示例#1
0
def makePlot(data):
	c=r.TCanvas();c.SetLogx();c.SetLogy()
	r.gPad.SetTopMargin(0.06)
	r.gPad.SetBottomMargin(0.15)
	r.gPad.SetLeftMargin(0.2)
	mg=r.TMultiGraph()
	gs=r.TGraphErrors()
	obs=[r.TGraph() for i in range(len(data['graphs']))]
	exp=[r.TGraph() for i in range(len(data['graphs']))]
	stylize(gs,obs,exp)
	leg=r.TLegend(0.23,0.6 - (0.13 if H in [350,700] else 0),0.55,0.82 - (0.13 if H in [350,700] else 0))
	leg2=r.TLegend(0.58,0.7 - (0.13 if H in [350,700] else 0),0.9,0.82 - (0.13 if H in [350,700] else 0))
	leg.SetFillColor(0);leg2.SetFillColor(0)
	leg.SetHeader("95% CL limits:")
	leg2.SetTextFont(62)
	gempty=r.TGraph()
	gempty.SetMarkerColor(0)
	leg2.AddEntry(gempty,'m_{#tilde{q}} = '+str(data['H'])+' GeV','P')

	for i,graph in enumerate(data['graphs']):
		points = graph['points']
		n=len(points)
		for j,(ctau,lim) in enumerate(points):
			gs.SetPoint(gs.GetN(),ctau,data['sigma'])
			gs.SetPointError(gs.GetN()-1,0,data['sigmaErr'])
			obs[i].SetPoint(j,ctau,lim['obs'])
			print data['H'], graph['X'], ctau, lim['obs']*1000
			exp[i].SetPoint(j,ctau,lim['1ps'])
			exp[i].SetPoint(2*n-1-j,ctau,lim['1ms'])
		
		leg.AddEntry(obs[i],'m_{#tilde{#chi}^{0}_{1}}=%s GeV' %graph['X'],'PL')

	for i in range(len(data['graphs'])): mg.Add(exp[i],'F')
	for i in range(len(data['graphs'])): mg.Add(obs[i],'LP')
	
	leg.AddEntry(exp[0],'Exp. limits (\\pm 1\\sigma)','F')
	leg.AddEntry(gs,'#sigma_{#tilde{q}#tilde{q}*+#tilde{q}#tilde{q}} \\pm 1\\sigma_{theory}','LF')
	mg.Add(gs,'LE3')
	cmsStamp(lumi=18510,coords=(0.5,0.87),preliminary=False)
	mg.Draw('A')
	mg.SetMaximum((8 if H in [350,700] else 40)*max(data['sigma'],max([r.TMath.MaxElement(e.GetN(),e.GetY()) for e in exp])))
	gmin,gmax = r.TMath.MinElement(gs.GetN(),gs.GetX()),r.TMath.MaxElement(gs.GetN(),gs.GetX())
	mg.GetXaxis().SetRangeUser(0.95*gmin,2*gmax)
	mg.GetXaxis().SetMoreLogLabels()
	mg.GetYaxis().SetTitle("#sigma(#tilde{q}#tilde{q}*+#tilde{q}#tilde{q}) \
    B^{2}(#tilde{#chi}^{0}_{1} #rightarrow u#bar{d}#mu) [pb]")
	mg.GetXaxis().SetTitle('#tilde{#chi}^{0}_{1} c#tau [cm]')
	mg.GetXaxis().SetTitleOffset(1.4)
	mg.GetYaxis().SetTitleOffset(1.8)
	leg.Draw('same')
	leg2.Draw('same')

	name=str(data['H'])
	c.SaveAs(name+'.eps')
	os.system('epstopdf '+name+'.eps && rm '+name+'.eps && mv '+name+'.pdf '+plotDir)
示例#2
0
def limitPlot(MH = None,MX = None,list = None,observed=False):
	c=r.TCanvas()
	n=len(list)
	g=[r.TGraph(n),r.TGraph(n),r.TGraph(2*n),r.TGraph(2*n)]
	mg=r.TMultiGraph()
	for i,obj in enumerate(list):
		if observed : g[0].SetPoint(i,obj['ctau'],obj['obs'])
		g[1].SetPoint(i,obj['ctau'],obj['exp'])
		g[2].SetPoint(i,obj['ctau'],obj['1ps'])
		g[2].SetPoint(2*n-1-i,obj['ctau'],obj['1ms'])
		g[3].SetPoint(i,obj['ctau'],obj['2ms'])
		g[3].SetPoint(2*n-1-i,obj['ctau'],obj['2ps'])

