def legend4Plot(plot, left = False):
if left:
theLeg = TLegend(0.2, 0.62, 0.55, 0.92, "", "NDC")
else:
theLeg = TLegend(0.60, 0.62, 0.92, 0.92, "", "NDC")
theLeg.SetName('theLegend')
theLeg.SetBorderSize(0)
theLeg.SetLineColor(0)
theLeg.SetFillColor(0)
theLeg.SetFillStyle(0)
theLeg.SetLineWidth(0)
theLeg.SetLineStyle(0)
theLeg.SetTextFont(42)
theLeg.SetTextSize(.045)
entryCnt = 0
for obj in range(0, int(plot.numItems())):
objName = plot.nameOf(obj)
if (not plot.getInvisible(objName)):
theObj = plot.getObject(obj)
objTitle = theObj.GetTitle()
if len(objTitle) < 1:
objTitle = objName
dopts = plot.getDrawOptions(objName).Data()
# print 'obj:',theObj,'title:',objTitle,'opts:',dopts,'type:',type(dopts)
if theObj.IsA().InheritsFrom('TNamed'):
theLeg.AddEntry(theObj, objTitle, dopts)
entryCnt += 1
theLeg.SetY1NDC(0.9 - 0.05*entryCnt - 0.005)
theLeg.SetY1(theLeg.GetY1NDC())
return theLeg
def compareShapes(histograms=[], histogramlables=[], styles=[], maxfactor = 1.3):
leg = TLegend(0.6, 0.7, 0.94, 0.92);
leg.SetBorderSize(0);
leg.SetLineStyle(0);
leg.SetTextFont(42);
leg.SetFillStyle(0);
AddLegendEntry = leg.AddEntry
c = TCanvas("compareShapes", 'compareShapes', defaultCanvasWidth, defaultCanvasHeight)
c.cd()
for hist, label, style in zip(histograms,histogramlables,styles):
hist.Sumw2()
hist = normalise(hist)
hist.SetLineColor(style['color'])
hist.SetLineWidth(4)
AddLegendEntry(hist, label, "f")
index = 0
maximum = getMax(histograms)
for hist in histograms:
if index == 0:
hist.GetYaxis().SetRangeUser(0, maximum*maxfactor)
hist.Draw('histe')
else:
hist.Draw('histe same')
index += 1
return c, leg
def create_legend(x0=0.696, y0 = 0.95, x1=0.94, y1=0.55):
# legend = TLegend(0.6, 0.7, 0.94, 0.92);
legend = TLegend(x0, y0, x1, y1)
legend.SetBorderSize(0);
legend.SetLineStyle(0);
legend.SetTextFont(42);
legend.SetFillStyle(0);
return legend
def getLegend():
legend = TLegend(0.55010112, 0.7183362, 0.70202143, 0.919833)
legend.SetTextSize(0.032)
legend.SetLineColor(0)
legend.SetShadowColor(0)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetMargin(0.35)
return legend
def getLegend(x1=0.70010112,y1=0.123362,x2=0.90202143,y2=0.279833): legend = TLegend(x1,y1,x2,y2) legend.SetTextSize(0.032) legend.SetLineColor(0) legend.SetShadowColor(0) legend.SetLineStyle(1) legend.SetLineWidth(1) legend.SetFillColor(0) legend.SetFillStyle(0) legend.SetMargin(0.35) return legend
def legend(title=''):
lg = TLegend(0.65, 0.55, 0.95, 0.90, title)
lg.SetFillColor(0)
lg.SetFillStyle(0)
lg.SetLineColor(0)
lg.SetLineStyle(0)
lg.SetBorderSize(0)
lg.SetShadowColor(0)
lg.SetTextFont(42)
lg.SetTextSize(0.06)
return lg
def myLegend(coordinate=[0.48, 0.55, 0.97, 0.87], ncol=1):
co = coordinate
leg = TLegend(co[0], co[1], co[2], co[3])
leg.SetNColumns(ncol)
leg.SetBorderSize(0)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.035)
return leg
def SetLegend(coordinate_=[.15, .7, .47, .87], ncol=1):
c_ = coordinate_
legend = TLegend(c_[0], c_[1], c_[2], c_[3])
legend.SetBorderSize(0)
legend.SetNColumns(ncol)
legend.SetLineColor(1)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.05)
return legend
def loadlegend(top, bottom, left, right): relPosX = 0.001 relPosY = 0.005 posX = 1 - right - relPosX*(1-left-right) posY = 1 - top - relPosY*(1-top-bottom) legendOffsetX = 0.0 legendOffsetY = - 0.05 textSize = 0.05 textFont = 60 legendSizeX = 0.4 legendSizeY = 0.2 legend = TLegend(posX-legendSizeX+legendOffsetX,posY-legendSizeY+legendOffsetY,posX+legendOffsetX,posY+legendOffsetY) legend.SetTextSize(textSize) legend.SetLineStyle(0) legend.SetBorderSize(0) return legend
pad1.SetBorderSize(0)
pad1.SetFrameBorderSize(0)
pad2.SetBorderSize(0)
pad2.SetFrameBorderSize(0)
pad2.SetBottomMargin(0.3)
pad2.SetBorderMode(0)
pad1.Draw()
pad2.Draw()
pad1.cd()
legend_years = TLegend(0.15, 0.7, 0.3, 0.95)
legend_years.SetHeader(" ")
legend_years.SetFillColor(0)
legend_years.SetBorderSize(0)
legend_years.SetLineColor(1)
legend_years.SetLineStyle(1)
legend_years.SetLineWidth(1)
legend_years.SetFillStyle(0)
legend_years.SetTextSize(0.03)
legend_years.AddEntry(h_signal_2016, "2016", "lep")
legend_years.AddEntry(h_signal_2017, "2017", "lep")
legend_years.AddEntry(h_signal_2018, "2018", "lep")
scaling_factor_2016_2018 = (h_signal_2018.Integral()) / (
h_signal_2016.Integral())
scaling_factor_2017_2018 = (h_signal_2018.Integral()) / (
h_signal_2017.Integral())
h_signal_2016.Scale(scaling_factor_2016_2018)
h_signal_2016.SetMarkerStyle(20)
h_signal_2016.SetMarkerColor(3)
h_signal_2017.Scale(scaling_factor_2017_2018)
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
#gStyle.SetTitleOffset(1.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
minimum = []
## Legend
leg = TLegend(0.1, 0.80, 0.89, 0.89) #,NULL,"brNDC");
leg.SetBorderSize(0)
leg.SetNColumns(3)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
c.SetBottomMargin(0.15)
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
#print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
#histList[ii].Scale(1.0/histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
minimum.append(histList[ii].GetMinimum())
maximum.sort()
ii = ii + 1
print histList
print maximum, " ", max(maximum)
print minimum, " ", min(minimum)
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(1.5) #1.4 for log
histList[ih].SetMinimum(0.1) #1.4 for log
if logstatus[1] is 0:
maxi = max(maximum)
mini = min(minimum)
if maxi == 0.0: maxi = 0.001
if mini == 0.0: mini = -0.001
histList[ih].SetMaximum(maxi * 3) #1.4 for log
histList[ih].SetMinimum(mini * 3) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("P hist")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("P hist same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(100)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(2)
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetMarkerStyle(20)
histList[ih].SetMarkerSize(1.0)
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "P")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(0.98)
histList[ih].GetYaxis().SetTitleFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
# histList[ih].GetXaxis().SetLabelSize(0.0000);
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
#histList[ih].GetXaxis().SetTitleOffset(1.14)
histList[ih].GetXaxis().SetTitleFont(42)
histList[ih].GetXaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetXaxis().SetNdivisions(507)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
i = i + 1
pt = TPaveText(0.01, 0.92, 0.95, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.046)
#text = pt.AddText(0.12,0.35,"CMS Internal 36 fb^{-1} (2016) ")
text = pt.AddText(0.12, 0.35,
"CMS Internal 41.5 fb^{-1} (2017) ")
#text = pt.AddText(0.12,0.35,"CMS Internal 59.6 fb^{-1} (2018) ")
#text = pt.AddText(0.6,0.5,"41.5 fb^{-1} (2017) ")
pt.Draw()
leg.Draw()
outputdirname = 'UncPlots/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
def makeBiasPlot(output,
muFile,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
mu = open(muFile, 'r')
limits = {}
mux = []
muy = []
mu1SigLow = []
mu1SigHigh = []
mu2SigLow = []
mu2SigHigh = []
for entry in mu:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
mux.append(massPoint)
print massPoint, limits[massPoint][medianNr]
muy.append(limits[massPoint][medianNr])
mu1SigLow.append(limits[massPoint][lower1Sig])
mu1SigHigh.append(limits[massPoint][upper1Sig])
mu2SigLow.append(limits[massPoint][lower2Sig])
mu2SigHigh.append(limits[massPoint][upper2Sig])
muX = numpy.array(mux)
muY = numpy.array(muy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of mux: ", len(mux)
if printStats: print "length of mu1SigLow: ", len(mu1SigLow)
if printStats: print "length of mu1SigHigh: ", len(mu1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(mux)):
values2.append(mu2SigLow[x])
xPointsForValues2.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values2.append(mu2SigHigh[x])
xPointsForValues2.append(mux[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(mux)):
values.append(mu1SigLow[x])
xPointsForValues.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values.append(mu1SigHigh[x])
xPointsForValues.append(mux[x])
if printStats: print "length of values: ", len(values)
mu2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
mu1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "mu2Sig: ", mu2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "mu1Sig: ", mu1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, mu2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, mu1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
muX = numpy.array(mux)
muY = numpy.array(muy)
GraphMU = TGraph(len(muX), muX, muY)
GraphMU.SetLineWidth(3)
GraphMU.SetLineStyle(2)
GraphMU.SetLineColor(ROOT.kBlue)
#Draw the graphs:
DummyGraph = TH1F("DummyGraph", "", 100, 10, 40)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
DummyGraph.GetYaxis().SetTitle("#hat{#mu}")
gStyle.SetOptStat(0)
if "Des" in output:
DummyGraph.GetXaxis().SetRangeUser(10, 28)
else:
DummyGraph.GetXaxis().SetRangeUser(10, 40)
DummyGraph.SetMinimum(-2)
DummyGraph.SetMaximum(10)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
DummyGraph.SetLineColor(ROOT.kWhite)
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphMU.Draw("lpsame")
else:
GraphMU.Draw("lp")
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
leg.AddEntry(GraphMU, "median value", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "1#sigma quantile", "f")
leg.AddEntry(GraphErr2Sig, "2#sigma quantile", "f")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
maxX = 40
if "Des" in output:
maxX = 28
line = ROOT.TLine(10, 0, maxX, 0)
if "mu1" in output:
line = ROOT.TLine(10, 1, maxX, 1)
line.SetLineStyle(ROOT.kDashed)
line.Draw("same")
plotPad.RedrawAxis()
cCL.Update()
printPlots(cCL, output)
def makeLimitPlot(output,
obs,
exp,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
xSecs = getFittedXSecCurve("CI_%s" % interference, 1.3)
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
xSecCurves = []
xSecCurves.append(getFittedXSecCurve("CI_%s" % interference, 1.3))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 10, 46)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#mu#mu +X) [pb]"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrowee +X) [pb]")
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#font[12]{ll}) [pb]"
)
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(10, 46)
DummyGraph.SetMinimum(5e-4)
DummyGraph.SetMaximum(1)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
print curve.Eval(28)
#curve.Draw()
curve.Draw("sameR")
