicsDeclaredFilterFlag", min=1).onlyData(),
supy.steps.filters.value("beamScrapingFilterFlag", min=1),
supy.steps.filters.value("beamHaloTightFilterFlag", min=1),
supy.steps.filters.value("hbheNoiseFilterFlag", min=1),
supy.steps.filters.value("hcalLaserEventFilterFlag", min=1),
supy.steps.filters.value("ecalLaserCorrFilterFlag", min=1),
supy.steps.filters.value("eeBadScFilterFlag", min=1),
supy.steps.filters.value("ecalDeadCellTPFilterFlag", min=1),
supy.steps.filters.value("trackingFailureFilterFlag", min=1),
]
### pile-up reweighting
+ [
supy.calculables.other.Target(
"pileupTrueNumInteractionsBX0",
thisSample=config["baseSample"],
target=(supy.whereami() + "/../data/pileup/HT300_R12BCD_true.root", "pileup"),
groups=[("qcd", []), ("H", [])],
).onlySim()
]
### trigger
+ [
supy.steps.filters.label("hlt trigger"),
steps.trigger.hltFilterWildcard("HLT_HT300_v"),
# steps.trigger.hltFilterWildcard("HLT_HT300_DoubleDisplacedPFJet60_v",veto=True),
steps.trigger.hltTriggerObjectMultiplicity("hlt2DisplacedHT300L1FastJetL3Filter", min=2),
]
### plots
+ [steps.event.general()]
+ self.jetPlots()
)
def totalEfficiencies(self, org, dir=None, flavor=''):
recoLow, recoHigh, acceptance, denom = None, None, None, None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'LowNX' + flavor == plotName: recoLow = step[plotName]
if 'HighNX' + flavor == plotName: recoHigh = step[plotName]
if 'AccNX' + flavor == plotName: acceptance = step[plotName]
if 'NX' + flavor == plotName: denom = step[plotName]
acc = tuple([
r.TGraphAsymmErrors(n, d, "cl=0.683 n")
for n, d in zip(acceptance, denom)
])
efflow = tuple([
r.TGraphAsymmErrors(n, d, "cl=0.683 n")
for n, d in zip(recoLow, denom)
])
effhigh = tuple([
r.TGraphAsymmErrors(n, d, "cl=0.683 n")
for n, d in zip(recoHigh, denom)
])
effacclow = tuple([
r.TGraphAsymmErrors(n, d, "cl=0.683 n")
for n, d in zip(recoLow, acceptance)
])
effacchigh = tuple([
r.TGraphAsymmErrors(n, d, "cl=0.683 n")
for n, d in zip(recoHigh, acceptance)
])
#fs = [0.4,0.6,1.,1.4] old factors for the record if not approved
fs = [0.1, 0.2, 0.3, 0.6, 1., 2., 3., 6., 10.]
allfs = [0.1 * a for a in fs]
allfs += fs
allfs += [10 * a for a in fs]
allfs = [round(a, 5) for a in allfs]
N = len(allfs)
forbidden = [7, 8, 9, 16, 17, 18]
f = 0.89
sysmap = {
'1000350': 0.075,
'1000150': 0.075,
'400150': 0.096,
'40050': 0.091,
'20050': 0.10
}
for i, sample in enumerate(org.samples):
digits = re.findall(r'\d+', sample['name'])
H, X = digits[0], digits[2]
name = 'H_' + str(H) + '_X_' + str(X)
sys = sysmap[H + X]
ctau = self.ctau[self.sig_names.index(name)]
data = {}
for factor in set(allfs):
data[factor] = []
for j in range(N):
if j in forbidden: continue
x, y = r.Double(0), r.Double(0)
eff = effhigh
effacc = effacchigh
if j < N / 3:
eff = efflow
effacc = effacclow
eff[i].GetPoint(j, x, y)
e = f * float(y)
eErr = f * eff[i].GetErrorY(j)
effacc[i].GetPoint(j, x, y)
ea = f * float(y)
eaErr = f * effacc[i].GetErrorY(j)
acc[i].GetPoint(j, x, y)
a = float(y)
aErr = acc[i].GetErrorY(j)
#if e > 0. : eErr = e*math.sqrt(sys*sys+pow(eErr/e,2))
#else : eErr = 0.
