def Ratio(histo1,histo2, recorded, title):
#gSystem.Exec("mkdir -p ZPlots")
can1 = makeCMSCanvas(str(random.random()),"mult vs lumi ",900,700)
lumi = []
lumi_err = []
ratio = []
ratio_err = []
sumLumi = 0.
for i in range(0,len(recorded)):
sumLumi += float(recorded[i])
lumi.append(sumLumi - float(recorded[i])/2)
lumi_err.append(float(recorded[i])/2)
ratio.append(histo1[i].GetEntries()/histo2[i].GetEntries())
ratio_err.append(0)
graph1 = TGraphErrors(len(recorded),array('d',lumi),array('d',ratio),array('d',lumi_err),array('d',ratio_err))
can1.cd()
graph1.SetTitle("")
graph1.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph1.GetYaxis().SetTitle("e^{+}e^{-}/#mu^{+}#mu^{-}")
graph1.SetMarkerStyle(20)
graph1.SetMarkerSize(1)
graph1.Draw("AP")
printLumiPrelOut(can1)
can1.SaveAs("ZPlots/Z_ratio_"+title+".pdf")
can1.SaveAs("ZPlots/Z_ratio_"+title+".png")
return;
def ZMultVsLumi(histo, recorded, outputDir, title):
#gSystem.Exec("mkdir -p ZPlots")
can1 = makeCMSCanvas(str(random.random()),"mult vs lumi ",900,700)
lumi = []
lumi_err = []
mult = []
mult_err = []
sumLumi = 0.
for i in range(0,len(recorded)):
sumLumi += float(recorded[i])
lumi.append(sumLumi - float(recorded[i])/2)
lumi_err.append(float(recorded[i])/2)
mult.append(histo[i].GetEntries()/float(recorded[i]))
mult_err.append(math.sqrt(histo[i].GetEntries()/float(recorded[i])))
graph1 = TGraphErrors(len(lumi),array('d',lumi),array('d',mult),array('d',lumi_err),array('d',mult_err))
can1.cd()
graph1.SetTitle("")
graph1.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph1.GetYaxis().SetTitle("#Z / fb^{-1}")
graph1.SetMarkerStyle(20)
graph1.SetMarkerSize(1)
graph1.Draw("AP")
printLumiPrelOut(can1)
can1.SaveAs(str(outputDir) + "/Z_multiplicity_"+title+".pdf")
can1.SaveAs(str(outputDir) + "/Z_multiplicity_"+title+".png")
return graph1;
def DoCBFit(histo, ZZtree, title, p):
canv = makeCMSCanvas(str(random.random()),"Fit result ",900,700)
Z1_fitFunction = TF1('Z1_fitFunction',DoubleCB(),60. ,120., 7)
Z1_fitFunction.SetParameters(p[0],p[1],p[2],p[3],p[4],p[5],p[6])
Z1_fitFunction.SetParLimits(0,85.,95.)#mean
Z1_fitFunction.SetParLimits(1,0.,5.)#width
Z1_fitFunction.SetParLimits(2,0.,2.)#alpha1
Z1_fitFunction.SetParLimits(3,0.,100.)#n1
Z1_fitFunction.SetParLimits(4,0.,2.)#alpha2
Z1_fitFunction.SetParLimits(5,0.,100.)#n2
Z1_fitFunction.SetParLimits(6,0.,1000000.)#const
Z1_fitFunction.SetParName(0,"Mean")#mean
Z1_fitFunction.SetParName(1,"Sigma")#width
Z1_fitFunction.SetParName(2,"#alpha_{1}")#alpha1
Z1_fitFunction.SetParName(3,"n_{1}")#n1
Z1_fitFunction.SetParName(4,"#alpha_{2}")#alpha2
Z1_fitFunction.SetParName(5,"n_{2}")#n2
Z1_fitFunction.SetParName(6,"C")#const
canv.cd()
histo.Fit(Z1_fitFunction)
gStyle.SetOptFit()
histo.SetTitle("")
histo.Draw()
print ("Mass: " +str(Z1_fitFunction.GetParameters()[0]) + " Width: " + str(Z1_fitFunction.GetParameters()[1]))
printLumiPrelOut(canv)
canv.SaveAs("DataVsMC/FitResults/"+title+"_fit.pdf")
canv.SaveAs("DataVsMC/FitResults/"+title+"_fit.png")
return Z1_fitFunction.GetParameters()[0], Z1_fitFunction.GetParError(0);
def DoLandauFit(histo, lumi, ZZtree, title):
#gSystem.Exec("mkdir -p FitResults")
can = []
result = []
for i in range(0,len(histo)):
canv = makeCMSCanvas(str(random.random())+str(i),"Fit result "+str(i),900,700)
can.append(canv)
Z1_fitFunction = TF1('Z1_fitFunction',"[0]*TMath::Landau(x,[1],[2])",0,4)
Z1_fitFunction.SetParameters(100,0.1,1.0)
#Z1_fitFunction.SetParLimits(0,85.,95.)