	stylize(g)
	mg.Add(g[3],'F')
	mg.Add(g[2],'F')
	mg.Add(g[1],'L')
	mg.SetMaximum(50*r.TMath.MaxElement(g[3].GetN(),g[3].GetY()))
	if observed : mg.Add(g[0],'PL')
	c.SetLogy()
	c.SetLogx()
	mg.Draw('A')
	mg.GetXaxis().SetTitle('X^{0} c#tau [cm]')
	ctaus=sorted([obj['ctau'] for obj in list])
	mg.GetXaxis().SetRangeUser(ctaus[0]*0.95,ctaus[-1]*2)
	if option=='ea':
		#mg.GetYaxis().SetTitle('#sigma #times BR #times Acceptance [pb] (95% CL)')
		mg.GetYaxis().SetTitle('#sigma B^{2} #times Acceptance [pb] (95% CL)')
	else:
		#mg.GetYaxis().SetTitle('#sigma #times BR [pb] (95% CL)')
		mg.GetYaxis().SetTitle('#sigma(H^{0} #rightarrow X^{0}X^{0}) B^{2}(X^{0} #rightarrow q#bar{q}) [pb]')

	leg=r.TLegend(0.23,0.55,0.60,0.79)
	leg.SetHeader("95% CL limits:")
	leg.SetFillColor(0)
	leg2=r.TLegend(0.55,0.65,0.85,0.79)
	leg2.SetFillColor(0)
	gempty=r.TGraph()
	gempty.SetMarkerColor(0)
	#leg.AddEntry(gempty,'95% CL limits','P')
	leg2.AddEntry(gempty,'m_{H^{0}} = '+str(MH)+' GeV','P')
	leg2.AddEntry(gempty,'m_{X^{0}} = '+str(MX)+' GeV','P')
	if observed : leg.AddEntry(g[0],'Observed','L')
	leg.AddEntry(g[1],'Expected','L')
	leg.AddEntry(g[2],'Expected \\pm 1\\sigma','F')
	leg.AddEntry(g[3],'Expected \\pm 2\\sigma','F')
	leg.Draw('same')
	leg2.Draw('same')
	cmsStamp(lumi=18510,coords=(0.5,0.87),preliminary=False)
	name=str(MH)+'_'+str(MX)+option
	os.chdir(plotDir)
	c.SaveAs(name+'.eps')
	os.system('epstopdf '+name+'.eps')
	os.system('rm '+name+'.eps')
	os.chdir('../../')
示例#3
0
def makePlot(data):
    c = r.TCanvas()
    c.SetLogx()
    c.SetLogy()
    r.gPad.SetTopMargin(0.06)
    r.gPad.SetBottomMargin(0.15)
    r.gPad.SetLeftMargin(0.2)
    mg = r.TMultiGraph()
    obs = [r.TGraph() for i in range(len(data["graphs"]))]
    exp = [r.TGraph() for i in range(len(data["graphs"]))]
    stylize(obs, exp)
    leg = r.TLegend(0.23, 0.62 - (0.13 if H in [350, 700] else 0), 0.55, 0.82 - (0.13 if H in [350, 700] else 0))
    leg2 = r.TLegend(0.58, 0.7 - (0.13 if H in [350, 700] else 0), 0.9, 0.82 - (0.13 if H in [350, 700] else 0))
    leg.SetFillColor(0)
    leg2.SetFillColor(0)
    leg.SetHeader("95% CL limits:")
    leg2.SetTextFont(62)
    gempty = r.TGraph()
    gempty.SetMarkerColor(0)
    leg2.AddEntry(gempty, "m_{H^{0}} = " + str(data["H"]) + " GeV", "P")

    for i, graph in enumerate(data["graphs"]):
        points = graph["points"]
        n = len(points)
        for j, (ctau, lim) in enumerate(points):
            obs[i].SetPoint(j, ctau, lim["obs"])
            exp[i].SetPoint(j, ctau, lim["1ps"])
            exp[i].SetPoint(2 * n - 1 - j, ctau, lim["1ms"])

        leg.AddEntry(obs[i], "m_{X^{0}}=%s GeV" % graph["X"], "PL")

    for i in range(len(data["graphs"])):
        mg.Add(exp[i], "F")
    for i in range(len(data["graphs"])):
        mg.Add(obs[i], "PL")