plCMS = TPaveLabel(.15, .81, .25, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.15, .76, .275, .82, "Supplementary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
#plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.440517, 0.523051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Observed 95%% CL limit" % ratioLabels[1],
"l")
leg.AddEntry(GraphObs2, "%s Observed 95%% CL limit" % ratioLabels[0],
"l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg.AddEntry(xSecCurves[0], labels[interference], "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
elif "2017" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"42.1 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee) + 42.1 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
def drawPlots(plots, plotopts, rootopts, output, optzero, optmean, opth, optw):
from ROOT import TPostScript, TCanvas, TLegend
from ROOT import gROOT, gStyle, gPad
gROOT.Reset()
gROOT.SetStyle("Plain")
gStyle.SetOptStat(0)
gStyle.SetPalette(1)
leg = TLegend(0.54, 0.71, 0.9, 0.9)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(10)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
if output != "DISPLAY":
ps = TPostScript(output, 111)
ps.NewPage()
canv = TCanvas('c1', "Validation Plot Viewer", 600, 800)
canv.Divide(opth, optw)
maxperlist = opth * optw
#current pad
num = 0
#for stupid drawing system
legends = []
#drawing hists
for plotopt in plotopts:
print "Drawing", plotopt.display_name
num += 1
if (num > maxperlist
and output != "DISPLAY"): #end of a current PS page
ps.NewPage()
print "new page"
num = 1
canv.cd(num)
gPad.SetLogy(plotopt.logy)
leg.Clear()
entries = {}
valuemax = -999999.9
valuemin = 999999.9
entryZ = 0
for rootopt in rootopts: #get the max entries
entries[rootopt] = plots[plotopt][rootopt].GetEntries()
if (plots[plotopt][rootopt].GetEntries() > entryZ):
entryZ = plots[plotopt][rootopt].GetEntries()
for rootopt in rootopts: #get the max entries
plot = plots[plotopt][rootopt]
if (plotopt.profile):
print rootopt.legendname, "is a profile: no need to scale"
else:
if not (entries[rootopt] == 0):
print "scaling", rootopt.legendname, "to", entryZ / entries[
rootopt]
plot.Scale(entryZ / entries[rootopt])
else:
print rootopt.legendname, "is an empty hist, no scale"
for rootopt in rootopts: #get the highest peak
if (plots[plotopt][rootopt].GetMaximum() > valuemax):
valuemax = plots[plotopt][rootopt].GetMaximum()
entryZ = plots[plotopt][rootopt].GetEntries()
sameDrawOpt = ""
#now we plot all fillers, as otherwise they will render invisible everything behind them
for rootopt in rootopts:
if (rootopt.markerstyle > 0): #not filler
continue
plot = plots[plotopt][rootopt]
print "Drawing filler from", rootopt.legendname
if optzero:
if (plotopt.logy == 1):
plot.SetMinimum(1.0)
else:
plot.SetMinimum(0.0)
plot.SetMaximum(valuemax * 1.1)
plot.GetXaxis().SetTitle(
plotopt.axis_captions[plotopt.vars_to_draw[0].lstrip("+")])
if len(plotopt.vars_to_draw) > 1:
plot.GetYaxis().SetTitle(
plotopt.axis_captions[plotopt.vars_to_draw[1].lstrip("+")])
if (plotopt.i2d):
plot.Draw("CONT4Z " + sameDrawOpt)
else:
plot.Draw(rootopt.drawopt + sameDrawOpt)
sameDrawOpt = " SAME"
#plot the rest & fill the legend in the normal order
for rootopt in rootopts:
plot = plots[plotopt][rootopt]
prname = rootopt.legendname
if optmean and (not plotopt.profile):
prname += " (mean: " + ("%.4f" % plot.GetMean()) + ")"
leg.AddEntry(plot, prname, "L")
if (rootopt.markerstyle == 0): #filler
continue #fillers are already drawn
print "Drawing plot from", rootopt.legendname
if optzero:
if (plotopt.logy == 1):
plot.SetMinimum(1.0)
else:
plot.SetMinimum(0.0)
plot.SetMaximum(valuemax * 1.1)
plot.GetXaxis().SetTitle(
plotopt.axis_captions[plotopt.vars_to_draw[0].lstrip("+")])
if len(plotopt.vars_to_draw) > 1:
plot.GetYaxis().SetTitle(
plotopt.axis_captions[plotopt.vars_to_draw[1].lstrip("+")])
if (plotopt.i2d):
plot.Draw("CONT4Z " + sameDrawOpt)
else:
plot.Draw(rootopt.drawopt + sameDrawOpt)
sameDrawOpt = " SAME"
if not plotopt.i2d:
legends.append(leg.Clone())
legends[len(legends) - 1].Draw()
canv.Update()
if output != "DISPLAY":
canv.Close()
ps.Close()
return canv, legends
def train_and_apply():
np.random.seed(1)
ROOT.gROOT.SetBatch()
#Extract data from root file
tree = uproot.open("out_all.root")["outA/Tevts"]
branch_mc = [
"MC_B_P", "MC_B_eta", "MC_B_phi", "MC_B_pt", "MC_D0_P", "MC_D0_eta",
"MC_D0_phi", "MC_D0_pt", "MC_Dst_P", "MC_Dst_eta", "MC_Dst_phi",
"MC_Dst_pt", "MC_Est_mu", "MC_M2_miss", "MC_mu_P", "MC_mu_eta",
"MC_mu_phi", "MC_mu_pt", "MC_pis_P", "MC_pis_eta", "MC_pis_phi",
"MC_pis_pt", "MC_q2"
]
branch_rec = [
"B_P", "B_eta", "B_phi", "B_pt", "D0_P", "D0_eta", "D0_phi", "D0_pt",
"Dst_P", "Dst_eta", "Dst_phi", "Dst_pt", "Est_mu", "M2_miss", "mu_P",
"mu_eta", "mu_phi", "mu_pt", "pis_P", "pis_eta", "pis_phi", "pis_pt",
"q2"
]
nvariable = len(branch_mc)
x_train = tree.array(branch_mc[0], entrystop=options.maxevents)
for i in range(1, nvariable):
x_train = np.vstack(
(x_train, tree.array(branch_mc[i], entrystop=options.maxevents)))
x_test = tree.array(branch_rec[0], entrystop=options.maxevents)
for i in range(1, nvariable):
x_test = np.vstack(
(x_test, tree.array(branch_rec[i], entrystop=options.maxevents)))
x_train = x_train.T
x_test = x_test.T
x_test = array2D_float(x_test)
#Different type of reconstruction variables
#BN normalization
gamma = 0
beta = 0.2
ar = np.array(x_train)
a = K.constant(ar[:, 0])
mean = K.mean(a)
var = K.var(a)
x_train = K.eval(K.batch_normalization(a, mean, var, gamma, beta))
for i in range(1, nvariable):
a = K.constant(ar[:, i])
mean = K.mean(a)
var = K.var(a)
a = K.eval(K.batch_normalization(a, mean, var, gamma, beta))
x_train = np.vstack((x_train, a))
x_train = x_train.T
ar = np.array(x_test)
a = K.constant(ar[:, 0])
mean = K.mean(a)
var = K.var(a)
x_test = K.eval(K.batch_normalization(a, mean, var, gamma, beta))
for i in range(1, nvariable):
a = K.constant(ar[:, i])
mean = K.mean(a)
var = K.var(a)
a = K.eval(K.batch_normalization(a, mean, var, gamma, beta))
x_test = np.vstack((x_test, a))
x_test = x_test.T
#Add noise, remain to be improved
noise = np.random.normal(loc=0.0, scale=0.01, size=x_train.shape)
x_train_noisy = x_train + noise
noise = np.random.normal(loc=0.0, scale=0.01, size=x_test.shape)
x_test_noisy = x_test + noise
x_train = np.clip(x_train, -1., 1.)
x_test = np.clip(x_test, -1., 1.)
x_train_noisy = np.clip(x_train_noisy, -1., 1.)
x_test_noisy = np.clip(x_test_noisy, -1., 1.)
# Network parameters
input_shape = (x_train.shape[1], )
batch_size = 128
latent_dim = 2
# Build the Autoencoder Model
# First build the Encoder Model
inputs = Input(shape=input_shape, name='encoder_input')
x = inputs
# Shape info needed to build Decoder Model
shape = K.int_shape(x)
# Generate the latent vector
latent = Dense(latent_dim, name='latent_vector')(x)
# Instantiate Encoder Model
encoder = Model(inputs, latent, name='encoder')
encoder.summary()
# Build the Decoder Model
latent_inputs = Input(shape=(latent_dim, ), name='decoder_input')
x = Dense(shape[1])(latent_inputs)
x = Reshape((shape[1], ))(x)
outputs = Activation('tanh', name='decoder_output')(x)
# Instantiate Decoder Model
decoder = Model(latent_inputs, outputs, name='decoder')
decoder.summary()
# Autoencoder = Encoder + Decoder
# Instantiate Autoencoder Model
autoencoder = Model(inputs, decoder(encoder(inputs)), name='autoencoder')
autoencoder.summary()
autoencoder.compile(loss='mse', optimizer='adam')
# Train the autoencoder
autoencoder.fit(x_train_noisy,
x_train,
validation_data=(x_test_noisy, x_test),
epochs=options.epochs,
batch_size=batch_size)
# Predict the Autoencoder output from corrupted test imformation
x_decoded = autoencoder.predict(x_test_noisy)
# Draw Comparision Plots
c = TCanvas("c", "c", 700, 700)
fPads1 = TPad("pad1", "Run2", 0.0, 0.29, 1.00, 1.00)
fPads2 = TPad("pad2", "", 0.00, 0.00, 1.00, 0.29)
fPads1.SetBottomMargin(0.007)
fPads1.SetLeftMargin(0.10)
fPads1.SetRightMargin(0.03)
fPads2.SetLeftMargin(0.10)
fPads2.SetRightMargin(0.03)
fPads2.SetBottomMargin(0.25)
fPads1.Draw()
fPads2.Draw()
fPads1.cd()
nbin = 50
min = -1.
max = 1.
variable = "P^{B}"
lbin = (max - min) / nbin
lbin = str(float((max - min) / nbin))
xtitle = branch_rec[options.branch - 1]
ytitle = "Events/" + lbin + "GeV"
h_rec = TH1D("h_rec", "" + ";%s;%s" % (xtitle, ytitle), nbin, min, max)
h_rec.Sumw2()
h_pre = TH1D("h_pre", "" + ";%s;%s" % (xtitle, ytitle), nbin, min, max)
h_pre.Sumw2()
for i in range(x_test_noisy.shape[0]):
h_rec.Fill(x_test_noisy[i][options.branch - 1])
h_pre.Fill(x_decoded[i][options.branch - 1])
h_rec = UnderOverFlow1D(h_rec)
h_pre = UnderOverFlow1D(h_pre)
maxY = TMath.Max(h_rec.GetMaximum(), h_pre.GetMaximum())
h_rec.SetLineColor(2)
h_rec.SetFillStyle(0)
h_rec.SetLineWidth(2)
h_rec.SetLineStyle(1)
h_pre.SetLineColor(3)
h_pre.SetFillStyle(0)
h_pre.SetLineWidth(2)
h_pre.SetLineStyle(1)
h_rec.SetStats(0)
h_pre.SetStats(0)
h_rec.GetYaxis().SetRangeUser(0, maxY * 1.1)
h_rec.Draw("HIST")
h_pre.Draw("same HIST")
h_rec.GetYaxis().SetTitleSize(0.06)
h_rec.GetYaxis().SetTitleOffset(0.78)
theLeg = TLegend(0.5, 0.45, 0.95, 0.82, "", "NDC")
theLeg.SetName("theLegend")
theLeg.SetBorderSize(0)
theLeg.SetLineColor(0)
theLeg.SetFillColor(0)
theLeg.SetFillStyle(0)
theLeg.SetLineWidth(0)
theLeg.SetLineStyle(0)
theLeg.SetTextFont(42)
theLeg.SetTextSize(.05)
theLeg.AddEntry(h_rec, "Reconstruction", "L")
theLeg.AddEntry(h_pre, "Prediction", "L")
theLeg.SetY1NDC(0.9 - 0.05 * 6 - 0.005)
theLeg.SetY1(theLeg.GetY1NDC())
fPads1.cd()
theLeg.Draw()
title = TLatex(
0.91, 0.93, "AE prediction compare with reconstruction, epochs=" +
str(options.epochs))
title.SetNDC()
title.SetTextSize(0.05)
title.SetTextFont(42)
title.SetTextAlign(31)
title.SetLineWidth(2)
title.Draw()
fPads2.cd()
h_Ratio = h_pre.Clone("h_Ratio")
h_Ratio.Divide(h_rec)
h_Ratio.SetLineColor(1)
h_Ratio.SetLineWidth(2)
h_Ratio.SetMarkerStyle(8)
h_Ratio.SetMarkerSize(0.7)
h_Ratio.GetYaxis().SetRangeUser(0, 2)
h_Ratio.GetYaxis().SetNdivisions(504, 0)
h_Ratio.GetYaxis().SetTitle("Pre/Rec")
h_Ratio.GetYaxis().SetTitleOffset(0.35)
h_Ratio.GetYaxis().SetTitleSize(0.13)
h_Ratio.GetYaxis().SetTitleSize(0.13)
h_Ratio.GetYaxis().SetLabelSize(0.11)
h_Ratio.GetXaxis().SetLabelSize(0.1)
h_Ratio.GetXaxis().SetTitleOffset(0.8)
h_Ratio.GetXaxis().SetTitleSize(0.14)
h_Ratio.SetStats(0)
axis1 = TGaxis(min, 1, max, 1, 0, 0, 0, "L")
axis1.SetLineColor(1)
axis1.SetLineWidth(1)
for i in range(1, h_Ratio.GetNbinsX() + 1, 1):
D = h_rec.GetBinContent(i)
eD = h_rec.GetBinError(i)
if D == 0: eD = 0.92
B = h_pre.GetBinContent(i)
eB = h_pre.GetBinError(i)
if B < 0.1 and eB >= B:
eB = 0.92
Err = 0.