#Z1_fitFunction.SetParLimits(1,0.,5.)
#Z1_fitFunction.SetParLimits(2,0.,2.)
Z1_fitFunction.SetParName(0,"Const")#constant
Z1_fitFunction.SetParName(1,"Position")#position
Z1_fitFunction.SetParName(2,"Scale")#scale
for i in range(0,len(histo)):
can[i].cd()
histo[i].Fit(Z1_fitFunction,"","",0.,2.)
histo[i].Draw()
gStyle.SetOptFit()
position = Z1_fitFunction.GetParameters()[1]
scale = Z1_fitFunction.GetParameters()[2]
position_err = Z1_fitFunction.GetParError(1)
scale_err = Z1_fitFunction.GetParError(2)
result.append(Result(position,scale,lumi[i],position_err,scale_err))
print ("Position: " +str(position) + " Scale: " + str(scale))
printLumiPrelOut(can[i])
can[i].SaveAs("FitResults/"+title+"_Landfit_"+str(i)+".pdf")
can[i].SaveAs("FitResults/"+title+"_Landfit_"+str(i)+".png")
return result;
def DoRooFit(histo, title):
can = makeCMSCanvas(str(random.random()),"Fit result ",900,700)
#Varible
if "ele" in title:
x1 = RooRealVar("x1","m_{e^{+}e^{-}}",80,100)
if "mu" in title:
x1 = RooRealVar("x1","m_{#mu^{+}#mu^{-}}",80,100)
#Define CB function
m = RooRealVar("mean_{CB}","mean of gaussian",60,120)
s = RooRealVar("#sigma_{CB}","width of gaussian",0,3)
a = RooRealVar("#alpha_{CB}","mean of gaussian",0,100)
n = RooRealVar("n_{CB}","width of gaussian",0,5)
CB = RooCBShape("CB","CB PDF",x1, m, s, a, n)
m.setConstant(kFALSE)
s.setConstant(kFALSE)
a.setConstant(kFALSE)
n.setConstant(kFALSE)
#Define Gaussian function
mean1 = RooRealVar("mean_{G}","mean of gaussian",-60,60)
sigma1 = RooRealVar("#sigma_{G}","width of gaussian",0,10)
gauss1 = RooGaussian("gauss1","gaussian PDF",x1,mean1,sigma1)
mean1.setConstant(kFALSE)
sigma1.setConstant(kFALSE)
#Starting values of the parameters
mean1.setVal(1.0)
sigma1.setVal(1.0)
m.setVal(90.0)
s.setVal(1.0)
a.setVal(10.0)
n.setVal(2.0)
# Construct CB (x) gauss
x1.setBins(10000, "cache")
CBxG = RooFFTConvPdf("CBxG", "CB (X) gauss", x1, CB, gauss1)
can.cd()
d = RooDataHist("d","d",RooArgList(x1),RooFit.Import(histo))
CBxG.fitTo(d, RooLinkedList())
# Plot PDF and toy data overlaid
xframe2 = x1.frame(RooFit.Name("xframe"),RooFit.Title("")) # RooPlot
d.plotOn(xframe2, RooLinkedList() )
CBxG.paramOn(xframe2, RooFit.Layout(0.65,0.99,0.9))
xframe2.getAttText().SetTextSize(0.03)
CBxG.plotOn(xframe2)
xframe2.Draw()
can.SaveAs("DataVsMC/FitResults/"+title+"_Roofit.pdf")
can.SaveAs("DataVsMC/FitResults/"+title+"_Roofit.png")
return;
def GraphVsLumi(result, outputDir, title):
#gSystem.Exec("mkdir -p ZPlots")
can1 = makeCMSCanvas(str(random.random()), "mean vs lumi ", 900, 700)
can2 = makeCMSCanvas(str(random.random()), "width vs lumi ", 900, 700)
lumi = []
lumi_err = []
mean = []
mean_err = []
width = []
width_err = []
sumLumi = 0.
