def plotHists(hists, files, xtitle, ytitle, title, pdfname, ly=False): c = ROOT.TCanvas() start = 0 label = Legend(p_ops.legendname) multi = ROOT.TMultiGraph() for i in range( len(hists) ): #This loops over the files. nhists(f1,f2,f3) is the format of hists. temp = files[i].GetName() if (p_ops.Normalized): hists[i] = NormalizeGraph(hists[i]) hists[i].SetLineColor(color[i]) hists[i].SetMarkerColor(color[i]) hists[i].SetMarkerStyle(style[i]) hists[i].SetMarkerSize(1) hists[i].SetLineWidth(2) hists[i].Rebin() # print 'i ' , i , ' MINIMUM: ' , hists[i].GetHistogram().GetMinimum() , ' MAXIMUM : ' , hists[i].GetHistogram().GetMaximum(), label.Add(hists[i], tag[i], "L") multi.Add(hists[i]) cluslabel = Legend("15 GeV < p_{T_{trigger}} < 20 GeV") #multi.SetMaximum(15) #multi.SetMinimum(5) multi.Draw("ALP") ROOT.gStyle.SetErrorX(0.0001) multi.SetMaximum(1.02 * multi.GetHistogram().GetMaximum()) multi.SetTitle(title) multi.GetXaxis().SetTitle(xtitle) multi.GetYaxis().SetTitle(ytitle) #multi.GetXaxis().SetTitle('x_{obs}^{Pb}:= #frac{p_{T}^{#gamma}e^{-#eta^{#gamma}} + p_{T}^{jet}e^{-#eta^{jet}}}{2E_{Pb}}') multi.GetXaxis().SetTitleSize(0.04) multi.GetXaxis().SetTitleOffset(1.6) #multi.GetYaxis().SetTitle('#frac{1}{N_{trig}}#frac{dN}{dx_{obs}^{Pb}}') #multi.GetXaxis().SetTitle('#Delta #phi (rads)') multi.GetXaxis().SetTitle(p_ops.xaxislabel) #multi.GetYaxis().SetTitle('#frac{1}{N_{trig}}#frac{dN}{d#Delta #phi}}') #multi.GetXaxis().SetRangeUser(0.005, 0.020) multi.GetXaxis().SetNdivisions(10) label.Draw(0.6, .96) cluslabel.Draw(0.55, 0.65) if ly == True: ROOT.gPad.SetLogy(1) latex = TLatex() latex.SetNDC() c.SaveAs(pdfname) c.Clear() print "END OF PLOTTING FUNCTION "
def plotHists(hists, files, xtitle, ytitle, title, pdfname, ly=False): c = ROOT.TCanvas("c", "c", 900, 600) pad1 = ROOT.TPad("pad1", "This is pad1", 0.0, 0.0, 0.9, 1.0, 0) pad2 = ROOT.TPad("pad2", "This is pad2", 0.85, 0.0, 1.0, 1.0, 0) pad1.Draw() pad2.Draw() pad1.cd() start = 0 label = Legend("") multi = ROOT.TMultiGraph() for i in range( len(hists) ): #This loops over the files. nhists(f1,f2,f3) is the format of hists. temp = files[i].GetName() if (p_ops.Normalized): hists[i] = NormalizeGraph(hists[i]) hists[i].SetLineColorAlpha(color[i], alphas[i]) hists[i].SetMarkerColorAlpha(color[i], alphas[i]) hists[i].SetMarkerStyle(style[i]) hists[i].SetMarkerSize(1) hists[i].SetLineWidth(2) # print 'i ' , i , ' MINIMUM: ' , hists[i].GetHistogram().GetMinimum() , ' MAXIMUM : ' , hists[i].GetHistogram().GetMaximum(), label.Add(hists[i], tag[i], "P") multi.Add(hists[i]) multi.Draw("AP") ROOT.gStyle.SetErrorX(0.0001) multi.SetMaximum(1.02 * multi.GetHistogram().GetMaximum()) multi.SetTitle(title) multi.GetXaxis().SetTitle(xtitle) multi.GetYaxis().SetTitle(ytitle) multi.GetXaxis().SetNdivisions(8) multi.GetYaxis().SetNdivisions(8) multi.GetXaxis().CenterTitle() multi.GetYaxis().CenterTitle() multi.SetMinimum(0) #if ly==True: #multi.SetMinimum(multi.GetHistogram().GetMinimum()+1e-4) if ly: multi.SetMinimum(multi.GetHistogram().GetMinimum() + 1e-4) ROOT.gPad.SetLogy(1) pad2.cd() label.Draw(0.0, .7) latex = TLatex() latex.SetNDC() c.SaveAs(pdfname) c.Clear() print "END OF PLOTTING FUNCTION "