    leg.AddEntry(exp[0], "Exp. limits (\\pm 1\\sigma)", "F")
    cmsStamp(lumi=18510, coords=(0.5, 0.87), preliminary=False)
    mg.Draw("A")
    mg.SetMaximum(40 * max([r.TMath.MaxElement(e.GetN(), e.GetY()) for e in exp]))
    mg.GetYaxis().SetTitle("#sigma(H^{0} #rightarrow X^{0}X^{0}) B^{2}(X^{0} #rightarrow q#bar{q}) [pb]")
    mg.GetXaxis().SetTitle("X^{0} c#tau [cm]")
    mg.GetXaxis().SetTitleOffset(1.4)
    mg.GetYaxis().SetTitleOffset(1.8)
    leg.Draw("same")
    leg2.Draw("same")

    name = str(data["H"])
    c.SaveAs(name + ".eps")
    os.system("epstopdf " + name + ".eps && rm " + name + ".eps && mv " + name + ".pdf " + plotDir)
示例#4
0
def limitPlot(list = None):
	c=r.TCanvas()
	n=len(list)
	g=[r.TGraph(n),r.TGraph(n),r.TGraph(2*n),r.TGraph(2*n)]
	mg=r.TMultiGraph()
	den=list[0]['exp']
	for i,obj in enumerate(list):
		g[1].SetPoint(i,obj['relErr'],obj['exp']/den)
		g[2].SetPoint(i,obj['relErr'],obj['1ps']/den)
		g[2].SetPoint(2*n-1-i,obj['relErr'],obj['1ms']/den)
		g[3].SetPoint(i,obj['relErr'],obj['2ms']/den)
		g[3].SetPoint(2*n-1-i,obj['relErr'],obj['2ps']/den)

	stylize(g)
	func=r.TF1('func','1+[0]*x + [1]*x*x',0,90)
	func.SetLineWidth(2)
	func.SetMarkerSize(0)
	g[1].Fit('func')
	#mg.Add(g[3],'F')
	mg.Add(g[2],'F')
	mg.Add(g[1],'L')
	mg.SetMaximum(1.2*r.TMath.MaxElement(g[2].GetN(),g[2].GetY()))
	#c.SetLogy()
	#c.SetLogx()
	mg.Draw('A')
	mg.GetXaxis().SetTitle('Systematic uncertainty [%]')
	ctaus=sorted([obj['relErr'] for obj in list])
	mg.GetXaxis().SetRangeUser(ctaus[0]*0.95,ctaus[-1]*2)
	mg.GetYaxis().SetTitle('Limit / Limit (no uncertainty)')

	leg=r.TLegend(0.2,0.61,0.7,0.8)
	leg.SetFillColor(0)
	gempty=r.TGraph()
	gempty.SetMarkerColor(0)
	gempty.SetFillColor(0)
	gempty.SetLineColor(0)
	leg.AddEntry(gempty,'signal efficiency = '+str(dict['eff']*100)+'%')
	leg.AddEntry(g[1],'Exp. Limit','L')
	leg.AddEntry(g[2],'Exp. \\pm 1\\sigma','F')
	#leg.AddEntry(g[3],'Exp. \\pm 2\\sigma','F')
	leg.AddEntry(func,'1 + '+str(rnd(func.GetParameter(0),2))+' x + '+str(rnd(func.GetParameter(1),2))+' x^{2}')
	leg.Draw('same')
	cmsStamp(lumi=None,coords=(0.45,0.89))
	name=str(100*eff)
	os.chdir(plotDir)
	c.SaveAs(name+'percent.eps')
	os.system('epstopdf '+name+'percent.eps')
	os.system('rm '+name+'percent.eps')
	os.chdir('../../')
示例#5
0
def limitPlot(MH = None,MX = None,list = None,observed=False):
	if MX==148: MX=150
	elif MX==494: MX=500
	print MX
	c=r.TCanvas()
	n=len(list)
	g=[r.TGraph(n),r.TGraph(n),r.TGraph(2*n),r.TGraph(2*n),r.TGraphErrors(n)]
	mg=r.TMultiGraph()
	for i,obj in enumerate(list):
		if observed : g[0].SetPoint(i,obj['ctau'],obj['obs'])
		g[1].SetPoint(i,obj['ctau'],obj['exp'])
		g[2].SetPoint(i,obj['ctau'],obj['1ps'])
		g[2].SetPoint(2*n-1-i,obj['ctau'],obj['1ms'])
		g[3].SetPoint(i,obj['ctau'],obj['2ms'])
		g[3].SetPoint(2*n-1-i,obj['ctau'],obj['2ps'])
		g[4].SetPoint(i,obj['ctau'],obj['sigma'])
		g[4].SetPointError(i,0,obj['sigmaErr']*obj['sigma'])