for i in range(0, len(result)):
sumLumi += float(result[i].lumi)
lumi.append(sumLumi - float(result[i].lumi) / 2)
lumi_err.append(float(result[i].lumi) / 2)
mean.append(result[i].mean)
mean_err.append(result[i].mean_err)
width.append(result[i].width)
width_err.append(result[i].width_err)
graph1 = TGraphErrors(len(result), array('d', lumi), array('d', mean),
array('d', lumi_err), array('d', mean_err))
graph2 = TGraphErrors(len(result), array('d', lumi), array('d', width),
array('d', lumi_err), array('d', width_err))
can1.cd()
graph1.SetTitle("")
graph1.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph1.GetYaxis().SetTitle("Mass [GeV]")
graph1.SetMarkerStyle(20)
graph1.SetMarkerSize(1)
graph1.Draw("AP")
printLumiPrelOut(can1)
can1.SaveAs(str(outputDir) + "/" + title + "_mean.pdf")
can1.SaveAs(str(outputDir) + "/" + title + "_mean.png")
can2.cd()
graph2.SetTitle("")
graph2.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph2.GetYaxis().SetTitle("Width [GeV]")
graph2.SetMarkerStyle(20)
graph2.SetMarkerSize(1)
graph2.Draw("AP")
printLumiPrelOut(can2)
can2.SaveAs(str(outputDir) + "/" + title + "_width.pdf")
can2.SaveAs(str(outputDir) + "/" + title + "_width.png")
return graph1, graph2
def MeanRMSVsLumi(histo, recorded, outputDir, title):
can1 = makeCMSCanvas(str(random.random()), "mean vs lumi ", 900, 700)
can2 = makeCMSCanvas(str(random.random()), "RMS vs lumi ", 900, 700)
lumi = []
lumi_err = []
mean = []
mean_err = []
RMS = []
RMS_err = []
sumLumi = 0.
for i in range(0, len(recorded)):
sumLumi += float(recorded[i])
lumi.append(sumLumi - float(recorded[i]) / 2)
lumi_err.append(float(recorded[i]) / 2)
mean.append(histo[i].GetMean())
mean_err.append(0.) #dont put error on ISO and SIP histo[i].GetRMS()
RMS.append(histo[i].GetRMS())
RMS_err.append(0.)
graph1 = TGraphErrors(len(recorded), array('d', lumi), array('d', mean),
array('d', lumi_err), array('d', mean_err))
graph2 = TGraphErrors(len(recorded), array('d', lumi), array('d', RMS),
array('d', lumi_err), array('d', RMS_err))
can1.cd()
graph1.SetTitle("")
graph1.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph1.GetYaxis().SetTitle(" ")
graph1.SetMarkerStyle(20)
graph1.SetMarkerSize(1)
graph1.Draw("AP")
printLumiPrelOut(can1)
can1.SaveAs(str(outputDir) + "/" + title + "_mean.pdf")
can1.SaveAs(str(outputDir) + "/" + title + "_mean.png")
can2.cd()
graph2.SetTitle("")
graph2.GetXaxis().SetTitle(" ")
graph2.GetYaxis().SetTitle("Width [GeV]")
graph2.SetMarkerStyle(20)
graph2.SetMarkerSize(1)
graph2.Draw("AP")
printLumiPrelOut(can2)
can2.SaveAs(str(outputDir) + "/" + title + "_width.pdf")
can2.SaveAs(str(outputDir) + "/" + title + "_width.png")
return graph1, graph2
def PlotNpv(inputTXT, lumiInp):
canvas = makeCMSCanvas(str(random.random()),"Npv",900,700)
canvas.Divide(1,2)
canvas.cd(2)
Npv = []
error = []
lumi = []
lumi_err = []
noerr = []
with open(inputTXT, "r") as Inp:
print("Opening " + inputTXT + ".")
for line in Inp:
cleared_line = line.split(" ")
Npv.append(float(cleared_line[0]))
error.append(float(cleared_line[1]))
sumLumi = 0
for i in range(0,len(lumiInp)):
sumLumi += float(lumiInp[i])
lumi.append(sumLumi - float(lumiInp[i])/2)
lumi_err.append(float(lumiInp[i])/2)
noerr.append(0.)
graph1 = TGraphErrors(len(lumiInp),array('d',lumi),array('d',Npv),array('d',lumi_err),array('d',error))
graph2 = TGraphErrors(len(lumiInp),array('d',lumi),array('d',Npv),array('d',lumi_err),array('d',noerr))
graph1.SetTitle("")
graph1.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph1.GetXaxis().SetLimits(0.,40.)
graph1.GetYaxis().SetTitle("Npv")
graph1.SetMarkerStyle(20)
graph1.SetMarkerSize(1)
graph1.Draw("AP")
canvas.cd(1)
graph2.SetTitle("")
graph2.GetXaxis().SetTitle("Lumi [fb^{-1}]")
graph2.GetXaxis().SetLimits(0.,35.)