if B != 0.:
Err = TMath.Sqrt((eD * eD) / (B * B) + (D * D * eB * eB) /
(B * B * B * B))
h_Ratio.SetBinContent(i, D / B)
h_Ratio.SetBinError(i, Err)
if B == 0.:
Err = TMath.Sqrt((eD * eD) / (eB * eB) + (D * D * eB * eB) /
(eB * eB * eB * eB))
h_Ratio.SetBinContent(i, D / 0.92)
h_Ratio.SetBinError(i, Err)
if D == 0 and B == 0:
h_Ratio.SetBinContent(i, -1)
h_Ratio.SetBinError(i, 0)
h_Ratio.Draw("e0")
axis1.Draw()
c.SaveAs(branch_rec[options.branch - 1] + "_comparision.png")
wjets_color = ROOT.TColor.GetColor(0.717, 0.815, 0.749)
zvv_color = (kAzure + 3)
syst_color = ROOT.TColor.GetColor(0.960, 0.925, 0.6)
color = [
qcd_color, vh_color, diboson_color, singletop_color, ttbar_color,
zll_color, wjets_color, zvv_color
]
print color
legend = TLegend(0.65, 0.7, 0.92, 0.89)
legend.SetTextSize(0.046)
legend.SetBorderSize(0)
legend.SetLineColor(1)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetNColumns(2)
i = 0
for iprocess in processes:
hist_met_ = fin.Get('h_summary_' + iprocess)
hist_met_.Sumw2()
hist_met_.SetDirectory(0)
TH1.AddDirectory(0)
# gStyle.SetPalette(53)
hist_met_.SetFillColor(color[i])
#hist_met_.SetLineColor(color[i])
bkgStack.Add(hist_met_, 'hist')
def makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
smoother = TGraphSmooth("normal")
smoother2 = TGraphSmooth("normal")
zprimeX = []
zprimeY = []
fileZPrime = open('tools/xsec_SSM.txt', 'r')
for entries in fileZPrime:
entry = entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1]) * 1.3 / 1928)
zpX = numpy.array(zprimeX)
zpY = numpy.array(zprimeY)
GraphZPrime = TGraph(481, zpX, zpY)
GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX = []
zprimePsiY = []
fileZPrimePsi = open('tools/xsec_PSI.txt', 'r')
for entries in fileZPrimePsi:
entry = entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1]) * 1.3 / 1928)
zpPsiX = numpy.array(zprimePsiX)
zpPsiY = numpy.array(zprimePsiY)
GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY)
GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
if "Moriond" in output:
DummyGraph = TH1F("DummyGraph", "", 100, 120, 4500)
else:
DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)"
)
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)"
)
gStyle.SetOptStat(0)
if "Moriond" in output:
DummyGraph.GetXaxis().SetRangeUser(120, 4500)
else:
DummyGraph.GetXaxis().SetRangeUser(400, 4500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(4e-4)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
if not SPIN2:
GraphZPrimeSmooth.Draw("lsame")
GraphZPrimePsiSmooth.Draw("lsame")
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
leg.AddEntry(GraphObs, "% Observed 95% CL limit" % ratioLabel[1], "l")
leg.AddEntry(GraphObs2, "%s Observed 95% CL limit" % ratioLabel[0],
"l")
else:
leg.AddEntry(GraphObs, "Observed 95% CL limit", "l")
leg.AddEntry(GraphExp, "Expected 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Expected 95% CL limit, 1 s.d.", "f")
leg.AddEntry(GraphErr2Sig, "Expected 95% CL limit, 2 s.d.", "f")
leg1 = TLegend(0.665517, 0.483051, 0.834885, 0.623051, "", "brNDC")
leg1.SetTextSize(0.032)
if not SPIN2:
leg1.AddEntry(GraphZPrimePsiSmooth, "Z'_{#Psi} (LOx1.3)", "l")
leg1.AddEntry(GraphZPrimeSmooth, "Z'_{SSM} (LOx1.3)", "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(400, 1, 4500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(400, 0.9, 4500, 1.1, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
if drawObs:
graph_limit_vs_mass__obs_limit.Draw("Lsame")
graph_limit_vs_mass__exp_limit.Draw("Lsame")
graph_limit_vs_mass__Th_limit.Draw("Lsame")
drawCMS3(myC, 13, lumi_this)
leg_limit_vs_mass_ = TLegend(0.38, 0.66, 0.81, 0.92)
leg_limit_vs_mass_.SetHeader(label_this +
", c#tau_{#tilde{#chi}_{1}^{0}} = " +
ctau_this_str + " cm")
leg_limit_vs_mass_.SetBorderSize(0)
leg_limit_vs_mass_.SetTextSize(0.03)
leg_limit_vs_mass_.SetLineColor(1)
leg_limit_vs_mass_.SetLineStyle(1)
leg_limit_vs_mass_.SetLineWidth(1)
leg_limit_vs_mass_.SetFillColor(0)
leg_limit_vs_mass_.SetFillStyle(1001)
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__Th_limit,
"Theoretical cross section", "L")
if drawObs:
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__obs_limit,
"Observed 95% CL upper limit", "L")
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__exp_limit,
"Expected 95% CL upper limit", "L")
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__exp1sigma_limit,
"#pm 1 #sigma Expected", "F")
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__exp2sigma_limit,
"#pm 2 #sigma Expected", "F")
def compare(name,
file_list,
name_list,
legend_list,
normalize=False,
drawoption='hE',
xtitle='',
ytitle='',
minx=0,
maxx=0,
rebin=1,
miny=0,
maxy=0,
textsizefactor=1,
logy=False,
fit='',
fitlow=0,
fithigh=0,
colors=[]):
c = TCanvas(name, '', 600, 600)
c.SetLeftMargin(0.15) #
c.SetRightMargin(0.05) #
c.SetBottomMargin(0.11)
c.SetTopMargin(0.25)
legend = TLegend(0.0, 0.76, 0.99, 1.04)
legend.SetHeader('')
#legend.SetTextSize(0.03)
legend.SetBorderSize(0)
legend.SetTextFont(42)
legend.SetLineColor(1)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
histo_list = []
# tfile_list=[]
the_maxy = 0
widths = []
for i in range(len(name_list)):
# tfile_list.append(TFile(file_list[i],'READ'))
histo_list.append(file_list[i].Get(name_list[i]).Clone(name_list[i] +
'_' + str(i)))
#print(histo_list)
print(legend_list[i], histo_list[-1].Integral())
if normalize:
histo_list[-1].Scale(1.0 /
(histo_list[-1].Integral() + 0.00000001))
if not histo_list[-1].ClassName() == 'TGraphAsymmErrors':
histo_list[-1].SetStats(0)
histo_list[-1].SetLineWidth(3)
if colors == []:
histo_list[-1].SetLineColor(i + 1)
if i > 6:
histo_list[-1].SetLineColor(i + 4)
else:
histo_list[-1].SetLineColor(colors[i])
histo_list[-1].SetTitle('')
if rebin != 1:
histo_list[-1].Rebin(rebin)
if not histo_list[-1].ClassName() == 'TGraphAsymmErrors':
the_maxy = max(
the_maxy,
histo_list[-1].GetBinContent(histo_list[-1].GetMaximumBin()) *
1.05)
if fit != '':
if fitlow == 0 and fithigh == 0:
histo_list[-1].Fit(fit)
else:
histo_list[-1].Fit(fit, '', '', fitlow[i], fithigh[i])
histo_list[-1].GetFunction("gaus").SetLineColor(i + 1)
gaus = histo_list[-1].GetFunction("gaus")
print(i, gaus.GetParameter(0), gaus.GetParameter(1),
gaus.GetParameter(2))
widths.append(gaus.GetParameter(2))
if fit == '':
legend.AddEntry(histo_list[-1], legend_list[i], 'l')
else:
legend.AddEntry(
histo_list[-1],
legend_list[i] + ' FWHM=' + "%.2f [GeV]" % (2.354 * widths[i]),
'l')
for i in range(len(name_list)):
if i == 0:
if not histo_list[-1].ClassName() == 'TGraphAsymmErrors':
if miny != 0 or maxy != 0:
histo_list[i].SetMaximum(maxy)
histo_list[i].SetMinimum(miny)
else:
histo_list[i].SetMaximum(the_maxy)
histo_list[i].SetMinimum(0.0001)
else:
histo_list[i].SetMaximum(1.05)
histo_list[i].SetMinimum(0.0001)
histo_list[i].Draw(drawoption)
charsize = 0.05 * textsizefactor
histo_list[i].GetYaxis().SetLabelSize(charsize)
histo_list[i].GetYaxis().SetTitleSize(charsize)
histo_list[i].GetYaxis().SetTitleOffset(1.6)
histo_list[i].GetXaxis().SetLabelSize(charsize)
histo_list[i].GetXaxis().SetTitleSize(charsize)
histo_list[i].GetXaxis().SetTitleOffset(0.95)
# if useOutfile:
if xtitle != '':
histo_list[i].GetXaxis().SetTitle(xtitle)
if ytitle != '':
histo_list[i].GetYaxis().SetTitle(ytitle)
if maxx != 0 or minx != 0:
histo_list[i].GetXaxis().SetRangeUser(minx, maxx)
# histo_list[i].GetYaxis().SetTitle('Efficiency')
else:
if histo_list[-1].ClassName() == 'TGraphAsymmErrors':
drawoption = drawoption.replace("A", "")
histo_list[i].Draw(drawoption + 'SAME')
if logy:
c.SetLogy()
legend.Draw()
# outfile.cd()
#c.Write(name)
c.SaveAs('pdf/' + name + '.pdf')
def makeLimitPlot(output,obs,exp,chan,printStats=False):
fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE")
obsLimits = {}
for obsFile in obs:
if 'width' in obsFile:
width = obsFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
obsLimits[width] = createObsGraph(obsFile)
if SMOOTH:
for width,obsGraph in obsLimits.iteritems():
smooth_obs=TGraphSmooth("normal")
GraphObs_nonSmooth=obsGraph
obsLimits[width]=copy.deepcopy(smooth_obs.SmoothSuper(GraphObs_nonSmooth,"linear",0,0.005))
obsLimits[width].SetLineWidth(3)
expLimits = {}
for expFile in exp:
if 'width' in expFile:
width = expFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
expLimits[width] = createExpGraph(expFile)
cCL=TCanvas("cCL", "cCL",0,0,600,450)
gStyle.SetOptStat(0)
gStyle.SetPadRightMargin(0.063)
gStyle.SetPadLeftMargin(0.14)
gStyle.SetPadBottomMargin(0.12)
plotPad = ROOT.TPad("plotPad","plotPad",0,0,1,1)
plotPad.Draw()
plotPad.cd()
smoother=TGraphSmooth("normal")
smoother2=TGraphSmooth("normal")
zprimeX=[]
zprimeY=[]
fileZPrime=open('tools/xsec_ssm.txt','r')
for entries in fileZPrime:
entry=entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1])/1928)
zpX=numpy.array(zprimeX)
zpY=numpy.array(zprimeY)
GraphZPrime=TGraph(len(zprimeX),zpX,zpY)
GraphZPrimeSmooth=smoother2.SmoothSuper(GraphZPrime,"linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen+3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX=[]
zprimePsiY=[]
fileZPrimePsi=open('tools/xsec_psi.txt','r')
for entries in fileZPrimePsi:
entry=entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1])/1928)
zpPsiX=numpy.array(zprimePsiX)
zpPsiY=numpy.array(zprimePsiY)
GraphZPrimePsi=TGraph(len(zprimePsiX),zpPsiX,zpPsiY)
GraphZPrimePsiSmooth=smoother.SmoothSuper(GraphZPrimePsi,"linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
DummyGraph=TH1F("DummyGraph","",100,200,5500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if SPIN2:
DummyGraph.GetYaxis().SetTitle("[#sigma#upoint#font[12]{B}] G_{KK} / #sigma#upoint#font[12]{B}] Z")
else:
DummyGraph.GetYaxis().SetTitle("[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z")
# if SPIN2:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
# else:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(200,5500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(3e-4)
DummyGraph.GetXaxis().SetLabelSize(0.055)
DummyGraph.GetXaxis().SetTitleSize(0.055)
DummyGraph.GetXaxis().SetTitleOffset(1.05)
DummyGraph.GetYaxis().SetLabelSize(0.055)
DummyGraph.GetYaxis().SetTitleSize(0.055)
DummyGraph.GetYaxis().SetTitleOffset(1.3)
DummyGraph.Draw()