#if ea > 0. : eaErr = ea*math.sqrt(sys*sys+pow(eaErr/ea,2))
#else : eaErr = 0.
factor = allfs[j]
#print H,X,factor,a,aErr,e,eErr,ea,eaErr
output = [(a, aErr), (e, eErr), [ea, eaErr]]
data[factor].append(output)
#pickle.dump(output,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'_'+str(j)+'.pkl','w'))
for factor in data.keys():
list = data[factor]
ac = [obj[0][0] for obj in list if obj[0][0] > 0]
acErr = [obj[0][1] for obj in list if obj[0][0] > 0]
ef = [obj[1][0] for obj in list if obj[1][0] > 0]
efErr = [obj[1][1] for obj in list if obj[1][0] > 0]
efac = [obj[2][0] for obj in list if obj[2][0] > 0]
efacErr = [obj[2][1] for obj in list if obj[2][0] > 0]
if len(ef) == 0: continue
e, eErr = weightedAvg(ef, efErr)
a, aErr = weightedAvg(ac, acErr)
ea, eaErr = weightedAvg(efac, efacErr)
#eErr = e*math.sqrt(sys*sys+pow(eErr/e,2))
#eaErr = ea*math.sqrt(sys*sys+pow(eaErr/ea,2))
print H, X, factor, a, aErr, e, eErr, ea, eaErr
output = [(a, aErr), (e, eErr), [ea, eaErr]]
pickle.dump(
output,
open(
supy.whereami() + '/../results/' + dir +
'/efficiencies/' + name + '_' + str(factor) + '.pkl',
'w'))
def cppFiles() :
return [whereami()+"/../cpp/dict.cpp"]
def listOfSampleDictionaries(self) :
localDict = supy.samples.SampleHolder()
filePath = "%s/%s/integers.root"%(supy.whereami(),configuration.localpath())
localDict.add('integers','["%s"]'%filePath, lumi=0.009)
return [localDict]
def fileName():
return "%s/%s/skim.root" % (supy.whereami(), configuration.localpath())
import os
from supy import sites, whereami
__prefix = "%s/sites/%s" % (whereami(), sites.prefix())
def subScript():
return "%sSub.sh" % __prefix
def jobTemplate():
return "%sJob.sh" % __prefix
def condorTemplate():
return "%sTemplate.condor" % __prefix
def baseDir(fileName=""):
return fileName[:fileName.rfind('/')]
def condored(script):
return script.replace(".sh", ".condor") if os.path.exists(condorTemplate()) else script
def jobScriptFull(base="", tag="", sample="", iSlice=None, **_):
return "/".join([base, tag, sample, "job%d.sh" % iSlice])
def reportCache(self):
fileName = '/'.join(self.outputFileName.split('/')[:-1] + [self.name])
optstat = r.gStyle.GetOptStat()
from supy import whereami
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C" % whereami())
r.setTDRStyle()
r.tdrStyle.SetOptStat(0)
r.tdrStyle.SetOptFit(0)
r.tdrStyle.SetPalette(1)
r.tdrStyle.SetMarkerSize(0.5)
r.tdrStyle.SetTitleH(0.05)
r.tdrStyle.SetTitleW(0.4)
r.tdrStyle.SetTitleX(0.4)
r.tdrStyle.SetTitleY(1.0)
r.tdrStyle.SetTitleBorderSize(0)
samples = self.baseSamples()
names = [
'%s#rightarrow^{}t#bar{t} ' % i
for i in ['gg', 'qg', 'q#bar{q}', '#bar{q}g']
]
colors = [r.kBlack, r.kBlue, r.kRed, r.kGreen]
hists = [
self.fromCache(samples, ['2_x_y'], self.altTag)[s]['2_x_y']
for s in samples
]
for h in hists:
h.UseCurrentStyle()
h.SetTitle(';X_{T};X_{L}')
symmHists, antiHists = zip(*[self.prep(h) for h in hists])
symm, symm0, symm1, symm2 = zip(*symmHists)
anti, anti0, anti1 = zip(*antiHists)
for h, n in zip(symm, names):
h.SetTitle(n + ' (symmetric)')
for h, n in zip(anti, names):
h.SetTitle(n + ' (antisymmetric)')
height = max(h.GetBinContent(h.GetMaximumBin()) for h in symm)
c = r.TCanvas()
c.Print(fileName + '.pdf[')
c.Divide(2, 2)
r.tdrStyle.SetOptTitle(1)