graph2.GetYaxis().SetTitle("Npv")
graph2.SetMarkerStyle(20)
graph2.SetMarkerSize(1)
graph2.Draw("AP")
canvas.Update()
canvas.cd(2)
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.57,down,5.57, up)
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.58,down,8.58,up)
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.9,down,12.9,up)
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.57,down,16.57,up)
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.7,down,19.7,up)
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(26.9,down,26.9,up)
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
canvas.SaveAs("Npv.pdf")
return;
def TwoFileSAME2VsLumi(F1graph1, F1graph2, F2graph1, F2graph2, title, type):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
F1graph1.SetMarkerColor(kBlue)#electrons
F1graph2.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerColor(kBlue)#electrons
F2graph2.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerStyle(kOpenStar)
F2graph2.SetMarkerStyle(kOpenStar)
multigraph = TMultiGraph()
multigraph.Add(F1graph1,"AP")
multigraph.Add(F1graph2,"AP")
multigraph.Add(F2graph1,"AP")
multigraph.Add(F2graph2,"AP")
multigraph.Draw("AP")
multigraph.GetXaxis().SetLimits(0.,40.)
#TGaxis.SetMaxDigits(2)
#TGaxis.SetExponentOffset(-0.06, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(type == "ISO"):
multigraph.GetYaxis().SetTitle("Isolation")
gPad.Modified()
multigraph.SetMinimum(0.5*gPad.GetUymin())
multigraph.SetMaximum(1.5*gPad.GetUymax())
elif(type == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
printLumiPrelOut(canvas)
canvas.Update()
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.57,down,5.57, up)
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.58,down,8.58,up)
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.9,down,12.9,up)
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.57,down,16.57,up)
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.7,down,19.7,up)
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(26.9,down,26.9,up)
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
legend = TLegend(0.80,0.75,0.965,0.93)
legend.AddEntry(F1graph1,"e^{+}e^{-}","P")
legend.AddEntry(F1graph2,"#mu^{+}#mu^{-}","P")
legend.AddEntry(F2graph1,"e^{+}e^{-} ICHEP","P")
legend.AddEntry(F2graph2,"#mu^{+}#mu^{-} ICHEP","P")
legend.SetTextFont(32)
legend.Draw()
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def TwoFileSAME3VsLumi(F1graph1, F1graph2, F1graph3, F2graph1, F2graph2, F2graph3, title, type, DoInclusive):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
F1graph1.SetMarkerColor(kBlack)#electrons
F1graph2.SetMarkerColor(kBlue)#electrons
F1graph3.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerColor(kBlack)#electrons
F2graph2.SetMarkerColor(kBlue)#electrons
F2graph3.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerStyle(kOpenStar)#inclusive
F2graph2.SetMarkerStyle(kOpenStar)#electrons
F2graph3.SetMarkerStyle(kOpenStar)#muons
multigraph = TMultiGraph()
if(DoInclusive or type == "ZmassBARELL" or type == "ZwidthBARELL" or type == "ZmultBARELL"):
multigraph.Add(F1graph1,"AP")
multigraph.Add(F2graph1,"AP")
multigraph.Add(F1graph2,"AP")
multigraph.Add(F1graph3,"AP")
multigraph.Add(F2graph2,"AP")
multigraph.Add(F2graph3,"AP")
multigraph.Draw("AP")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetXaxis().SetLimits(0.,40.)