plCMS=TPaveLabel(.16,.76,.27,.83,"CMS","NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim=TPaveLabel(.16,.76,.27,.82,"Preliminary","NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
# plPrelim.Draw()
leg=TLegend(0.420517,0.7,0.85,0.878644,"","brNDC")
legWidth=TLegend(0.625,0.5,0.9,0.7,"width","brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.0425)
legWidth.SetTextSize(0.0425)
colors = {'01':ROOT.kBlue,'03':ROOT.kRed,'05':ROOT.kGreen+3,'10':ROOT.kOrange}
# for width in sorted(obsLimits):
# obsGraph = obsLimits[width]
# if colors.has_key(width):
# obsGraph.SetLineColor(colors[width])
# obsGraph.Draw("lsame")
# if width == '0.006':
# leg.AddEntry(obsGraph,"Observed 95% CL limit width 0.6%","l")
# else:
# leg.AddEntry(obsGraph,"Observed 95%% CL limit width %d%%"%int(width),"l")
#
# for width in sorted(expLimits):
# expGraph = expLimits[width]
# if colors.has_key(width):
# expGraph.SetLineColor(colors[width])
# expGraph.Draw("lsame")
# if width == '0.006':
# leg.AddEntry(expGraph,"Expected 95% CL limit width 0.6%, median","l")
# else:
# leg.AddEntry(expGraph,"Expected 95%% CL limit width %d%%, median"%(int(width)),"l")
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
obsGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(obsGraph,"Obs. 95% CL limit","l")
for width in sorted(expLimits):
expGraph = expLimits[width]
if colors.has_key(width):
expGraph.SetLineColor(colors[width])
expGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(expGraph,"Exp. 95% CL limit, median","l")
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
if width == '0.006':
legWidth.AddEntry(obsGraph,"0.6%","l")
else:
legWidth.AddEntry(obsGraph,"%d%%"%int(width),"l")
if not SPIN2:
GraphZPrimeSmooth.Draw("lsame")
GraphZPrimePsiSmooth.Draw("lsame")
leg1=TLegend(0.625,0.35,0.825,0.5,"","brNDC")
leg1.SetTextSize(0.0375)
leg1.AddEntry(GraphZPrimeSmooth,"Z'_{SSM} (width 2.97%)","l")
leg1.AddEntry(GraphZPrimePsiSmooth,"Z'_{#Psi} (width 0.53%)","l")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetLineColor(0)
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#plCMS.Draw()
plotPad.SetTicks(1,1)
plotPad.RedrawAxis()
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
legWidth.SetLineWidth(0)
legWidth.SetLineStyle(0)
legWidth.SetLineColor(0)
legWidth.SetFillStyle(0)
legWidth.SetNColumns(2)
legWidth.Draw("hist")
if "Moriond" in output:
if (chan=="mumu"):
plLumi=TPaveLabel(.65,.885,.9,.99,"36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})","NBNDC")
elif (chan=="elel"):
plLumi=TPaveLabel(.65,.885,.9,.99,"35.9 fb^{-1} (13 TeV, ee)","NBNDC")
elif (chan=="elmu"):
plLumi=TPaveLabel(.27,.885,.9,.99,"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})","NBNDC")
else:
if (chan=="mumu"):
plLumi=TPaveLabel(.65,.905,.9,.99,"13.0 fb^{-1} (13 TeV, #mu#mu)","NBNDC")
elif (chan=="elel"):
plLumi=TPaveLabel(.65,.905,.9,.99,"2.7 fb^{-1} (13 TeV, ee)","NBNDC")
elif (chan=="elmu"):
plLumi=TPaveLabel(.4,.905,.9,.99,"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)","NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.RedrawAxis()
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
obsGraph.SetName("graphObs%s"%width)
obsGraph.Write("graphObs%s"%width)
for width in sorted(expLimits):
expGraph = expLimits[width]
expGraph.SetName("graphExp%s"%width)
expGraph.Write("graphExp%s"%width)
fileForHEPData.Write()
fileForHEPData.Close()
cCL.Update()
printPlots(cCL,output)
class plotTogether:
tfiles = {}
lgx = 0.65
lgy = 0.4
def __init__(self):
self.unctitle = ''
self.MCplots = []
self.DAplots = []
self.NOplots = []
self.Otherplots = []
self.DIVplots = []
self.Canvases = []
self.Pads = []
self.unc = False
ROOT.gStyle.SetOptFit(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTickX(0)
ROOT.gStyle.SetPadTickY(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTopMargin(0.05)
ROOT.gStyle.SetPadRightMargin(0.05)
ROOT.gStyle.SetPadBottomMargin(0.15)
ROOT.gStyle.SetPadLeftMargin(0.15)
ROOT.gStyle.SetLabelFont(43, "x")
ROOT.gStyle.SetLabelFont(43, "y")
ROOT.gStyle.SetLabelFont(43, "z")
ROOT.gStyle.SetLabelOffset(0.01, "x")
ROOT.gStyle.SetLabelOffset(0.01, "y")
ROOT.gStyle.SetLabelOffset(0.01, "z")
ROOT.gStyle.SetLabelSize(25, "x")
ROOT.gStyle.SetLabelSize(25, "y")
ROOT.gStyle.SetLabelSize(25, "z")
ROOT.gStyle.SetTitleFont(43, "x")
ROOT.gStyle.SetTitleFont(43, "y")
ROOT.gStyle.SetTitleFont(43, "z")
ROOT.gStyle.SetTitleOffset(1.2, "x")
ROOT.gStyle.SetTitleOffset(1.5, "y")
ROOT.gStyle.SetTitleOffset(1.1, "z")
ROOT.gStyle.SetTitleSize(30, "x")
ROOT.gStyle.SetTitleSize(30, "y")
ROOT.gStyle.SetTitleSize(30, "z")
def legend(self, legtitle):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
#self.lg = TLegend(0.55, 0.4, xpos-0.02, ypos-0.02)
self.lg = TLegend(self.lgx, self.lgy, xpos - 0.02, ypos - 0.02)
if len(legtitle) != 0:
self.lg.SetHeader(legtitle)
self.lg.SetFillColor(0)
self.lg.SetFillStyle(0)
self.lg.SetLineColor(0)
self.lg.SetLineStyle(0)
self.lg.SetBorderSize(0)
self.lg.SetShadowColor(0)
self.lg.SetTextFont(42)
self.lg.SetTextSize(0.07)
def printLatexYieldTable(self, fname='yield_table.tex'):
''' This function will print a table based on how the addMCplot and addDAplot functions were called.
It will sum over all files that have no title, and assing them to the previous title. So for example:
plot[p].addMCplot(DYfile, p, 'V+Jets', DYscale, ROOT.kGreen+2, projection = pro)
plot[p].addMCplot(Wfile, p, '', Wscale, ROOT.kGreen+2, projection = pro)
will create a category 'V+Jets' that includes DY and W+jets events stored in DYfile and Wfile.
A call to this function should be added just after a call to drawAddWithRatio for that particular histogram, and then, for example:
can = plot[p].drawAddWithRatio( .......
if (p == "RECO/all_njets"):
plot[p].printLatexYieldTable('totyield_table.tex'
'''
MCtot = 0.
MCtot_err = 0.
category_yield = []
category_err = []
category_title = []
cat_yield = 0.
cat_err = 0.
for index, hist in enumerate(self.MCplots):
if hist.GetTitle() != '':
category_title.append(hist.GetTitle())
cat_yield = 0.
cat_err = 0.
err = ROOT.Double(0)
# Make sure you run this over a histogram with known under- and overflows!
# For example number of jets, or MET, anything that hasn't been initialized to -9
events = hist.IntegralAndError(0, hist.GetNbinsX() + 1, err)
#events = hist.Integral()
cat_yield += events
cat_err = math.sqrt(cat_err * cat_err + err * err)
if len(self.MCplots
) == index + 1 or self.MCplots[index + 1].GetTitle() != '':
category_yield.append(cat_yield)
category_err.append(cat_err)
MCtot += events
MCtot_err = math.sqrt(MCtot_err * MCtot_err + err * err)
# Ready to print the numbers, first open the latex file:
latexfile = open(fname, "w")
latexfile.write(
"\\begin{tabular}{l|r@{$\\pm$}l} \\hline \n") # r@{$\pm$}l
latexfile.write("%-12s & %20s \\\\ \\hline \n" %
('Source', '\multicolumn{2}{c}{Yield}'))
for i in range(len(category_title)):
print "%-12s %5.1f +- %4.1f" % (category_title[i],
category_yield[i], category_err[i])
latexfile.write(
"%-12s & %5.1f & %4.1f \\\\ \n" %
(category_title[i], category_yield[i], category_err[i]))
print "%-12s %5.1f +- %4.1f" % ('BKG SUM ', MCtot, MCtot_err)
latexfile.write("%-12s & %5.1f & %4.1f\\\\ \\hline \n" %
('BKG SUM ', MCtot, MCtot_err))
DAtot = 0.
for hist in self.DAplots:
DAtot += hist.Integral()
print "%-12s %5i" % ('Data ', DAtot)
latexfile.write("%-12s & \multicolumn{2}{c}{%5i} \\\\ \n" %
('Data ', DAtot))
latexfile.write("\\end{tabular} \n")
latexfile.close()
print "Wrote LaTeX table with yields in: ", fname
print "The errors are obtained from ROOT::TH1::IntegralAndError() and added in quadrature per category"
return [DAtot, MCtot, MCtot_err]
def addMCplot(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
elif projection.startswith('Xbin:'):
bins = projection.split('Xbin:')[-1].split('-')
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX(
histpath.split('/')[-1] + '_myproX', int(bins[0]),
int(bins[1]))))
elif projection.startswith('Ybin:'):
bins = projection.split('Ybin:')[-1].split('-')
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX(
histpath.split('/')[-1] + '_myproY', int(bins[0]),
int(bins[1]))))
else:
self.MCplots.append(TH1D(self.tfiles[filename].Get(histpath)))
self.MCplots[-1].SetFillColor(color)
self.MCplots[-1].SetLineColor(color)
#self.MCplots[-1].Scale(scale, 'width')
self.MCplots[-1].Scale(scale)
self.MCplots[-1].SetTitle(title)
def setUncTitle(self, unctitle):
self.unctitle = unctitle
def addUncerHist(self, fcentral, ferrdown, ferrup, hist, projection=''):
if self.unc == False:
self.herr = TH1D(self.DAplots[-1])
self.herr.Reset()
self.herr.SetName('err')
self.unc = True
if fcentral not in self.tfiles:
self.tfiles[fcentral] = TFile(fcentral, 'read')
if ferrdown not in self.tfiles:
self.tfiles[ferrdown] = TFile(ferrdown, 'read')
if ferrup not in self.tfiles:
self.tfiles[ferrup] = TFile(ferrup, 'read')
hcen = self.tfiles[fcentral].Get(hist)
hdown = self.tfiles[ferrdown].Get(hist)
hup = self.tfiles[ferrup].Get(hist)
if projection == 'Y':
hcen = TH1D(hcen.ProjectionY())
hdown = TH1D(hdown.ProjectionY())
hup = TH1D(hup.ProjectionY())
if projection == 'X':
hcen = TH1D(hcen.ProjectionX())
hdown = TH1D(hdown.ProjectionX())
hup = TH1D(hup.ProjectionX())
elif projection.startswith('Xbin:'):
bins = projection.split('Xbin:')[-1].split('-')
hcen = TH1D(
hcen.ProjectionX(
hist.split('/')[-1] + '_myproX', int(bins[0]),
int(bins[1])))
hdown = TH1D(
hdown.ProjectionX(
hist.split('/')[-1] + '_myproX', int(bins[0]),
int(bins[1])))
hup = TH1D(
hup.ProjectionX(
hist.split('/')[-1] + '_myproX', int(bins[0]),
int(bins[1])))
elif projection.startswith('Ybin:'):
bins = projection.split('Ybin:')[-1].split('-')
hcen = TH1D(
hcen.ProjectionY(
hist.split('/')[-1] + '_myproY', int(bins[0]),
int(bins[1])))
hdown = TH1D(
hdown.ProjectionY(
hist.split('/')[-1] + '_myproY', int(bins[0]),
int(bins[1])))
hup = TH1D(
hup.ProjectionY(
hist.split('/')[-1] + '_myproY', int(bins[0]),
int(bins[1])))
for b in range(1, 1 + self.herr.GetNbinsX()):
cen = hcen.GetBinContent(b)
if cen == 0:
continue
up = hup.GetBinContent(b)
down = hdown.GetBinContent(b)
old = self.herr.GetBinContent(b)
errA = (up - cen) / cen
errB = (down - cen) / cen
err = math.sqrt((errA**2 + errB**2) / 2.)