for i, h in enumerate(symm):
c.cd(i + 1)
h.SetMaximum(height)
h.SetMinimum(0)
h.Draw('colz')
c.Print(fileName + '.pdf')
#for i,h in enumerate(symm) :
# c.cd(i+1)
# h.Draw('surf2')
#c.Print(fileName+'.pdf')
r.tdrStyle.SetOptTitle(0)
c.Clear()
c.cd(0)
for par in range(3):
hists = eval('symm%d' % par)
height = 1.05 * max(
h.GetBinContent(h.GetMaximumBin()) for h in hists)
for i, h in enumerate(hists):
h.GetYaxis().SetTitle('Fitted value of ' +
h.GetTitle().split('=')[-1])
fit = next(iter(h.GetListOfFunctions()), None)
if fit:
fit.SetLineColor(colors[i])
fit.SetLineWidth(1)
h.SetLineColor(colors[i])
h.SetMarkerColor(colors[i])
h.SetMaximum(height)
h.SetMinimum(-height if h.GetMinimum() < 0 else 0)
h.Draw('same' if i else '')
c.Print(fileName + '.pdf')
c.Clear()
c.Divide(2, 2)
r.tdrStyle.SetOptTitle(1)
height = max(h.GetBinContent(h.GetMaximumBin()) for h in anti)
for i, h in enumerate(anti):
c.cd(i + 1)
h.SetMaximum(height)
h.SetMinimum(-height)
h.Draw('colz')
c.Print(fileName + '.pdf')
#for i,h in enumerate(anti) :
# c.cd(i+1)
# h.Draw('surf2')
#c.Print(fileName+'.pdf')
r.tdrStyle.SetOptTitle(0)
c.Clear()
c.cd(0)
for par in range(2):
hists = eval('anti%d' % par)
height = 1.05 * max(
[h.GetBinContent(h.GetMaximumBin())
for h in hists] + [abs(h.GetMinimum()) for h in hists])
for i, h in enumerate(hists):
h.GetYaxis().SetTitle('Fitted value of ' +
h.GetTitle().split('=')[-1])
fit = next(iter(h.GetListOfFunctions()), None)
if fit:
fit.SetLineColor(colors[i])
fit.SetLineWidth(1)
h.SetLineColor(colors[i])
h.SetMarkerColor(colors[i])
h.SetMaximum(height)
h.SetMinimum(-height)
h.Draw('same' if i else '')
c.Print(fileName + '.pdf')
c.Clear()
height = 1.1 * max(h.GetMaximum() for h in symm)
funcs = [next(iter(s.GetListOfFunctions()), None) for s in symm]
[(func.SetLineStyle(1), func.SetLineWidth(1),
func.SetLineColor(colors[i])) for i, func in enumerate(funcs)]
for iY in range(1, 1 + symm[0].GetNbinsY()):
projs = []
for i, (s, func) in enumerate(zip(symm, funcs)):
proj = s.ProjectionX('%s_%d' % (s.GetName(), iY), iY, iY)
proj.SetLineColor(colors[i])
proj.SetMarkerColor(colors[i])
proj.SetMinimum(0)
proj.SetMaximum(height)
proj.Fit(func, 'QR')
projs.append(proj)
for p in projs:
p.Draw('same' if i else '')
c.Print(fileName + '.pdf')
c.Clear()
height = 1.1 * max([h.GetMaximum() for h in anti] +
[abs(h.GetMinimum()) for y in anti])
funcs = [next(iter(s.GetListOfFunctions()), None) for s in anti]
[(func.SetLineStyle(1), func.SetLineWidth(1),
func.SetLineColor(colors[i])) for i, func in enumerate(funcs)]
for iY in range(1, 1 + anti[0].GetNbinsY()):
projs = []
for i, (s, func) in enumerate(zip(anti, funcs)):
proj = s.ProjectionX('%s_%d' % (s.GetName(), iY), iY, iY)
proj.SetLineColor(colors[i])
proj.SetMinimum(-height)
proj.SetMaximum(height)
proj.Fit(func, 'QR')
projs.append(proj)
for p in projs:
p.Draw('same' if i else '')
c.Print(fileName + '.pdf')
c.Print(fileName + '.pdf]')
r.gStyle.SetOptStat(optstat)
print "Wrote file: %s.pdf" % fileName
def hadd() :
return ['hadd', whereami()+'/bin/phaddy'][1]
def listOfSteps(self,config) :
return ([
supy.steps.printer.progressPrinter()]
### pile-up reweighting
+[supy.calculables.other.Target("pileupTrueNumInteractionsBX0",thisSample=config['baseSample'],