multigraph.GetYaxis().SetTitleOffset(1.4)
gPad.Modified()
if(type == "Zmass" or type == "ZmassBARELL"):
multigraph.SetMaximum(1.008*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("M_{l^{+}l^{-}} [GeV]")
elif(type == "Zwidth" or type == "ZwidthBARELL"):
multigraph.SetMaximum(1.1*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("#Gamma [GeV]")
elif(type == "Zmult" or type == "ZmultBARELL"):
multigraph.SetMaximum(1.2*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("#Z")
elif(type == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
multigraph.SetMaximum(1.1*gPad.GetUymax())
printLumiPrelOut(canvas)
canvas.Update()
down = gPad.GetUymin()
up = gPad.GetUymax()
MC_muMass = 90.92
MC_eleMass = 90.63
Data_muMass = 90.95
Data_eleMass = 90.68
lineB = TLine(5.57,down,5.57, up)
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.58,down,8.58,up)
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.9,down,12.9,up)
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.57,down,16.57,up)
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.7,down,19.7,up)
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(26.9,down,26.9,up)
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
if(type == "Zmass"):
lineMC_ele = TLine(0.,MC_eleMass,40., MC_eleMass)
lineMC_ele.SetLineColor(kBlue)
lineMC_ele.SetLineStyle(1)
lineMC_ele.Draw()
lineMC_mu = TLine(0.,MC_muMass,40., MC_muMass)
lineMC_mu.SetLineColor(kRed)
lineMC_mu.SetLineStyle(1)
lineMC_mu.Draw()
lineData_ele = TLine(0.,Data_eleMass,40., Data_eleMass)
lineData_ele.SetLineColor(kBlue)
lineData_ele.SetLineStyle(2)
lineData_ele.Draw()
lineData_mu = TLine(0.,Data_muMass,40., Data_muMass)
lineData_mu.SetLineColor(kRed)
lineData_mu.SetLineStyle(2)
lineData_mu.Draw()
legend = TLegend(0.80,0.75,0.965,0.93)
if(type == "Zmass" or type == "Zwidth" or type == "Zmult"):
legend.AddEntry(F1graph2,"e^{+}e^{-}","P")
legend.AddEntry(F1graph3,"#mu^{+}#mu^{-}","P")
legend.AddEntry(F2graph2,"e^{+}e^{-} ICHEP","P")
legend.AddEntry(F2graph3,"#mu^{+}#mu^{-} ICHEP","P")
else:
legend.AddEntry(F1graph1,"EBEB","P")
legend.AddEntry(F2graph1,"EBEB ICHEP","P")
legend.AddEntry(F1graph2,"EBEE","P")
legend.AddEntry(F1graph3,"EEEE","P")
legend.AddEntry(F2graph2,"EBEE ICHEP","P")
legend.AddEntry(F2graph3,"EEEE ICHEP","P")
legend.SetTextFont(32)
legend.Draw()
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def SAME2VsLumi(g1, g2,title, ptype, dataPeriod):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
graph1=copy.deepcopy(g1)
graph2=copy.deepcopy(g2)
graph1.SetMarkerColor(kBlue)#electrons
graph2.SetMarkerColor(kRed)#muons
multigraph = TMultiGraph()
multigraph.Add(graph1,"AP")
multigraph.Add(graph2,"AP")
multigraph.Draw("AP")
TGaxis.SetMaxDigits(2)
TGaxis.SetExponentOffset(-0.06, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(ptype == "ISO"):
multigraph.GetYaxis().SetTitle("Isolation")
gPad.Modified()
multigraph.SetMinimum(0.5*gPad.GetUymin())
multigraph.SetMaximum(1.5*gPad.GetUymax())
elif(ptype == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
multigraph.SetMinimum(min(multigraph.GetHistogram().GetMinimum(),1.))
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMinimum(),2.2))
min(multigraph.GetHistogram().GetMinimum(),1.)
printLumiPrelOut(canvas)
# Draw legend
legend = TLegend(0.93,0.84,0.99,0.93)
legend.AddEntry(graph1,"e^{+}e^{-}","P")
legend.AddEntry(graph2,"#mu^{+}#mu^{-}","P")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(20)
legend.Draw()
canvas.Update()
# Draw letters for data-taking periods
if(dataPeriod == "data2017"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(2., 0.8*gPad.GetUymax(),"B")
textLetters.DrawLatex(9.5, 0.8*gPad.GetUymax(),"C")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(),"D")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(),"E")
textLetters.DrawLatex(36., 0.8*gPad.GetUymax(),"F")
elif(ptype == "SIP"):
textLetters.DrawLatex(2., 1.5,"B")
textLetters.DrawLatex(9.5, 1.5,"C")
textLetters.DrawLatex(16., 1.5,"D")
textLetters.DrawLatex(23., 1.5,"E")
textLetters.DrawLatex(36., 1.5,"F")