def plotHists(hists, files, xtitle, ytitle, title, pdfname, ly=False): c = ROOT.TCanvas() start = 0 label = Legend("") multi = ROOT.TMultiGraph() for i in range( len(hists) ): #This loops over the files. nhists(f1,f2,f3) is the format of hists. temp = files[i].GetName() #print 'printing Temp ' , temp temp = temp.split('_MinBias')[0] if temp in tag: temp = temp + " , version %s " % (i + 1) hists[i].SetLineColor(color[i]) hists[i].SetMarkerColor(color[i]) hists[i].SetMarkerStyle(style[i]) hists[i].SetMarkerSize(1) hists[i].SetLineWidth(2) # print 'i ' , i , ' MINIMUM: ' , hists[i].GetHistogram().GetMinimum() , ' MAXIMUM : ' , hists[i].GetHistogram().GetMaximum(), label.Add(hists[i], tag[i], "L") multi.Add(hists[i]) multi.Draw("AP") ROOT.gStyle.SetErrorX(0.0001) #multi.SetMaximum(1.02*multi.GetHistogram().GetMaximum()) multi.SetMaximum(0.25) multi.SetMinimum(0.0) multi.SetTitle(title) multi.GetXaxis().SetTitle(xtitle) multi.GetYaxis().SetTitle(ytitle) multi.GetXaxis().SetNdivisions(10) label.Draw(0.2, .95) if ly == True: ROOT.gPad.SetLogy(1) latex = TLatex() latex.SetNDC() #latex.DrawLatex(0.2,0.90,"#font[62]{#scale[0.9]{lucidEvtOr}}") c.SaveAs(pdfname) c.Clear() print "END OF PLOTTING FUNCTION "
def plotHists(hists, files, xtitle, ytitle, title, pdfname, ly=False): c = ROOT.TCanvas() start = 0 label = Legend("") multi = ROOT.TMultiGraph() for i in range( len(hists) ): #This loops over the files. nhists(f1,f2,f3) is the format of hists. temp = files[i].GetName() if (p_ops.Normalized): hists[i] = NormalizeGraph(hists[i]) hists[i].SetLineColor(color[i]) hists[i].SetMarkerColor(color[i]) hists[i].SetMarkerStyle(style[i]) hists[i].SetMarkerSize(1) hists[i].SetLineWidth(2) # print 'i ' , i , ' MINIMUM: ' , hists[i].GetHistogram().GetMinimum() , ' MAXIMUM : ' , hists[i].GetHistogram().GetMaximum(), label.Add(hists[i], tag[i], "L") multi.Add(hists[i]) #multi.SetMaximum(15) #multi.SetMinimum(5) multi.Draw("ALP") ROOT.gStyle.SetErrorX(0.0001) multi.SetMaximum(1.02 * multi.GetHistogram().GetMaximum()) multi.SetTitle(title) multi.GetXaxis().SetTitle(xtitle) multi.GetYaxis().SetTitle(ytitle) multi.GetXaxis().SetTitle('Median density #rho [GeV]') multi.GetYaxis().SetTitle('normalized counts') multi.GetXaxis().SetNdivisions(10) label.Draw(0.6, .95) if ly == True: ROOT.gPad.SetLogy(1) latex = TLatex() latex.SetNDC() c.SaveAs(pdfname) c.Clear() print "END OF PLOTTING FUNCTION "
def Plotting(histos, purity, variable, rebin=1, title='', ymax=None): hSR, hBR, hBR_scaled, hSub, hMC, hweights = histos #hSR, hBR ,hMC = GetHistos(variable,rebin) hBR.SetTitle(title) #hBR.SetMinimum(0) hBR.Draw() hBR.SetMaximum(hBR.GetMaximum() * 1.2) hBR.GetYaxis().SetNdivisions(22) hBR.GetXaxis().SetNdivisions(9) hBR_scaled.Draw('samehist') #hBR_scaled.Draw('samehist') hSR.Draw('same') label = Legend(labeltitle) label.Add(hSR, "Signal Region", "P") label.Add(hBR, "Bkg Region", "P") label.Add(hBR_scaled, "Bkg Region, scaled by purity", "L") label.Draw(0.45, 0.90) plotname = variable + '_step1_purity%2.3f' % purity['nominal'] canvas.SaveAs('IntermediateStep_' + plotname + "_DATANAME_%s.pdf" % dataname) canvas.Clear() ######################## hMC.SetFillColorAlpha(ROOT.kOrange, 0.70) #hMC.Draw('hist') hs = ROOT.THStack() hs.Add(hSub) hs.Add(hBR) #hs.Add(hBR_scaled,'hist') hs.Draw('nostack') if (ymax > 0): hs.SetMaximum(ymax) else: hs.SetMaximum(hBR.GetMaximum() * 1.2) hs.SetTitle(title) hs.GetYaxis().SetNdivisions(12) hs.GetXaxis().SetNdivisions(10) #hSys = ObtainSystematicVariation(purity, rebin, variable) #hs.Add(hSys) #hSys.SetFillColorAlpha(ROOT.kGray,0.5) #hSys.SetFillStyle(3144) #hSys.Draw("E2same") #hSub.Draw("same") #hSys.Draw("E2same") #hMC.Draw("samehist") label = Legend(labeltitle) label.Add(hSub, "#gamma-jet", "P") #label.Add(hMC, "Pythia LO #gamma-jet","L") label.Add(hBR, "#pi^{0}-jet ", "P") label.Draw(.2, .90) latex = TLatex() latex.SetNDC() latex.SetTextColor(1) latex.DrawLatex(0.65, 0.88, "15 < p_{T}^{trig} < 20 GeV") latex.DrawLatex(0.65, 0.81, "p_{T}^{jet} > 5 GeV") if (variable != 'dPhi'): latex.DrawLatex(0.65, 0.74, "#Delta#phi > #pi/2") # myText(0.6,0.82,ROOT.kBlack, "12 < p_{T}^{trig} < 16 GeV") #myText(0.6,0.76, kBlack, "p_{T}^{jet} > 5 GeV") #myText(0.6,0.71,kBlack, "#Delta #phi > #pi/2") canvas.SaveAs('Final_' + plotname + "_DATANAME_%s.pdf" % dataname) canvas.Clear()
ROOT.gPad.SetLogz() c.cd(2) label = Legend("") label.Add(mc_reco, 'MC Reco', 'L') label.Add(mc_truth, 'MC True', 'L') hs_mc = ROOT.THStack() hs_mc.Add(mc_reco) hs_mc.Add(mc_truth) hs_mc.Draw('nostack') hs_mc.SetTitle('; x^{reco}_{J}; counts') label.Draw(0.5, .87) c.cd(3) ratio_mc = mc_truth.Clone() ratio_mc.SetMinimum(0) ratio_mc.SetLineColor(1) ratio_mc.Divide(mc_reco) ratio_mc.Draw() ratio_mc.SetTitle(' ; x^{truth}; Truth/Reco') c.Draw() c.SaveAs('UnfoldingMatrix%s.png' % (dataname)) def SetHistoStyle(h, color=2, alpha=0.5): h.SetMarkerColorAlpha(color, alpha) h.SetLineColorAlpha(color, alpha) h.SetMarkerStyle(20)
#zero.SetLineColor(1) #g_ratio[0].Fit(zero) g_ratio[0].SetMarkerSize(1) g_ratio[0].SetMarkerColor(color[1]) g_ratio[0].Print() print 'Mean of ratios ', '%.3f' % g_ratio[0].GetMean( 2), ' %, RMS of ratios ', '%.3f' % g_ratio[0].GetRMS(2), " % " multi.Add(g_ratio[0]) #label.Add(g_ratio[0],tag[1]+"/"+tag[0]) for j in range(2, len(tag)): g_ratio.append(DivideGraphs(allhists[i][0], allhists[i][j])) g_ratio[j - 1].SetMarkerColor(color[j]) g_ratio[j - 1].SetMarkerSize(1) #zero.SetLineColor(color[j]) #g_ratio[j-1].Fit(zero) multi.Add(g_ratio[j - 1]) # label.Add(g_ratio[j-1],tag[j]+"/"+tag[0]) multi.Draw("AP") label.Draw(0.5, .35) multi.SetMaximum(RatioLimit) multi.SetMinimum(-1 * RatioLimit) multi.GetYaxis().SetTitle("Ratio -1 [%]") multi.GetXaxis().SetTitle(allhists[i][0].GetXaxis().GetTitle()) #latex = TLatex() #latex.SetNDC() #latex.DrawLatex(0.5,0.90,tag[1]+"/" + tag[0]) #c.SaveAs(output_dir +"/"+hists[i]+"_"+Tag+"Ratios.pdf")
purity_Lambda.SetLineColorAlpha(4, 0.85) purity_NN.SetMarkerColorAlpha(2, 0.85) purity_Lambda.SetMarkerColorAlpha(4, 0.85) l.Add(purity_NN, "NN>0.85", "L") l.Add(purity_Lambda, "#lambda_{0}^{2} > 0.27", "L") purity_NN.SetTitle("; p_{T} cluster [GeV]; purity") purity_NN.GetXaxis().SetRangeUser(8.0, 25.0) purity_NN.SetMaximum(1.0) purity_NN.SetMinimum(0.0) purity_NN.Draw() purity_Lambda.Draw("same") purity_NN.SetLineColorAlpha(2, 0.85) purity_Lambda.SetLineColorAlpha(4, 0.85) l.Draw(.2, .35) c.SaveAs("purity.pdf") c.Clear() closure_NN.SetTitle("; p_{T} cluster [GeV]; closure test") closure_NN.SetLineColorAlpha(2, 0.65) closure_Lambda.SetLineColorAlpha(4, 0.65) closure_NN.SetMarkerStyle(20) closure_NN.SetLineWidth(2) closure_Lambda.SetMarkerStyle(20) closure_Lambda.SetLineWidth(2) closure_NN.SetMarkerColorAlpha(2, 0.85) closure_Lambda.SetMarkerColorAlpha(4, 0.85) closure_NN.Draw() closure_Lambda.Draw("same") l.Draw(.2, .35)