#err = max(abs(errA), abs(errB))
self.herr.SetBinContent(b, math.sqrt(old**2 + err**2))
def addUncerVal(self, val):
if self.unc == False:
self.herr = TH1D(self.DAplots[-1])
self.herr.Reset()
self.herr.SetName('err')
self.unc = True
for b in range(1, 1 + self.herr.GetNbinsX()):
old = self.herr.GetBinContent(b)
self.herr.SetBinContent(b, math.sqrt(old**2 + val**2))
def addDAplot(self, filename, histpath, title, projection='', scale=1.):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
elif projection.startswith('Xbin:'):
bins = projection.split('Xbin:')[-1].split('-')
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX(
histpath.split('/')[-1] + '_myproX', int(bins[0]),
int(bins[1]))))
elif projection.startswith('Ybin:'):
bins = projection.split('Ybin:')[-1].split('-')
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX(
histpath.split('/')[-1] + '_myproY', int(bins[0]),
int(bins[1]))))
else:
self.DAplots.append(TH1D(self.tfiles[filename].Get(histpath)))
self.DAplots[-1].SetTitle(title)
self.DAplots[-1].Scale(scale)
#self.DAplots[-1].Scale(1., 'width')
self.DAplots[-1].Scale(1.)
def addOtherplot(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.Otherplots.append(TH1D(self.tfiles[filename].Get(histpath)))
#self.NOplots[-1].SetFillColor(color)
self.Otherplots[-1].SetLineColor(color)
self.Otherplots[-1].SetTitle(title)
self.Otherplots[-1].Scale(scale)
def addNormplot(self, filename, histpath, title, color, projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.NOplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.NOplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.NOplots.append(TH1D(self.tfiles[filename].Get(histpath)))
#self.NOplots[-1].SetFillColor(color)
self.NOplots[-1].SetLineColor(color)
self.NOplots[-1].SetTitle(title)
def drawAddWithRatio(self,
options='hist',
rebin=1,
legtitle='',
title='DEFAULT',
ratio=False,
rangemin=0.,
rangemax=0.,
printbinwidth=True,
xtitle='',
ytitle='',
logy=False,
xlabels=[]):
self.cumaddhist = []
self.cumaddhist.append(TH1D(self.MCplots[0]))
for hist in self.MCplots[1:]:
self.cumaddhist.append(TH1D(self.cumaddhist[-1]))
self.cumaddhist[-1].Add(hist)
self.cumaddhist[-1].SetFillColor(hist.GetFillColor())
self.cumaddhist[-1].SetLineColor(hist.GetLineColor())
self.cumaddhist[-1].SetTitle(hist.GetTitle())
totalevents = 0.
for hist in self.MCplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total MC events: ', totalevents
totalevents = 0.
for hist in self.DAplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total DA events: ', totalevents
mymax = 0.
self.Canvases.append(
TCanvas('CanvasAdd_' + self.cumaddhist[-1].GetName(),
'CanvasAdd_' + self.cumaddhist[-1].GetName(), 800, 600))
if ratio == True:
split = 0.3
spaceleft = 0.15
spaceright = 0.05
self.Pads.append(TPad("histpad", "histpad", 0, split, 1., 1.))
self.Pads[-1].SetTopMargin(0.05)
self.Pads[-1].SetBottomMargin(0.022)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Canvases[-1].cd()
self.Pads.append(TPad("divpad", "divpad", 0, 0, 1., split))
self.Pads[-1].SetTopMargin(0.0)
self.Pads[-1].SetBottomMargin(0.4)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Pads[-2].cd()
if len(title) > 0:
ROOT.gPad.SetTopMargin(0.1)
self.legend(legtitle)
if len(xlabels) != 0:
b = 0
for label in xlabels:
b += 1
self.cumaddhist[-1].GetXaxis().SetBinLabel(b, label)
if ratio == True:
self.cumaddhist[-1].GetXaxis().SetTitleOffset(5.)
self.cumaddhist[-1].GetXaxis().SetLabelOffset(5.)
for hist in reversed(self.cumaddhist):
hist.Rebin(rebin)
hist.Draw(options)
mymax = max(mymax, hist.GetMaximum())
if rangemin != 0 or rangemax != 0:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
if 'same' not in options:
if self.unc:
self.herr.Rebin(rebin)
self.herr.Scale(1. / rebin)
self.errprint = TH1D(hist)
self.errprint.SetName('errprint')
for b in range(1, self.errprint.GetNbinsX() + 1):
self.errprint.SetBinError(
b,
self.herr.GetBinContent(b) * hist.GetBinContent(b))
self.errprint.SetFillColor(1)
self.errprint.SetLineColor(1)
self.errprint.SetFillStyle(3354)
self.errprint.Draw('E2same')
units = re.findall('\[.*\]', hist.GetXaxis().GetTitle())
unit = ''
if len(units) == 1:
unit = units[0][1:-1]
if ytitle == '':
if len(hist.GetYaxis().GetTitle()) == 0:
ytitle = 'Events'
else:
ytitle = hist.GetYaxis().GetTitle()
#ytitle = ytitle.lower()
if printbinwidth == True:
hist.GetYaxis().SetTitle(
ytitle +
' / {0:g}'.format(hist.GetXaxis().GetBinWidth(1)) +
' ' + unit)
else:
hist.GetYaxis().SetTitle(ytitle)
if (xtitle != ''):
hist.GetXaxis().SetTitle(xtitle)
options += ' same'
for np in self.NOplots:
np.Rebin(rebin)
np.Scale(self.DAplots[0].Integral() / np.Integral())
np.SetLineWidth(2)
np.Draw('sameE0')
mymax = max(mymax, np.GetMaximum())
for op in self.Otherplots:
op.Rebin(rebin)
op.SetLineWidth(2)
op.Draw('sameE0')
mymax = max(mymax, op.GetMaximum())
if len(self.DAplots) == 1:
self.DAplots[0].Rebin(rebin)
self.DAplots[0].SetMarkerStyle(20)
self.DAplots[0].SetMarkerSize(1.1)
self.DAplots[0].SetLineWidth(2)
self.DAplots[0].Draw('E1X0same')
mymax = max(mymax, self.DAplots[0].GetMaximum())
if len(self.DAplots) == 1:
self.lg.AddEntry(self.DAplots[0], self.DAplots[0].GetTitle(), 'p')
for hist in reversed(self.cumaddhist):
if len(hist.GetTitle()) != 0:
self.lg.AddEntry(hist, hist.GetTitle(), 'f')
for np in self.NOplots:
self.lg.AddEntry(np, np.GetTitle() + ' (Scaled)', 'l')
for op in self.Otherplots:
self.lg.AddEntry(op, op.GetTitle(), 'l')
if len(self.unctitle) != 0:
self.lg.AddEntry(self.errprint, self.unctitle, 'f')
self.lg.Draw()
#self.settitle(title)
settitle(title)
setchannel()
cmstext()
if logy == False:
self.cumaddhist[-1].GetYaxis().SetRangeUser(0, mymax * 1.5)
if logy == True:
self.cumaddhist[-1].GetYaxis().SetRangeUser(10, mymax * 50)
self.Pads[-2].SetLogy(True)
self.Pads[-2].RedrawAxis()
if ratio == True:
self.Pads[-1].cd()
self.Pads[-1].SetGridy()
self.DIVplots.append(TH1D(self.DAplots[0]))
if (xtitle != ''):
self.DIVplots[-1].GetXaxis().SetTitle(xtitle)
self.DIVplots[-1].GetXaxis().SetTitle(
self.DIVplots[-1].GetXaxis().GetTitle().replace(
'additional', 'Additional'))
#self.DIVplots[-1].Divide(self.cumaddhist[-1])
for b in range(1, self.DIVplots[-1].GetNbinsX() + 1):
if (self.cumaddhist[-1].GetBinContent(b) > 0.):
divval = self.DIVplots[-1].GetBinContent(
b) / self.cumaddhist[-1].GetBinContent(b)
divvalerr = self.DIVplots[-1].GetBinError(
b) / self.cumaddhist[-1].GetBinContent(b)
self.DIVplots[-1].SetBinContent(b, divval)
#self.DIVplots[-1].SetBinError(b, divvalerr)
self.DIVplots[-1].SetBinError(
b,
math.sqrt(divvalerr**2 +
(self.cumaddhist[-1].GetBinError(b) /
self.cumaddhist[-1].GetBinContent(b))**2))
else:
self.DIVplots[-1].SetBinContent(b, 0.)
self.DIVplots[-1].SetBinError(b, 0.)
self.DIVplots[-1].SetMarkerSize(1.1)
if len(xlabels) != 0:
b = 0
for label in xlabels:
b += 1
self.DIVplots[-1].GetXaxis().SetBinLabel(b, label)
self.DIVplots[-1].Draw('E1X0same')
self.DIVplots[-1].GetXaxis().SetTitleOffset(3)
self.DIVplots[-1].GetYaxis().SetTitle('#frac{Data}{Simulation} ')
self.DIVplots[-1].GetYaxis().SetTitleOffset(1.3)
self.DIVplots[-1].GetYaxis().SetRangeUser(0.5, 1.5)
self.DIVplots[-1].GetYaxis().SetNdivisions(105)
if rangemin != 0 or rangemax != 0:
self.DIVplots[-1].GetXaxis().SetRangeUser(rangemin, rangemax)
if self.unc:
self.errprintratio = TH1D(self.herr)
for b in range(1, self.errprintratio.GetNbinsX() + 1):
self.errprintratio.SetBinError(b,
self.herr.GetBinContent(b))
self.errprintratio.SetBinContent(b, 1.)