if(dataPeriod == "data2018"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(6., 0.8*gPad.GetUymax(), "A")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(), "B")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(), "C")
textLetters.DrawLatex(43., 0.8*gPad.GetUymax(), "D")
elif(ptype == "SIP"):
textLetters.DrawLatex(6., 1.5, "A")
textLetters.DrawLatex(16., 1.5, "B")
textLetters.DrawLatex(23., 1.5, "C")
textLetters.DrawLatex(43., 1.5, "D")
# ****
if(dataPeriod == "data2018"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineA = TLine(13.48, down, 13.48, up) # Run2018A up to 13.48 fb-1
lineA.SetLineColor(kBlack)
lineA.SetLineStyle(2)
lineA.Draw()
lineB = TLine(20.265, down, 20.265, up) # Run2018B up to 20.265 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(26.877, down, 26.877, up) # Run2018C up to 26.877 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
# ****
if(dataPeriod == "data2017"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(4.793, down, 4.793, up) # Run2017B up to 4.793 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(14.549, down, 14.549, up) # Run2017C up to 14.549 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(18.868, down, 18.868, up) # Run2017D up to 18.868 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(28.293, down, 28.293, up) # Run2017E up to 28.293 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
# ****
if(dataPeriod == "data2016"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.789, down, 5.789, up) # Run2016B up to 5.789 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.366, down, 8.366, up) # Run2016C up to 8.366 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.616, down, 12.616, up) # Run2016D up to 12.616 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.624, down, 16.624, up) # Run2016E up to 16.624 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.725, down, 19.725, up) # Run2016F up to 19.725 fb-1
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(27.268, down, 27.268, up) # Run2016G up to 27.268 fb-1
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
# ****
canvas.SaveAs(title + ".root")
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def SAME3VsLumi(g1, g2, g3, title, ptype, lineMC1, lineDATA1, lineMC2, lineDATA2, lineMC3, lineDATA3, DoInclusive, dataPeriod):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
graph2=copy.deepcopy(g2)
graph3=copy.deepcopy(g3)
graph2.SetMarkerColor(kBlue)#electrons
graph3.SetMarkerColor(kRed)#muons
multigraph = TMultiGraph()
if(DoInclusive):
graph1=copy.deepcopy(g1)
multigraph.Add(graph1,"AP")
multigraph.Add(graph2,"AP")
multigraph.Add(graph3,"AP")
multigraph.Draw("AP")
TGaxis.SetMaxDigits(2)
TGaxis.SetExponentOffset(-0.05, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(ptype == "Zmass"):
multigraph.GetYaxis().SetTitle("M_{Z} [GeV]")
# multigraph.GetYaxis().SetTitle("M_{l^{+}l^{-}} [GeV]")
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMaximum(),91.4))
multigraph.SetMinimum(min(multigraph.GetHistogram().GetMinimum(),89.6))
elif(ptype == "Zwidth"):
multigraph.GetYaxis().SetTitle("#Gamma_{Z} [GeV]")
elif(ptype == "Zmult"):
multigraph.GetYaxis().SetTitle("#Z / fb^{-1}")
if(not DoInclusive) :
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMaximum(),60000.)) # set y axis minimum at 60000.
multigraph.SetMinimum(0.) # set y axis minimum at 0.
# multigraph.SetMaximum(60000.) #second type: vs 2016 plots
# multigraph.SetMinimum(25000.)
printLumiPrelOut(canvas)
# Draw legend
legend = TLegend(0.93,0.84,0.99,0.93)
if(DoInclusive):
#legend.AddEntry(graph1,"inclusive","P")
legend.AddEntry(graph1,"BB","P")
legend.AddEntry(graph2,"BE","P")
legend.AddEntry(graph3,"EE","P")
else :
legend.AddEntry(graph2,"e^{+}e^{-}","P")
legend.AddEntry(graph3,"#mu^{+}#mu^{-}","P")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(20)
legend.Draw()
canvas.Update()
# Draw letters for data-taking periods
if(dataPeriod == "data2017"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "Zmass"):
textLetters.DrawLatex(2., gPad.GetUymin()+0.2,"B")
textLetters.DrawLatex(9.5, gPad.GetUymin()+0.2,"C")
textLetters.DrawLatex(16., gPad.GetUymin()+0.2,"D")
textLetters.DrawLatex(23., gPad.GetUymin()+0.2,"E")
textLetters.DrawLatex(36., gPad.GetUymin()+0.2,"F")