	stylize(g)
	mg.Add(g[3],'F')
	mg.Add(g[2],'F')
	mg.Add(g[1],'L')
	mg.Add(g[4],'LE3')
	maxg=r.TMath.MaxElement(g[3].GetN(),g[3].GetY())
	ming=r.TMath.MinElement(g[3].GetN(),g[3].GetY())
	mg.SetMaximum((6 if MH in [350,700] else 40)*max(maxg,obj['sigma']))
	mg.SetMinimum(0.5*min(ming,obj['sigma']))
	if observed : mg.Add(g[0],'PL')
	c.SetLogy()
	c.SetLogx()
	mg.Draw('A')
	mg.GetXaxis().SetTitle('#tilde{#chi}^{0}_{1} c#tau [cm]')
	mg.GetXaxis().SetMoreLogLabels()
	mg.GetXaxis().SetNdivisions(303)
	ctaus=sorted([obj['ctau'] for obj in list])
	mg.GetXaxis().SetRangeUser(ctaus[0]*0.95,ctaus[-1]*2)
	if option=='ea':
		#mg.GetYaxis().SetTitle('#sigma #times BR #times Acceptance [pb] (95% CL)')
		mg.GetYaxis().SetTitle('#sigma #times Acceptance [pb] (95% CL)')
	else:
		#mg.GetYaxis().SetTitle('#sigma #times BR [pb] (95% CL)')
		mg.GetYaxis().SetTitle("#sigma(#tilde{q}#tilde{q}*+#tilde{q}#tilde{q}) \
		B^{2}(#tilde{#chi}^{0}_{1} #rightarrow u#bar{d}#mu) [pb]")

	leg=r.TLegend(0.23,0.6 - (0.13 if MH in [350,700] else 0),0.55,0.82 - (0.13 if MH in [350,700] else 0))
	leg.SetFillColor(0)
	leg2=r.TLegend(0.58,0.6 - (0.13 if MH in [350,700] else 0),0.9,0.82 - (0.13 if MH in [350,700] else 0))
	leg2.SetFillColor(0)
	gempty=r.TGraph()
	gempty.SetMarkerColor(0)
	leg2.AddEntry(gempty,'m_{#tilde{q}} = '+str(MH)+' GeV','P')
	leg2.AddEntry(gempty,'m_{#tilde{#chi}^{0}_{1}} = '+str(MX)+' GeV','P')
	leg2.AddEntry(g[4],'#sigma_{#tilde{q}#tilde{q}*+#tilde{q}#tilde{q}} \\pm 1\\sigma_{theory}','LF')

	
	if observed : leg.AddEntry(g[0],'Observed','PL')
	leg.SetHeader("95% CL limits:")
	leg.AddEntry(g[1],'Expected','L')
	leg.AddEntry(g[2],'Expected \\pm 1\\sigma','F')
	leg.AddEntry(g[3],'Expected \\pm 2\\sigma','F')
	leg.Draw('same')
	leg2.Draw('same')
	cmsStamp(lumi=18510,coords=(0.5,0.87),preliminary=False)
	name=str(MH)+'_'+str(MX)+option
	os.chdir(plotDir)
	c.SaveAs(name+'.eps')
	os.system('epstopdf '+name+'.eps')
	os.system('rm '+name+'.eps')
	os.chdir('../../')
示例#6
0
文件: ABCDscan.py 项目: hardenbr/djpy
def plotABCDscan(analysis,org,plotter,n,blind=True,onlyB=False):

	setupTdrStyle()


	plotter.pdfFileName = plotter.pdfFileName.replace(analysis.name+'.pdf','Scans_'+analysis.name+'.pdf')
	plotter.canvas.Clear()
	plotter.printCanvas("[")
	text1 = plotter.printTimeStamp()
	plotter.flushPage()

	# get all the counts
	counts = [[0]*len(analysis.scan) for sample in org.samples]
	for step in org.steps : 
		for plotName in sorted(step.keys()) :
			if 'ABCDEFGHcounts' not in plotName: continue
			i = eval(plotName[:plotName.find('ABCDEFGH')])
			for j in range(len(org.samples)): counts[j][i] = getCounts(step[plotName][j])