target=(supy.whereami()+"/../data/pileup/HT300_Double_R12BCD_true.root","pileup"),
groups=[('SQ',[])]).onlySim()]
### acceptance filters
+self.dijetSteps0()
+[steps.event.general()]
+[steps.event.genevent()]
#+[steps.efficiency.NX(pdfweights=None)]
#+[steps.efficiency.NXAcc(indicesAcc=self.AccCuts[-1]['name']+'Indices',pdfweights=None)]
+[steps.efficiency.NE(pdfweights=None)]
+[supy.steps.filters.label('data cleanup'),
supy.steps.filters.value('primaryVertexFilterFlag',min=1),
supy.steps.filters.value('physicsDeclaredFilterFlag',min=1).onlyData(),
supy.steps.filters.value('beamScrapingFilterFlag',min=1),
supy.steps.filters.value('beamHaloTightFilterFlag',min=1),
supy.steps.filters.value('hbheNoiseFilterFlag',min=1),
supy.steps.filters.value('hcalLaserEventFilterFlag',min=1),
supy.steps.filters.value('ecalLaserCorrFilterFlag',min=1),
supy.steps.filters.value('eeBadScFilterFlag',min=1),
supy.steps.filters.value('ecalDeadCellTPFilterFlag',min=1),
supy.steps.filters.value('trackingFailureFilterFlag',min=1),
]
### trigger
+[supy.steps.filters.label("hlt trigger"),
#steps.trigger.hltFilterWildcard("HLT_HT300_v"),
#steps.trigger.hltTriggerObjectMultiplicity('hlt2DisplacedHT300L1FastJetL3Filter',min=0),
#steps.trigger.hltTriggerObjectMultiplicity('hlt2PFDisplacedJetsPt50',min=0),
#supy.steps.filters.multiplicity('TrigPromptGenQ1',min=2),
#supy.steps.filters.multiplicity('TrigPromptGenQ2',min=2),
steps.trigger.hltFilterWildcard("HLT_HT300_DoubleDisplacedPFJet60_v"),
supy.steps.filters.value('caloHT',min=325),
#supy.steps.filters.value('mycaloHT',min=325),
]
+self.dijetSteps1()
+self.discs()
+self.dijetSteps2()
+[steps.event.general(tag='1')]
#+[
# steps.efficiency.NXReco(pdfweights=None,
# indicesRecoLow='ABCDEFGHIndices0',
# indicesRecoHigh='ABCDEFGHIndices1')
# ]
+[
steps.efficiency.multiplicity(pdfweights=None,
indicesRecoLow='ABCDEFGHIndices0',
indicesRecoHigh='ABCDEFGHIndices1')
]
+[
steps.efficiency.NEReco(pdfweights=None,
indicesRecoLow='ABCDEFGHIndices0',
indicesRecoHigh='ABCDEFGHIndices1')
]
)
def inputFilesListFile(self, sampleName):
return "%s/inputFileLists/%s/%s.inputFiles" % (whereami(), self.name, sampleName)
def lumiEnv(initialize=True) :
return ". %s/%s %s %s"%(supy.whereami(),
supy.sites.lumiEnvScript(),
supy.sites.info(key='globalOutputDir'),
'true' if initialize else 'false')
def hadd() :
return ['hadd', whereami()+'/bin/phaddy'][1]
def fileName(min, max):
dir = "%s/%s" % (supy.whereami(), configuration.localpath())
return '%s/skim_%s.root' % (dir, stem(min, max))
def reportCache(self) :
useTDR = True
likes = self.likelihoods()
fileName = '/'.join(self.outputFileName.split('/')[:-1]+[self.name])
optstat = r.gStyle.GetOptStat()
if useTDR:
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C"%whereami())
r.setTDRStyle()
r.gStyle.SetOptStat(0)
r.gStyle.SetPalette(1)
c = r.TCanvas()
utils.tCanvasPrintPdf(c, fileName, False, '[')
with open(fileName+'.txt', "w") as file :
print >> file, '\n'.join(str(d) for d in self.populations)
print >> file
for key in sorted((set(likes[0]) & set(likes[1]) & set(likes[2])), key = lambda k: -1 if self.name==k else k) :
if not all(item[key] for item in likes) : continue
dilutions = [utils.dilution(bins1,bins2) for bins1,bins2 in itertools.combinations([utils.binValues(item[key]) for item in likes],2)]