elif(ptype == "Zwidth"):
textLetters.DrawLatex(2., gPad.GetUymin()+0.3,"B")
textLetters.DrawLatex(9.5, gPad.GetUymin()+0.3,"C")
textLetters.DrawLatex(16., gPad.GetUymin()+0.3,"D")
textLetters.DrawLatex(23., gPad.GetUymin()+0.3,"E")
textLetters.DrawLatex(36., gPad.GetUymin()+0.3,"F")
elif(ptype == "Zmult") :
textLetters.DrawLatex(2., 260000,"B")
textLetters.DrawLatex(9.5, 260000,"C")
textLetters.DrawLatex(16., 260000,"D")
textLetters.DrawLatex(23., 260000,"E")
textLetters.DrawLatex(36., 260000,"F")
if(dataPeriod == "data2018"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "Zmass"):
textLetters.DrawLatex(6., gPad.GetUymin() + 0.6,"A")
textLetters.DrawLatex(16., gPad.GetUymin() + 0.6,"B")
textLetters.DrawLatex(23., gPad.GetUymin() + 0.6,"C")
textLetters.DrawLatex(43., gPad.GetUymin() + 0.6,"D")
elif(ptype == "Zwidth"):
textLetters.DrawLatex(6., gPad.GetUymin() +0.3,"A")
textLetters.DrawLatex(16., gPad.GetUymin() +0.3,"B")
textLetters.DrawLatex(23., gPad.GetUymin() +0.3,"C")
textLetters.DrawLatex(43., gPad.GetUymin() +0.3,"D")
elif(ptype == "Zmult") :
textLetters.DrawLatex(6., 260000,"A")
textLetters.DrawLatex(16., 260000,"B")
textLetters.DrawLatex(23., 260000,"C")
textLetters.DrawLatex(43., 260000,"D")
# ****
if(dataPeriod == "data2018"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineA = TLine(13.48, down, 13.48, up) # Run2018A up to 13.48 fb-1
lineA.SetLineColor(kBlack)
lineA.SetLineStyle(2)
lineA.Draw()
lineB = TLine(20.265, down, 20.265, up) # Run2018B up to 20.265 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(26.877, down, 26.877, up) # Run2018C up to 26.877 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
if(dataPeriod == "data2017"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(4.793, down, 4.793, up) # Run2017B up to 4.793 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(14.549, down, 14.549, up) # Run2017C up to 14.549 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(18.868, down, 18.868, up) # Run2017D up to 18.868 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(28.293, down, 28.293, up) # Run2017E up to 28.293 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
if(dataPeriod == "data2016"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.789, down, 5.789, up) # Run2016B up to 5.789 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.366, down, 8.366, up) # Run2016C up to 8.366 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.616, down, 12.616, up) # Run2016D up to 12.616 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.624, down, 16.624, up) # Run2016E up to 16.624 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.725, down, 19.725, up) # Run2016F up to 19.725 fb-1
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(27.268, down, 27.268, up) # Run2016G up to 27.268 fb-1
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
# ****
# draw orizontal lines for MC and DATA fit
if(ptype == "Zmass" or ptype == "Zwidth") :
leftEnd = gPad.GetUxmin()
rightEnd = gPad.GetUxmax()
if(DoInclusive):
line1 = TLine(leftEnd,lineMC1,rightEnd,lineMC1)
line1.SetLineColor(kBlack)
line1.SetLineStyle(1)
line1.Draw()
line2 = TLine(leftEnd,lineDATA1,rightEnd,lineDATA1)
line2.SetLineColor(kBlack)
line2.SetLineStyle(2)
line2.Draw()
# line for graph 2: color blue
line3 = TLine(leftEnd,lineMC2,rightEnd,lineMC2)
line3.SetLineColor(kBlue)
line3.SetLineStyle(1)
line3.Draw()
line4 = TLine(leftEnd,lineDATA2,rightEnd,lineDATA2)
line4.SetLineColor(kBlue)
line4.SetLineStyle(2)
line4.Draw()
# line for graph 3: color red
line5 = TLine(leftEnd,lineMC3,rightEnd,lineMC3)
line5.SetLineColor(kRed)
line5.SetLineStyle(1)
line5.Draw()
line6 = TLine(leftEnd,lineDATA3,rightEnd,lineDATA3)
line6.SetLineColor(kRed)
line6.SetLineStyle(2)
line6.Draw()
# ***
canvas.SaveAs(title + ".root")
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def DoDCBunbinnedFit(histo, lumi, ZZtree, outputDir, title, fitMC, fitDATA): #fitMC = true for fitting MC in FitMC.py, fitDATA = true for fitting data in FitDATA.py
# create canvas list
can = []
datahist = []
massplot = []
result = []
for i in range(0,len(histo)):