	# pick points to scan
	scans=[]
	for cut in analysis.scanPrompt: scans.append((cut,cut,None))

	# constant names
	cutNames = ['(NPrompt1,PromptFrac1)','(NPrompt2,PromptFrac2)','DiscVtx']
	histNames = ['observed','FG/B','EG/C','DG/A','BE/A','CF/A','EF/D','BCD/A^{2}']

	# plot scans
	for scan in scans:
		plotter.canvas=r.TCanvas("c","c",600,600)
		plotter.canvas.Divide(1,2)
		plotter.canvas.cd(1).SetPad(0.01,0.30+0.0,0.99,0.99)
		plotter.canvas.cd(1).SetTopMargin(0.07)
		plotter.canvas.cd(1).SetBottomMargin(0.)
		plotter.canvas.cd(2).SetPad(0.01,0.01,0.99,0.30)
		plotter.canvas.cd(2).SetTopMargin(0.)
		plotter.canvas.cd(2).SetBottomMargin(0.35)
		plotter.canvas.cd(1)
		r.gPad.SetLogy()
		#r.gPad.SetTicky(0)
	
		title=''
		#title='max Prompt Tracks = %s, max Prompt Energy Fraction = %s'%(scan[0][0],scan[0][1])
		xtitle = 'Vertex/cluster discriminant'
		ytitle = 'Number of events'

		indices = [i for i,cuts in enumerate(analysis.scan) if len(listdiff(cuts,scan))<=1]
		labels = [string(cuts[scan.index(None)]) for i,cuts in enumerate(analysis.scan) if i in indices]
		# first make a plot of signal efficiency
		sigSamples = [sample for sample in org.samples if 'H' in sample['name']]		
	 	sigeff = [r.TH1F('','',len(indices),0,1) for sample in sigSamples]
		for j,sample in enumerate(sigSamples):
			i = org.indexOfSampleWithName(sample['name'])
			norm = sample['xs']*org.lumi
			for k,idx in enumerate(indices):
				sigeff[j].SetBinContent(k+1,100*counts[i][idx][0][0]/float(2*norm))
				sigeff[j].SetBinError(k+1,100*counts[i][idx][0][1]/float(norm))
				sigeff[j].GetXaxis().SetBinLabel(k+1,labels[k])

		# Data/QCD plots with signal efficiency on the same plot
		for j,sample in enumerate(org.samples):
			if 'H' in sample['name'] : continue

			histos = [r.TH1F(name,title,len(indices),0,1) for name in histNames]
			histob = r.TH1F('predicted bkg.',title,len(indices),0,1)
			histob0 = r.TH1F('predicted bkg.',title,len(indices),0,1)
			histoz = r.TH1F('','',len(indices),0,1)

			for h in histos: h.GetXaxis().SetNdivisions(len(indices)*100+10,False)
			histoz.GetXaxis().SetNdivisions(len(indices)*100+10,False)

			for k,idx in enumerate(indices):
				b,berr = getBkg(counts[j][idx],None)
				histob.SetBinContent(k+1,b)
				histob.SetBinError(k+1,berr)
				histob0.SetBinContent(k+1,b)
				histob0.SetBinError(k+1,0.00001)
				N=int(counts[j][idx][0][0])
				if N==0: 
					histoz.SetBinContent(k+1,-1e5)
					continue
				p=pvalue(b,berr,N,1e4)
				z=r.RooStats.PValueToSignificance(p)
				histoz.SetBinContent(k+1,z)
				histoz.SetBinError(k+1,0.)

			if onlyB:
				legend = r.TLegend(0.5, 0.65, 0.93, 0.83)
			else:
				legend = r.TLegend(0.7, 0.55, 0.93, 0.93)
			for i in reversed(range(n)):
				if blind and 'Data' in sample['name'] and i==0: continue
				for k,idx in enumerate(indices):
					histos[i].SetBinContent(k+1,counts[j][idx][i][0])
					histos[i].SetBinError(k+1,counts[j][idx][i][1])
					histos[i].GetXaxis().SetBinLabel(k+1,labels[k])
					histoz.GetXaxis().SetBinLabel(k+1,labels[k])
					histob.GetXaxis().SetBinLabel(k+1,'')
					histob0.GetXaxis().SetBinLabel(k+1,'')
					