print >> file, "\t".join([key.ljust(25)]+["%.4f"%d for d in dilutions])
h = 1.1*max(item[key].GetMaximum() for item in likes)
l = r.TLegend(0.75,0.85,0.98,0.98)
l.SetHeader("Dilutions : %.3f %.3f %.3f"%tuple(dilutions))
for i,(item,color,pop) in enumerate(zip(likes,[r.kBlack,r.kRed,r.kBlue],self.populations)) :
names = {'TridiscriminantWTopQCD':'#Delta',
'ProbabilityHTopMasses':'P_{MSD}',
'TopRatherThanWProbability':'P_{CSV}',
'muMetMt':'M_{T} (GeV)',
'elMetMt':'M_{T} (GeV)'
}
if useTDR:
item[key].SetTitle(';%s;probability / bin'%names[key])
I = item[key].Integral()
item[key].Scale(1./I)
else: I = 1
item[key].UseCurrentStyle()
item[key].SetLineColor(color)
item[key].SetLineWidth(2)
item[key].SetMaximum(h/I)
item[key].SetMinimum(0)
if not useTDR: item[key].GetYaxis().SetTitle("pdf")
item[key].Draw("hist" + ('same' if i else ''))
l.AddEntry(item[key], pop['pre'],'l')
if not useTDR: l.Draw()
utils.tCanvasPrintPdf(c, fileName, False)
c.Clear()
c.Divide(3,2)
covs = [self.fromCache([item['pre']], ["_cov_%s_%s"%pair for pair in itertools.combinations(self.dists.keys(),2)], tag = item['tag'])[item['pre']] for item in self.populations]
for key in (set(covs[0]) & set(covs[1]) & set(covs[2])) :
if not all(item[key] for item in covs) : continue
hists = [item[key] for item in covs]
deps = [utils.dependence(h,limit=1,inSigma=False) for h in hists]
for i,(h,d,pop) in enumerate(zip(hists,deps,self.populations)) :
d.SetTitle(pop['pre'])
c.cd(i+1); h.Draw('colz')
c.cd(i+4); d.Draw('colz')
utils.tCanvasPrintPdf(c, fileName, False)
c.Clear()
for key in sorted((set(likes[0]) & set(likes[1]) & set(likes[2])), key = lambda k: -1 if self.name==k else k) :
if not all(item[key] for item in likes) : continue
for i,j in itertools.combinations(range(3),2) :
k = next(k for k in range(3) if k not in [i,j])
templates = [ utils.binValues(likes[ii][key]) for ii in [i,j] ]
observed = utils.binValues(likes[k][key])
try: cs = utils.fractions.componentSolver(observed,templates)
except: cs = None
if not cs : continue
notK = likes[k][key].Clone('bf_not_'+likes[k][key].GetName())
notK.Reset()
notK.Add(likes[i][key],likes[j][key],cs.fractions[0],cs.fractions[1])
dil = utils.dilution(utils.binValues(likes[k][key]),utils.binValues(notK))
l = r.TLegend(0.75,0.85,0.98,0.98)
l.SetHeader("Dilution : %.3f"%dil)
l.AddEntry(likes[k][key], self.populations[k]['pre'], 'l')
l.AddEntry(notK, 'not '+self.populations[k]['pre'], 'l')
notK.SetLineStyle(2)
likes[k][key].Draw('hist')
notK.Draw('hist same')
l.Draw()
utils.tCanvasPrintPdf(c, fileName, False)
utils.tCanvasPrintPdf(c, fileName, True, ']')
r.gStyle.SetOptStat(optstat)
def __init__(self,indicesAcc='',indicesRecoLow='',indicesRecoHigh='',pdfweights=None):
for item in ['indicesAcc','indicesRecoLow','indicesRecoHigh','pdfweights']: setattr(self,item,eval(item))
self.trigweights = pickle.load(open(whereami()+"/../data/trigw"))
self.flavorMap={1:'uds',2:'uds',3:'uds',4:'c',5:'b',11:'e',13:'mu',1.5:'ud',7:'qmu',7.5:'qmu'}
def reportCache(self):
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C" % whereami())
r.setTDRStyle()
self.setup(None)
for hist in filter(None, self.histsBQN):
hist.Scale(1. / hist.Integral(0, hist.GetNbinsX() + 1))
if None in self.histsBQN:
print '%s.setup() failed' % self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1] +
[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName + '[')
leg = r.TLegend(0.18, 0.45, 0.95, 0.75)
#leg.SetHeader("jet flavor")
leg.SetFillColor(r.kWhite)
leg.SetBorderSize(0)
leg.SetTextFont(42)
for h in self.histsBQN:
h.Fill(h.GetBinCenter(1), h.GetBinContent(0))
h.SetBinContent(0, 0)
height = 1.1 * max(h.GetMaximum() for h in self.histsBQN)
for i, (f, color, style) in enumerate(
zip('BQN', [r.kBlack, r.kRed, r.kBlue], [1, 7, 8])):
h = self.histsBQN[i]
h.UseCurrentStyle()
h.SetTitle(";%s;Probability / %.2f" %
(h.GetXaxis().GetTitle().split()[0].replace('jet', ''),
(self.binning[2] - self.binning[1]) / self.binning[0]))
h.SetLineColor(color)
h.SetLineWidth(2 if style == 1 else 3)
h.SetLineStyle(style)
h.SetMaximum(height)
h.SetMinimum(0)
h.Draw("hist" + ("same" if i else ""))
leg.AddEntry(
h, {
"B": "Jets from b quark hadronization",
"Q": "Jets from W boson decay",
"N": "Other jets"
}[f], 'l')
leg.Draw()
r.gPad.RedrawAxis()
stamp = r.TText()
ssize = stamp.GetTextSize()
stamp.SetTextFont(62)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.20, 0.88, "CMS")
stamp.SetTextFont(52)
stamp.SetTextSize(0.8 * ssize)
stamp.DrawTextNDC(0.20, 0.83, "Simulation")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.84, 0.96, "(8 TeV)")
c.Print(fileName)
c.Print(fileName + ']')
print 'Wrote : %s' % fileName
r.gStyle.SetOptStat(optStat)
def fileName(self, index=None):
return "/".join([supy.whereami(), configuration.localpath(), "%d.root" % index])
def reportCache(self):
optStat = r.gStyle.GetOptStat()
r.gStyle.SetOptStat(0)
r.gROOT.ProcessLine(".L %s/cpp/tdrstyle.C" % whereami())
r.setTDRStyle()
r.tdrStyle.SetPadRightMargin(0.06)
self.setup(None)
if not self.hists:
print '%s.setup() failed' % self.name
r.gStyle.SetOptStat(optStat)
return
fileName = '/'.join(self.outputFileName.split('/')[:-1] +
[self.name]) + '.pdf'
c = r.TCanvas()
c.Print(fileName + '[')
stamp = r.TText()
ssize = stamp.GetTextSize()
for f in 'BQN':
leg = r.TLegend(0.31, 0.65, 0.9, 0.95)
#leg.SetHeader("#eta range")
leg.SetFillColor(r.kWhite)
leg.SetBorderSize(0)
leg.SetTextFont(42)
for i, (color, style) in enumerate(
zip([r.kBlack, r.kRed, r.kBlue], [1, 7, 8])):
h = self.hists[f + str(i)]
label = h.GetTitle().split(',')[1].replace("0.000<",
"").replace(
"<", " < ")
letter = h.GetTitle().split(',')[0]
h.SetTitle(
';#lower[0.2]{p_{#lower[-0.25]{T}}^{meas} (GeV)};#lower[-0.15]{Median log(E^{#lower[0.4]{gen}}/E^{#lower[0.4]{meas}})}'
)
h.SetLineColor(color)
h.SetLineStyle(style)
h.SetLineWidth(3 if style != 1 else 2)
h.SetMaximum(0.2)
h.SetMinimum(-0.2)
h.Draw("histsame" if i else "hist")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(
0.2, 0.2, {
'B': 'Jets from b quark hadronization',
'Q': 'Jets from W boson decay',
'N': 'Other jets'
}[letter])
leg.AddEntry(h, label, 'l')
leg.Draw()
r.gPad.RedrawAxis()
stamp.SetTextFont(62)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.16, 0.96, "CMS")
stamp.SetTextFont(52)
stamp.SetTextSize(0.8 * ssize)
stamp.DrawTextNDC(0.27, 0.96, "Simulation")
stamp.SetTextFont(42)
stamp.SetTextSize(ssize)
stamp.DrawTextNDC(0.8, 0.96, "(8 TeV)")
c.Print(fileName)
c.Print(fileName + ']')
print 'Wrote : %s' % fileName
r.gStyle.SetOptStat(optStat)