canv = makeCMSCanvas(str(random.random())+str(i),"Fit result "+str(i),900,700)
can.append(canv)
# variable
if "ele" in title:
x1_zmass = RooRealVar("x1_zmass","m_{e^{+}e^{-}}",60,120)
if "mu" in title:
x1_zmass = RooRealVar("x1_zmass","m_{#mu^{+}#mu^{-}}",60,120)
# define fit function (DCB)
meanDCB = RooRealVar("mean_{DCB}", "mean of DCB", 60.,120. )
sigmaDCB = RooRealVar("#sigma_{DCB}", "width of DCB", 0., 6. )
alphaDCB = RooRealVar("#alpha_{DCB}", "alpha of DCB", 0., 100. )
nDCB = RooRealVar("n_{DCB}", "n of DCB", 0., 10. )
alpha2DCB = RooRealVar("#alpha2_{DCB}", "alpha2 of DCB", 0., 100. )
n2DCB = RooRealVar("n2_{DCB}", "n2 of DCB", 0., 10. )
DCB_function = DoubleCB( x1_zmass, meanDCB, sigmaDCB, alphaDCB, nDCB, alpha2DCB, n2DCB)
# do the fit and plot
for i in range(0,len(histo)):
datahist[i] = RooDataHist("data","data",RooArgList(x1_zmass),RooFit.Import(histo))
DCB_function.fitTo(datahist[i],ROOT.RooFit.Extended(1)) #do the fit
massplot[i] = x1_zmass.frame()
datahist[i].plotOn(massplot[i])
DCB_function.plotOn(massplot[i])
DCB_function.paramOn(massplot[i], RooFit.Layout(0.65,0.99,0.9))
can[i].cd()
gStyle.SetOptFit()
massplot[i].Draw()
mass = meanDCB.getVal()
width = sigmaDCB.getVal()
mass_err = 0. #to check
width_err = 0. #to check
result.append(Result(mass,width,lumi[i],mass_err,width_err))
print ("Mass: " +str(mass) + " Width: " + str(width))
printLumiPrelOut(can[i])
if(fitMC) :
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.pdf")
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.png")
elif(fitDATA) :
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.pdf")
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.png")
else :
can[i].SaveAs(str(outputDir) + "/"+ title +"_fit_"+str(i)+".pdf")
can[i].SaveAs(str(outputDir) + "/"+ title +"_fit_"+str(i)+".png")
return result;
def DoSimpleFit(histo, lumi, ZZtree, outputDir, title, fitMC, fitDATA): #fitMC = true for fitting MC in FitMC.py, fitDATA = true for fitting data in FitDATA.py
can = []
result = []
for i in range(0,len(histo)):
canv = makeCMSCanvas(str(random.random())+str(i),"Fit result "+str(i),900,700)
can.append(canv)
Z1_fitFunction = TF1(str(random.random()),DoubleCB(),60. ,120., 7)
Z1_fitFunction.SetParLimits(0,80.,100.)#mean
Z1_fitFunction.SetParLimits(1,0.,5.)#width
Z1_fitFunction.SetParLimits(2,0.,2.)#alpha1
Z1_fitFunction.SetParLimits(3,0.,10.)#n1
Z1_fitFunction.SetParLimits(4,0.,2.)#alpha2
Z1_fitFunction.SetParLimits(5,0.,10.)#n2
# Z1_fitFunction.SetParLimits(6,0.,1000000.)#const
Z1_fitFunction.SetParName(0,"Mean")#mean
Z1_fitFunction.SetParName(1,"Sigma")#width
Z1_fitFunction.SetParName(2,"#alpha_{1}")#alpha1
Z1_fitFunction.SetParName(3,"n_{1}")#n1
Z1_fitFunction.SetParName(4,"#alpha_{2}")#alpha2
Z1_fitFunction.SetParName(5,"n_{2}")#n2
Z1_fitFunction.SetParName(6,"C")#const
for i in range(0,len(histo)):
# print "***", histo[i].GetTitle(), lumi[i], title, histo[i].GetEntries(), "***"
# define fit function
if(fitMC) : # fit function for fitting MC in FitMC.py
Z1_fitFunction.SetParameters(91.,2.5,1.,1.,1.,1.,histo[i].Integral()/5.)
elif(fitDATA): # fit function for fitting DATA in FitDATA.py
Z1_fitFunction.SetParameters(91.,2.5,1.,1.,1.,1.,histo[i].Integral()/5.)
else :
if(ZZtree) :
Z1_fitFunction.SetParameters(91.,2.5,1.,1.,1.,1.,10.)
else:
Z1_fitFunction.SetParameters(91.,2.5,1.,1.,1.,1.,histo[i].Integral()/5.)
# do the fit
can[i].cd()
histo[i].Fit(Z1_fitFunction) # do the fit
histo[i].Draw("E")
gStyle.SetOptFit()
mass = Z1_fitFunction.GetParameters()[0]
width = Z1_fitFunction.GetParameters()[1]
mass_err = Z1_fitFunction.GetParError(0)
width_err = Z1_fitFunction.GetParError(1)
result.append(Result(mass,width,lumi[i],mass_err,width_err))
print ("Mass: " +str(mass) + " Width: " + str(width))
printLumiPrelOut(can[i])
if(fitMC) :
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.pdf")
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.png")
elif(fitDATA) :
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.pdf")
can[i].SaveAs(str(outputDir) + "/"+ str(title[i]) +"_fit.png")
else :
can[i].SaveAs(str(outputDir) + "/"+ title +"_fit_"+str(i)+".pdf")
can[i].SaveAs(str(outputDir) + "/"+ title +"_fit_"+str(i)+".png")
return result;