self.errprintratio.SetFillColor(1)
self.errprintratio.SetFillStyle(3354)
self.errprintratio.Draw('E2same')
self.DIVplots[-1].Draw('E1X0same')
self.Pads[-1].RedrawAxis()
return (self.Canvases[-1])
class plotUnc:
tfiles = {}
lgx = 0.65
lgy = 0.4
def __init__(self):
self.MCplots = []
self.MCplotsUp = []
self.MCplotsDown = []
self.DAplots = []
self.Otherplots = []
self.DIVplots = []
self.Canvases = []
self.Pads = []
self.unc = False
ROOT.gStyle.SetOptFit(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTickX(0)
ROOT.gStyle.SetPadTickY(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTopMargin(0.05)
ROOT.gStyle.SetPadRightMargin(0.05)
ROOT.gStyle.SetPadBottomMargin(0.15)
ROOT.gStyle.SetPadLeftMargin(0.15)
ROOT.gStyle.SetLabelFont(43, "x")
ROOT.gStyle.SetLabelFont(43, "y")
ROOT.gStyle.SetLabelFont(43, "z")
ROOT.gStyle.SetLabelOffset(0.01, "x")
ROOT.gStyle.SetLabelOffset(0.01, "y")
ROOT.gStyle.SetLabelOffset(0.01, "z")
ROOT.gStyle.SetLabelSize(25, "x")
ROOT.gStyle.SetLabelSize(25, "y")
ROOT.gStyle.SetLabelSize(25, "z")
ROOT.gStyle.SetTitleFont(43, "x")
ROOT.gStyle.SetTitleFont(43, "y")
ROOT.gStyle.SetTitleFont(43, "z")
ROOT.gStyle.SetTitleOffset(1.2, "x")
ROOT.gStyle.SetTitleOffset(1.5, "y")
ROOT.gStyle.SetTitleOffset(1.1, "z")
ROOT.gStyle.SetTitleSize(30, "x")
ROOT.gStyle.SetTitleSize(30, "y")
ROOT.gStyle.SetTitleSize(30, "z")
def legend(self, legtitle):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
#self.lg = TLegend(0.55, 0.4, xpos-0.02, ypos-0.02)
self.lg = TLegend(self.lgx, self.lgy, xpos - 0.02, ypos - 0.02)
if len(legtitle) != 0:
self.lg.SetHeader(legtitle)
self.lg.SetFillColor(0)
self.lg.SetFillStyle(0)
self.lg.SetLineColor(0)
self.lg.SetLineStyle(0)
self.lg.SetBorderSize(0)
self.lg.SetShadowColor(0)
self.lg.SetTextFont(42)
self.lg.SetTextSize(0.07)
def setchannel(self, title='#splitline{l+jets parton}{%s}' % njets):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
lxtitle = TLatex(0., 0., 'Z')
lxtitle.SetNDC(True)
lxtitle.SetTextFont(63)
lxtitle.SetTextSize(25)
lxtitle.SetTextAlign(13)
lxtitle.DrawLatex(0.35, ypos - 0.03, title)
def cmstext(self, add=''):
xpos = ROOT.gPad.GetLeftMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
self.lx = TLatex(0., 0., 'Z')
self.lx.SetNDC(True)
self.lx.SetTextFont(62)
self.lx.SetTextSize(0.07)
self.lx.SetTextAlign(13)
self.lx.DrawLatex(xpos + 0.04, ypos - 0.02, 'CMS')
self.lx2 = TLatex(0., 0., 'Z')
self.lx2.SetNDC(True)
self.lx2.SetTextFont(52)
self.lx2.SetTextSize(0.07)
self.lx2.SetTextAlign(13)
self.lx2.DrawLatex(xpos + 0.04, ypos - 0.08, add)
def settitle(self, title):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
self.lxtitle = TLatex(0., 0., 'Z')
self.lxtitle.SetNDC(True)
self.lxtitle.SetTextFont(42)
self.lxtitle.SetTextSize(0.07)
self.lxtitle.SetTextAlign(31)
self.lxtitle.DrawLatex(xpos, ypos + 0.02, title)
def addCentralplot(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.MCplots.append(TH1D(self.tfiles[filename].Get(histpath)))
#self.MCplots[-1].SetFillColor(color)
self.MCplots[-1].SetLineColor(color)
#self.MCplots[-1].Scale(scale, 'width')
self.MCplots[-1].Scale(scale)
self.MCplots[-1].SetTitle(title)
return self.MCplots
def addTplotUp(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.MCplotsUp.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.MCplotsUp.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.MCplotsUp.append(TH1D(self.tfiles[filename].Get(histpath)))
self.MCplotsUp[-1].SetLineColor(color)
self.MCplotsUp[-1].SetTitle(title)
self.MCplotsUp[-1].Scale(scale)
#self.MCplotsUp[-1].Scale(1., 'width')
#self.MCplotsUp[-1].Scale(1.)//close box
return self.MCplotsUp
def addTplotDown(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.MCplotsDown.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.MCplotsDown.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.MCplotsDown.append(TH1D(self.tfiles[filename].Get(histpath)))
self.MCplotsDown[-1].SetLineColor(color)
self.MCplotsDown[-1].SetTitle(title)
self.MCplotsDown[-1].Scale(scale)
#self.MCplots[-1].Scale(1., 'width')
#self.MCplots[-1].Scale(1.)//close box
return self.MCplotsDown
def addOtherplot(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.Otherplots.append(TH1D(self.tfiles[filename].Get(histpath)))
self.Otherplots[-1].SetLineColor(color)
self.Otherplots[-1].SetTitle(title)
self.Otherplots[-1].Scale(scale)
return self.Otherplots
def drawAddWithRelUnc(self,
options='hist',
rebin=1,
legtitle='',
title='',
ratio=False,
rangemin=0.,
rangemax=0.,
printbinwidth=True,
xtitle='',
ytitle='',
logy=False):
self.cumaddhist = []
self.cumaddhist.append(TH1D(self.MCplots[0]))
self.cumaddhist.append(TH1D(self.Otherplots[0]))
self.cumaddhist.append(TH1D(self.Otherplots[1]))
for hist in self.MCplots[1:]:
self.cumaddhist.append(TH1D(self.cumaddhist[-1]))
self.cumaddhist[-1].Add(hist)
self.cumaddhist[-1].SetFillColor(hist.GetFillColor())
self.cumaddhist[-1].SetLineColor(hist.GetLineColor())
self.cumaddhist[-1].SetTitle(hist.GetTitle())
totalevents = 0.
for hist in self.MCplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total MC events: ', totalevents
totalevents = 0.
for hist in self.DAplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total DA events: ', totalevents
mymax = 0.
self.Canvases.append(
TCanvas('CanvasAdd_' + self.cumaddhist[-1].GetName(),
'CanvasAdd_' + self.cumaddhist[-1].GetName(), 800, 600))
if ratio == True:
split = 0.3
spaceleft = 0.15
spaceright = 0.05
self.Pads.append(TPad("histpad", "histpad", 0, split, 1., 1.))
self.Pads[-1].SetTopMargin(0.05)
self.Pads[-1].SetBottomMargin(0.022)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Canvases[-1].cd()
self.Pads.append(TPad("divpad", "divpad", 0, 0, 1., split))
self.Pads[-1].SetTopMargin(0.0)
self.Pads[-1].SetBottomMargin(0.4)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Pads[-2].cd()
if len(title) > 0:
ROOT.gPad.SetTopMargin(0.1)
self.legend(legtitle)
if ratio == True:
self.cumaddhist[-1].GetXaxis().SetTitleOffset(5.)
self.cumaddhist[-1].GetXaxis().SetLabelOffset(5.)
for hist in reversed(self.cumaddhist):
hist.Rebin(rebin)
hist.Draw(options)
mymax = max(mymax, hist.GetMaximum())
if rangemin != 0 or rangemax != 0:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
if 'same' not in options:
units = re.findall('\[.*\]', hist.GetXaxis().GetTitle())
unit = ''
if len(units) == 1:
unit = units[0][1:-1]
if ytitle == '':
if len(hist.GetYaxis().GetTitle()) == 0:
ytitle = 'Events'
else:
ytitle = hist.GetYaxis().GetTitle()
#ytitle = ytitle.lower()
if printbinwidth == True:
hist.GetYaxis().SetTitle(
ytitle +
' / {0:g}'.format(hist.GetXaxis().GetBinWidth(1)) +
' ' + unit)
else:
hist.GetYaxis().SetTitle(ytitle)
if (xtitle != ''):
hist.GetXaxis().SetTitle(xtitle)
options += ' same'
for op in self.Otherplots:
op.Rebin(rebin)
op.SetLineWidth(2)
#op.Draw('sameE0')//close box
mymax = max(mymax, op.GetMaximum())
if len(self.DAplots) == 1:
self.DAplots[0].Rebin(rebin)
self.DAplots[0].SetMarkerStyle(20)
self.DAplots[0].SetMarkerSize(1.1)
self.DAplots[0].SetLineWidth(2)
self.DAplots[0].Draw('E1X0same')
mymax = max(mymax, self.DAplots[0].GetMaximum())
if len(self.DAplots) == 1:
self.lg.AddEntry(self.DAplots[0], self.DAplots[0].GetTitle(), 'p')
for hist in reversed(self.cumaddhist):
if len(hist.GetTitle()) != 0:
self.lg.AddEntry(hist, hist.GetTitle(), 'f')
for op in self.Otherplots:
self.lg.AddEntry(op, op.GetTitle(), 'l')
self.lg.Draw()
self.settitle(title)
self.setchannel()
self.cmstext()
if logy == False:
self.cumaddhist[-1].GetYaxis().SetRangeUser(0, mymax * 1.5)
if logy == True:
self.cumaddhist[-1].GetYaxis().SetRangeUser(10, mymax * 50)
self.Pads[-2].SetLogy(True)
self.Pads[-2].RedrawAxis()
if ratio == True:
self.Pads[-1].cd()
self.Pads[-1].SetGridy()
self.DIVplots.append(TH1D(self.Otherplots[0]))
self.DIVplots.append(TH1D(self.Otherplots[1]))
if (xtitle != ''):
self.DIVplots[-1].GetXaxis().SetTitle(xtitle)
#self.DIVplots[-1].Divide(self.cumaddhist[-1])
for b in range(1, self.DIVplots[-1].GetNbinsX() + 1):
if (self.cumaddhist[-1].GetBinContent(b) > 0.):
divval = self.DIVplots[-1].GetBinContent(
b) / self.cumaddhist[-1].GetBinContent(b)
divvalerr = self.DIVplots[-1].GetBinError(
b) / self.cumaddhist[-1].GetBinContent(b)
self.DIVplots[-1].SetBinContent(b, divval)
#self.DIVplots[-1].SetBinError(b, divvalerr)
self.DIVplots[-1].SetBinError(
b,
math.sqrt(divvalerr**2 +
(self.cumaddhist[-1].GetBinError(b) /
self.cumaddhist[-1].GetBinContent(b))**2))
else:
self.DIVplots[-1].SetBinContent(b, 0.)
self.DIVplots[-1].SetBinError(b, 0.)