				histos[i].GetXaxis().SetTitle(xtitle)
				histos[i].GetYaxis().SetTitle(ytitle)
				histos[i].SetStats(False)
				histob.SetStats(False)
				histos[i].GetYaxis().SetTitleOffset(1.25)
				histos[i].GetYaxis().SetTitleSize(0.066)
				histos[i].GetYaxis().SetLabelSize(0.062)
				histoz.GetXaxis().SetTitle(xtitle)
				histoz.SetTitle('')
				histoz.SetStats(0)
				histoz.SetMarkerStyle(8)
				histob.SetMarkerSize(0)
				histob0.SetMarkerSize(0)
				histos[i].SetMarkerStyle(25 if i!=0 else 8)
				if i==(n-1):histos[i].SetMarkerStyle(21)
				histos[i].SetMarkerColor(i+1)
				histos[i].SetFillColor(0)
				histos[i].SetLabelSize(0.07)
				if onlyB: 
					if i==0:
						legend.AddEntry(histos[i],'Observed background')
				else:
					legend.AddEntry(histos[i],histNames[i])
				option='EX0' if i==(n-1) else 'EX0same'
				histos[i].Draw(option)
			if onlyB:
				legend.AddEntry(histob,'Predicted background')
				histob.SetFillColor(r.kBlue)
				histob0.SetFillColor(r.kWhite)
				histob.SetFillStyle(3001)
				histob0.SetLineWidth(3)
				histob.SetLineWidth(3)
				histob0.SetLineColor(r.kBlue)
				histob.SetLineColor(r.kBlue)
				histos[0].SetLineWidth(2)
				histos[0].Draw('EX0')
				histob.Draw("E2same")
				histob0.Draw("Lsame")
				histos[0].Draw('EX0same')
			histos_tmp=tuple([histos[i] for i in range(n)])
			plotter.setRanges(histos_tmp,*plotter.getExtremes(1,histos_tmp,[False]*n))
			
			if onlyB:
				cmsStamp(lumi=18500,coords=(0.71,0.84),preliminary=False)
				#cmsStamp(lumi=None,coords=(0.78,0.88))
			else:
				cmsStamp(lumi=org.lumi,coords=(0.45,0.88),simulation=True)
				#cmsStamp(lumi=None,coords=(0.45,0.85))
			
			pad = r.TPad("pad2","",0,0,1,1)
			pad.SetFillStyle(4000)
			pad.SetFrameFillStyle(0)
			pad.SetLogy(0)
			pad.Draw()
			pad.cd()
			for i,sample in enumerate(sigSamples):
				option='histY+' + ('same' if i>0 else '')
				sigeff[i].SetLineWidth(1)
				sigeff[i].SetStats(False)
				sigeff[i].SetLabelSize(0.06)
				sigeff[i].SetLineColor(i+2)
				sigeff[i].SetLineStyle(2)
				sigeff[i].GetYaxis().SetRangeUser(0,45)
				sigeff[i].GetYaxis().SetTitle('efficiency [%]')
				sigeff[i].Draw(option)
				legend.AddEntry(sigeff[i],sample['name'].split('.')[0])
			
			legend.SetFillColor(0)
			legend.SetBorderSize(0)
			legend.Draw("same")

			plotter.canvas.cd(2)
			r.gPad.SetGridy()
			histoz.GetYaxis().SetNdivisions(505,True)
			histoz.GetYaxis().SetTitleOffset(0.5)
			histoz.GetYaxis().SetTitleSize(0.16)
			histoz.GetXaxis().SetTitleOffset(1.0)
			histoz.GetXaxis().SetTitleSize(0.16)
			histoz.GetYaxis().SetLabelSize(0.14)
			histoz.GetYaxis().SetLabelOffset(0.015)
			histoz.GetYaxis().SetTickLength(1.3*histoz.GetYaxis().GetTickLength())
			histoz.GetXaxis().SetTickLength(2.*histoz.GetXaxis().GetTickLength())
			histoz.GetXaxis().SetLabelSize(0.19)
			histoz.GetXaxis().SetLabelOffset(0.02)
			histoz.GetYaxis().SetTitle('Significance ')
			#histoz.GetYaxis().CenterTitle()
			histoz.GetYaxis().SetRangeUser(-2.99,2.99)
			histoz.Draw('P')
			plotter.printCanvas()
			#plotter.canvas.Clear()

	plotter.printCanvas("]")
	print plotter.pdfFileName, "has been written."