self.DIVplots[-1].SetMarkerSize(1.1)
self.DIVplots[-1].Draw('E1X0same')
self.DIVplots[-1].GetXaxis().SetTitleOffset(3)
self.DIVplots[-1].GetYaxis().SetTitle('relative unc')
self.DIVplots[-1].GetYaxis().SetTitleOffset(1.3)
self.DIVplots[-1].GetYaxis().SetRangeUser(0.5, 1.5)
self.DIVplots[-1].GetYaxis().SetNdivisions(105)
if rangemin != 0 or rangemax != 0:
self.DIVplots[-1].GetXaxis().SetRangeUser(rangemin, rangemax)
self.DIVplots[-1].Draw('E1X0same')
self.Pads[-1].RedrawAxis()
return (self.Canvases[-1])
if drawObs:
graph_limit_vs_mass_v1_obs_limit.Draw("Lsame")
graph_limit_vs_mass_v1_exp_limit.Draw("Lsame")
graph_limit_vs_mass_v1_Th_limit.Draw("Lsame")
drawCMS2(myC, 13, lumi)
leg_limit_vs_mass_v1 = TLegend(0.25, 0.62, 0.9, 0.89)
leg_limit_vs_mass_v1.SetHeader(
"c#tau_{#tilde{#chi}_{1}^{0}} = " + str(ctau_this) +
" cm, #tilde{#chi}^{0}_{1} #rightarrow #gamma #tilde{G}")
leg_limit_vs_mass_v1.SetBorderSize(0)
leg_limit_vs_mass_v1.SetTextSize(0.03)
leg_limit_vs_mass_v1.SetLineColor(1)
leg_limit_vs_mass_v1.SetLineStyle(1)
leg_limit_vs_mass_v1.SetLineWidth(1)
leg_limit_vs_mass_v1.SetFillColor(0)
leg_limit_vs_mass_v1.SetFillStyle(1001)
leg_limit_vs_mass_v1.AddEntry(graph_limit_vs_mass_v1_Th_limit,
"Theoretical cross-section", "L")
if drawObs:
leg_limit_vs_mass_v1.AddEntry(graph_limit_vs_mass_v1_obs_limit,
"Observed 95% CL upper limit", "L")
leg_limit_vs_mass_v1.AddEntry(graph_limit_vs_mass_v1_exp_limit,
"Expected 95% CL upper limit", "L")
leg_limit_vs_mass_v1.AddEntry(graph_limit_vs_mass_v1_exp1sigma_limit,
"#pm 1 #sigma Expected", "F")
leg_limit_vs_mass_v1.AddEntry(graph_limit_vs_mass_v1_exp2sigma_limit,
"#pm 2 #sigma Expected", "F")
if drawObs:
graph_limit_vs_mass__obs_limit.Draw("Lsame")
graph_limit_vs_mass__exp_limit.Draw("Lsame")
graph_limit_vs_mass__Th_limit.Draw("Lsame")
drawCMS2(myC, 13, lumi_this)
leg_limit_vs_mass_ = TLegend(0.25, 0.62, 0.9, 0.89)
leg_limit_vs_mass_.SetHeader(
"c#tau_{#tilde{#chi}_{1}^{0}} = " + str(ctau_this) +
" cm, #tilde{#chi}^{0}_{1} #rightarrow #gamma #tilde{G}")
leg_limit_vs_mass_.SetBorderSize(0)
leg_limit_vs_mass_.SetTextSize(0.03)
leg_limit_vs_mass_.SetLineColor(1)
leg_limit_vs_mass_.SetLineStyle(1)
leg_limit_vs_mass_.SetLineWidth(1)
leg_limit_vs_mass_.SetFillColor(0)
leg_limit_vs_mass_.SetFillStyle(1001)
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__Th_limit,
"Theoretical cross-section", "L")
if drawObs:
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__obs_limit,
"Observed 95% CL upper limit", "L")
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__exp_limit,
"Expected 95% CL upper limit", "L")
leg_limit_vs_mass_.Draw()
myC.SaveAs(outputDir + "/limits" + "/limit_vs_mass_" + year_this +
"_ctau" + ctau_this_str + plot_tag + ".pdf")
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
gStyle.SetTitleOffset(0.9, "X")
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
leg = TLegend(0.4, 0.70, 0.939, 0.89) #,NULL,"brNDC");
legendtitle = legendtext[-1]
leg.SetHeader(legendtitle)
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(22)
leg.SetTextSize(0.045)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c.SetLogy(0)
#c.SetLogx(0)
c1_2 = TPad("c1_2", "newpad", 0.04, 0.05, 1, 0.994)
c1_2.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
#c1_2.SetBottomMargin(0.13)
c1_2.SetLogy(logstatus[1])
c1_2.SetLogx(logstatus[0])
c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
type_obj = type(histList[ii])
if (type_obj is TH1D) or (type_obj is TH1F) or (
type_obj is TH1) or (type_obj is TH1I):
histList[ii].Rebin(1)
histList[ii].Scale(1.0 / histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if (tt is TGraphAsymmErrors) | (tt is TGraph):
histList[ih].Draw("A3P")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("HIST")
if ih > 0:
#histList[ih].SetLineWidth(2)
if (tt is TGraphAsymmErrors) | (tt is TGraph):
histList[ih].Draw("3P same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("HISTsame")
if (tt is TGraphAsymmErrors) | (tt is TGraph):
# histList[ih].SetMaximum(0.06)
# histList[ih].SetMinimum(0.02)
# histList[ih].SetMaximum(maximum+0.3)
histList[ih].SetMinimum(0.02)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "P")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
histList[ih].SetMaximum(maximum[0] + 0.3)
histList[ih].SetMinimum(0)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.045)
histList[ih].GetYaxis().SetTitleOffset(1.1000998)
histList[ih].GetYaxis().SetTitleFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelSize(.045)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.0000)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.04)
histList[ih].GetXaxis().SetTitleFont(22)
histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
# histList[ih].GetXaxis().SetNdivisions(508)
#
i = i + 1
pt = TPaveText(0.0877181, 0.9, 0.9580537, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
text = pt.AddText(0.05, 0.5, "CMS Preliminary")
#text = pt.AddText(0.5,0.5,"12.9 fb^{-1} (13 TeV)")
# text = pt.AddText(0.8,0.5," (13 TeV)")
# text = pt.AddText(0.65,0.5," AK8")
pt.Draw()
# t2a = TPaveText(0.0877181,0.81,0.9580537,0.89,"brNDC")
# t2a.SetBorderSize(0)
# t2a.SetFillStyle(0)
# t2a.SetTextSize(0.040)
# t2a.SetTextAlign(12)
# t2a.SetTextFont(62)
# histolabel1= str(fileVec[(len(fileVec)-1)])
# text1 = t2a.AddText(0.06,0.5,"CMS Internal")
# t2a.Draw()
leg.Draw()
#
# c.cd()
outputdirname = 'HGCAL/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
def DrawOverlap(histList,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
cat='2b'):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
#gStyle.SetTitleOffset(1.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
gStyle.SetTickLength(0.0, "x")
i = 0
# histList_=[]
# histList=[]
# histList1=[]
# maximum=[]
## Legend
leg = TLegend(0.2, 0.80, 0.89, 0.89) #,NULL,"brNDC");
leg.SetBorderSize(0)
leg.SetNColumns(3)
# leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
# leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
c.SetBottomMargin(0.15)
c.SetLeftMargin(0.15)
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
# print ("you have provided "+str(len(fileVec))+" files and "+str(len(histVec))+" histograms to make a overlapping plot" )
# print "opening rootfiles"
c.cd()
print "provided hists", histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(1.5) #1.4 for log
histList[ih].SetMinimum(0.1) #1.4 for log
if logstatus[1] is 0:
maxi = histList[ih].GetMaximum()
histList[ih].SetMaximum(maxi * 2) #1.4 for log
histList[ih].SetMinimum(0) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE2 ")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE0 same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(100)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(0)
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
print "setting style for hist"
print "color code", colors[ih]
# histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetFillColor(colors[ih])
histList[ih].SetMarkerStyle(20)
histList[ih].SetMarkerSize(1.0)
histList[ih].SetLineWidth(1)
#invert legend between first and second
if ih == 0:
leg.AddEntry(histList[ih + 1], legendtext[ih + 1],
"PEL") #"f")
if ih == 1:
leg.AddEntry(histList[ih - 1], legendtext[ih - 1],
'f') #"PEL")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.4)
histList[ih].GetYaxis().SetTitleFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
# histList[ih].GetXaxis().SetLabelSize(0.0000);
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
#histList[ih].GetXaxis().SetTitleOffset(1.14)
histList[ih].GetXaxis().SetTitleFont(42)
histList[ih].GetXaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetXaxis().SetNdivisions(507)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
# histList[ih].GetXaxis().SetTickSize(0.00)
i = i + 1
pt = TPaveText(0.01, 0.92, 0.95, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.046)
#text = pt.AddText(0.12,0.35,"CMS Internal 36 fb^{-1} (2016) ")
text = pt.AddText(0.12, 0.35,
"CMS Internal 41.5 fb^{-1} (2017) ")
#text = pt.AddText(0.12,0.35,"CMS Internal 59.6 fb^{-1} (2018) ")
#text = pt.AddText(0.6,0.5,"41.5 fb^{-1} (2017) ")
cattxt = TLatex(0.20, 0.75, cat + ' ' + "category")
cattxt.SetTextSize(0.06)
cattxt.SetTextAlign(12)
cattxt.SetNDC(1)
cattxt.SetTextFont(42)
pt.Draw()
cattxt.Draw()
leg.Draw()
outputdirname = 'TFplots/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
def makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
#fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE")
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
xPointsForErrors = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
xPointsForErrors.append(0)
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
xPointsErrors = numpy.array(xPointsForErrors)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected2SigLow),
numpy.array(expected2SigHigh))
GraphErr1SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected1SigLow),
numpy.array(expected1SigHigh))
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
#cCL=TCanvas("cCL", "cCL",0,0,567,384)
cCL = TCanvas("cCL", "cCL", 0, 0, 600, 450)
gStyle.SetOptStat(0)
gStyle.SetPadRightMargin(0.063)
gStyle.SetPadLeftMargin(0.14)
gStyle.SetPadBottomMargin(0.12)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
if SPIN2:
signals = ["RS_kMpl01", "RS_kMpl005", "RS_kMpl001"]
elif GUT:
signals = ["ssm", "psi", "kai", "eta", "I", "S", "N"]
else:
signals = ["ssm", "psi"]
xSecCurves = []
for signal in signals:
xSecCurves.append(getXSecCurve(signal, kFacs[signal]))
#xSecCurves.append(getXSecCurve(signal,kFacs[signal],massDependent=True))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if SPIN2:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] G_{KK} / [#sigma#upoint#font[12]{B}] Z"
)
else:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z")
# if SPIN2:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
# else:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(200, 5500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(1e-4)
DummyGraph.GetXaxis().SetLabelSize(0.055)
DummyGraph.GetXaxis().SetTitleSize(0.055)
DummyGraph.GetXaxis().SetTitleOffset(1.05)
DummyGraph.GetYaxis().SetLabelSize(0.055)
DummyGraph.GetYaxis().SetTitleSize(0.055)
DummyGraph.GetYaxis().SetTitleOffset(1.3)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
curve.Draw("lsame")
plCMS = TPaveLabel(.16, .81, .27, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.16, .76, .27, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
if "2017" in output or "Combination" in output:
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
#leg=TLegend(0.540517,0.623051,0.834885,0.878644,"","brNDC") Default
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
if SPIN2:
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.0425)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Obs. 95%% CL limit" % ratioLabels[1], "l")
leg.AddEntry(GraphObs2, "%s Obs. 95%% CL limit" % ratioLabels[0], "l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg1 = TLegend(0.7, 0.4, 0.9, 0.55, "", "brNDC")
leg1.SetTextSize(0.05)
if GUT:
leg1 = TLegend(0.6, 0.35, 0.75, 0.623051, "", "brNDC")
if SPIN2:
leg1 = TLegend(0.7, 0.35, 0.9, 0.58, "G_{KK} (LO x 1.6)", "brNDC")
leg1.SetTextSize(0.045)
for index, signal in enumerate(signals):
xSecCurves[index].SetName(labels[signal])
xSecCurves[index].Write(labels[signal])
leg1.AddEntry(xSecCurves[index], labels[signal], "l")
leg1.SetBorderSize(0)
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetFillStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif "2017" in output or "Combination" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"42.4 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"41.4 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"77.3 fb^{-1} (13 TeV, ee) + 78.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.SetTicks(1, 1)
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
#GraphErr2SigForHEPData.SetName("graph2Sig")
#GraphErr2SigForHEPData.Write("graph2Sig")
#GraphErr1SigForHEPData.SetName("graph1Sig")
#GraphErr1SigForHEPData.Write("graph1Sig")
#GraphExp.SetName("graphExp")
#GraphExp.Write("graphExp")
#GraphObs.SetName("graphObs")
#GraphObs.Write("graphObs")
#fileForHEPData.Write()
#fileForHEPData.Close()
cCL.Update()
printPlots(cCL, output)
def makeLimitPlot(output, obs, exp, chan, printStats=False):
obsLimits = {}
for obsFile in obs:
if 'width' in obsFile:
width = obsFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
obsLimits[width] = createObsGraph(obsFile)
if SMOOTH:
for width, obsGraph in obsLimits.iteritems():
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = obsGraph
obsLimits[width] = copy.deepcopy(
smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0, 0.005))
obsLimits[width].SetLineWidth(3)
expLimits = {}
for expFile in exp:
if 'width' in expFile:
width = expFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
expLimits[width] = createExpGraph(expFile)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
smoother = TGraphSmooth("normal")
smoother2 = TGraphSmooth("normal")
zprimeX = []
zprimeY = []
fileZPrime = open('tools/xsec_ssm.txt', 'r')
for entries in fileZPrime:
entry = entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1]) * 1.3 / 1928)
zpX = numpy.array(zprimeX)
zpY = numpy.array(zprimeY)
GraphZPrime = TGraph(481, zpX, zpY)
GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX = []
zprimePsiY = []
fileZPrimePsi = open('tools/xsec_psi.txt', 'r')
for entries in fileZPrimePsi:
entry = entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1]) * 1.3 / 1928)
zpPsiX = numpy.array(zprimePsiX)
zpPsiY = numpy.array(zprimePsiY)
GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY)
GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
if "Moriond" in output:
DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500)
else:
DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)"
)
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)"
)
gStyle.SetOptStat(0)
if "Moriond" in output:
DummyGraph.GetXaxis().SetRangeUser(200, 5500)
else:
DummyGraph.GetXaxis().SetRangeUser(400, 4500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(4e-4)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
leg = TLegend(0.430517, 0.623051, 0.734885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
colors = {
'01': ROOT.kBlue,
'03': ROOT.kRed,
'05': ROOT.kGreen + 3,
'10': ROOT.kOrange
}
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
obsGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(obsGraph, "Observed 95% CL limit width 0.6%", "l")
else:
leg.AddEntry(obsGraph,
"Observed 95%% CL limit width %d%%" % int(width), "l")
for width in sorted(expLimits):
expGraph = expLimits[width]
if colors.has_key(width):
expGraph.SetLineColor(colors[width])
expGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(expGraph, "Expected 95% CL limit width 0.6%, median",
"l")
else:
leg.AddEntry(
expGraph,
"Expected 95%% CL limit width %d%%, median" % (int(width)),
"l")
# if not SPIN2:
# GraphZPrimeSmooth.Draw("lsame")
# GraphZPrimePsiSmooth.Draw("lsame")
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
cCL.Update()
printPlots(cCL, output)
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
text_="",
x_=0.5,
y_=0.5,
legendloc=[0.53, 0.13, 0.93, 0.39]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
#gStyle.SetTitleOffset(1.1,"Y");
#gStyle.SetTitleOffset(0.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
legpos = legendloc
leg = TLegend(legpos[0], legpos[1], legpos[2], legpos[3])
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.049)
from PlotTemplates import myCanvas1D
c = myCanvas1D()
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c1_2 = TPad("c1_2","newpad",0.04,0.13,1,0.994)
#c1_2.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
#c1_2.SetBottomMargin(0.013)
#c1_2.SetLogy(logstatus[1])
#c1_2.SetLogx(logstatus[0])
#c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
#print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
#histList[ii].Scale(1.0/histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(100) #1.4 for log
histList[ih].SetMinimum(0.00001) #1.4 for log
if logstatus[1] is 0:
histList[ih].SetMaximum(1.4) #1.4 for log
histList[ih].SetMinimum(0.001) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(10)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.08)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.14)
#histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetNdivisions(508)
from PlotTemplates import SetCMSAxis
histList[ih] = SetCMSAxis(histList[ih], 1.0, 1.15)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
i = i + 1
'''
pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
text = pt.AddText(0.2,0.5,"CMS Internal")
'''
from PlotTemplates import drawenergy1D
pt_ = drawenergy1D(False)
for ipt in pt_:
ipt.Draw()
'''
if len(text_) >0:
ltx = TLatex()
ltx.SetTextFont(42)
ltx.SetTextSize(0.049)
#text_f = "#font[42]{Phase Scan}"
ltx.DrawTextNDC(x_,y_,text_)
'''
from PlotTemplates import ExtraText
text_ex = ExtraText(text_, x_, y_)
text_ex.Draw()
ExtraText("ECAL Endcaps", 0.4, 0.85)
ltx_ = TLatex()
ltx_.SetTextFont(42)
ltx_.SetTextSize(0.049)
ltx_.DrawLatexNDC(0.32, 0.81, "L1 e-#gamma object p_{T} > 10 GeV")
#text_ex.Draw()
#pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
#text = pt.AddText(0.65,0.5,"Phase Scan data #sqrt{s} = 13 TeV (2018)")
#pt.Draw()
# t2a = TPaveText(0.0877181,0.81,0.9580537,0.89,"brNDC")
# t2a.SetBorderSize(0)
# t2a.SetFillStyle(0)
# t2a.SetTextSize(0.040)
# t2a.SetTextAlign(12)
# t2a.SetTextFont(62)
# histolabel1= str(fileVec[(len(fileVec)-1)])
# text1 = t2a.AddText(0.06,0.5,"CMS Internal")
# t2a.Draw()
leg.SetHeader("Matched TP energy")
leg.Draw()
#
# c.cd()
outputdirname = './'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
class plotTogether:
tfiles = {}
lgx = 0.65
lgy = 0.4
def __init__(self):
self.unctitle = ''
self.MCplots = []
self.DAplots = []
self.NOplots = []
self.Otherplots = []
self.DIVplots = []
self.Canvases = []
self.Pads = []
self.unc = False
ROOT.gStyle.SetOptFit(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTickX(0)
ROOT.gStyle.SetPadTickY(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetPadTopMargin(0.05)
ROOT.gStyle.SetPadRightMargin(0.05)
ROOT.gStyle.SetPadBottomMargin(0.15)
ROOT.gStyle.SetPadLeftMargin(0.15)
ROOT.gStyle.SetLabelFont(43, "x")
ROOT.gStyle.SetLabelFont(43, "y")
ROOT.gStyle.SetLabelFont(43, "z")
ROOT.gStyle.SetLabelOffset(0.01, "x")
ROOT.gStyle.SetLabelOffset(0.01, "y")
ROOT.gStyle.SetLabelOffset(0.01, "z")
ROOT.gStyle.SetLabelSize(25, "x")
ROOT.gStyle.SetLabelSize(25, "y")
ROOT.gStyle.SetLabelSize(25, "z")
ROOT.gStyle.SetTitleFont(43, "x")
ROOT.gStyle.SetTitleFont(43, "y")
ROOT.gStyle.SetTitleFont(43, "z")
ROOT.gStyle.SetTitleOffset(1.2, "x")
ROOT.gStyle.SetTitleOffset(1.5, "y")
ROOT.gStyle.SetTitleOffset(1.1, "z")
ROOT.gStyle.SetTitleSize(30, "x")
ROOT.gStyle.SetTitleSize(30, "y")
ROOT.gStyle.SetTitleSize(30, "z")
def legend(self, legtitle):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
#self.lg = TLegend(0.55, 0.4, xpos-0.02, ypos-0.02)
self.lg = TLegend(self.lgx, self.lgy, xpos - 0.02, ypos - 0.02)
if len(legtitle) != 0:
self.lg.SetHeader(legtitle)
self.lg.SetFillColor(0)
self.lg.SetFillStyle(0)
self.lg.SetLineColor(0)
self.lg.SetLineStyle(0)
self.lg.SetBorderSize(0)
self.lg.SetShadowColor(0)
self.lg.SetTextFont(42)
self.lg.SetTextSize(0.07)
njetstr = sys.argv[3][0] + ' jets' if '6' not in sys.argv[
3] and 'up' not in sys.argv[3] else '#geq' + sys.argv[3][0] + ' jets'
def setchannel(self, title='e/#mu+jets, ' + njetstr):
#def setchannel(self, title = 'e/#mu+jets, %s jets' %njets[0]):
#def setchannel(self, title = 'e/#mu+jets, #geq%s jets' %njets[0]):
#def setchannel(self, title = 'e/#mu+jets, #geq%s jets in SB' %njets[0]):
#def setchannel(self, title = 'l+jets'):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
lxtitle = TLatex(0., 0., 'Z')
lxtitle.SetNDC(True)
lxtitle.SetTextFont(63)
lxtitle.SetTextSize(25)
lxtitle.SetTextAlign(13)
lxtitle.DrawLatex(0.35, ypos - 0.03, title)
def cmstext(self, add=''):
xpos = ROOT.gPad.GetLeftMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
self.lx = TLatex(0., 0., 'Z')
self.lx.SetNDC(True)
self.lx.SetTextFont(62)
self.lx.SetTextSize(0.07)
self.lx.SetTextAlign(13)
self.lx.DrawLatex(xpos + 0.04, ypos - 0.03, 'CMS')
self.lx2 = TLatex(0., 0., 'Z')
self.lx2.SetNDC(True)
self.lx2.SetTextFont(52)
self.lx2.SetTextSize(0.05)
self.lx2.SetTextAlign(13)
self.lx2.DrawLatex(xpos + 0.04, ypos - 0.10, 'Preliminary')
def settitle(self, title):
xpos = 1. - ROOT.gPad.GetRightMargin()
ypos = 1. - ROOT.gPad.GetTopMargin()
self.lxtitle = TLatex(0., 0., 'Z')
self.lxtitle.SetNDC(True)
self.lxtitle.SetTextFont(42)
self.lxtitle.SetTextSize(0.07)
self.lxtitle.SetTextAlign(31)
self.lxtitle.DrawLatex(xpos, ypos + 0.02, title)
def printLatexYieldTable(self, fname='yield_table.tex'):
''' This function will print a table based on how the addMCplot and addDAplot functions were called.
It will sum over all files that have no title, and assing them to the previous title. So for example:
plot[p].addMCplot(DYfile, p, 'V+Jets', DYscale, ROOT.kGreen+2, projection = pro)
plot[p].addMCplot(Wfile, p, '', Wscale, ROOT.kGreen+2, projection = pro)
will create a category 'V+Jets' that includes DY and W+jets events stored in DYfile and Wfile.
A call to this function should be added just after a call to drawAddWithRatio for that particular histogram, and then, for example:
can = plot[p].drawAddWithRatio( .......
if (p == "RECO/all_njets"):
plot[p].printLatexYieldTable('totyield_table.tex'
'''
MCtot = 0.
MCtot_err = 0.
category_yield = []
category_err = []
category_title = []
cat_yield = 0.
cat_err = 0.
for index, hist in enumerate(self.MCplots):
if hist.GetTitle() != '':
category_title.append(hist.GetTitle())
cat_yield = 0.
cat_err = 0.
err = ROOT.Double(0)
# Make sure you run this over a histogram with known under- and overflows!
# For example number of jets, or MET, anything that hasn't been initialized to -9
events = hist.IntegralAndError(0, hist.GetNbinsX() + 1, err)
#events = hist.Integral()
cat_yield += events
cat_err = math.sqrt(cat_err * cat_err + err * err)
if len(self.MCplots
) == index + 1 or self.MCplots[index + 1].GetTitle() != '':
category_yield.append(cat_yield)
category_err.append(cat_err)
MCtot += events
MCtot_err = math.sqrt(MCtot_err * MCtot_err + err * err)
# Ready to print the numbers, first open the latex file:
latexfile = open(fname, "w")
latexfile.write(
"\\begin{tabular}{l|r@{$\\pm$}l} \\hline \n") # r@{$\pm$}l
latexfile.write("%-12s & %20s \\\\ \\hline \n" %
('Source', '\multicolumn{2}{c}{Yield}'))
for i in range(len(category_title)):
print "%-12s %5.1f +- %4.1f" % (category_title[i],
category_yield[i], category_err[i])
latexfile.write(
"%-12s & %5.1f & %4.1f \\\\ \n" %
(category_title[i], category_yield[i], category_err[i]))
print "%-12s %5.1f +- %4.1f" % ('BKG SUM ', MCtot, MCtot_err)
latexfile.write("%-12s & %5.1f & %4.1f\\\\ \\hline \n" %
('BKG SUM ', MCtot, MCtot_err))
DAtot = 0.
for hist in self.DAplots:
DAtot += hist.Integral()
print "%-12s %5i" % ('Data ', DAtot)
latexfile.write("%-12s & \multicolumn{2}{c}{%5i} \\\\ \n" %
('Data ', DAtot))
latexfile.write("\\end{tabular} \n")
latexfile.close()
print "Wrote LaTeX table with yields in: ", fname
print "The errors are obtained from ROOT::TH1::IntegralAndError() and added in quadrature per category"
return [DAtot, MCtot, MCtot_err]
def addMCplot(self,
filename,
histpath,
title,
scale,
color,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
print "little fox", self.tfiles[filename], histpath
if projection == 'Y':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.MCplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.MCplots.append(TH1D(self.tfiles[filename].Get(histpath)))
print "fox"
self.MCplots[-1].SetFillColor(color)
self.MCplots[-1].SetLineColor(color)
#self.MCplots[-1].Scale(scale, 'width')
self.MCplots[-1].Scale(scale)
self.MCplots[-1].SetTitle(title)
def setUncTitle(self, unctitle):
self.unctitle = unctitle
def addUncerHist(self,
fcentral,
datascale,
datascaledw,
datascaleup,
ferrdown,
ferrup,
hist,
scaleUnc,
projection='',
Norm=False,
AsymmetricError=False):
if self.unc == False:
self.herr = TH1D(self.DAplots[-1])
self.herr.Reset()
self.herr.SetName('err')
if AsymmetricError:
self.herrup = TH1D(self.DAplots[-1])
self.herrup.Reset()
self.herrup.SetName('errup')
self.herrdw = TH1D(self.DAplots[-1])
self.herrdw.Reset()
self.herrdw.SetName('errdw')
self.unc = True
if fcentral not in self.tfiles:
self.tfiles[fcentral] = TFile(fcentral, 'read')
if ferrdown not in self.tfiles:
self.tfiles[ferrdown] = TFile(ferrdown, 'read')
if ferrup not in self.tfiles:
self.tfiles[ferrup] = TFile(ferrup, 'read')
hcen = self.tfiles[fcentral].Get(hist)
hdown = self.tfiles[ferrdown].Get(hist)
hup = self.tfiles[ferrup].Get(hist)
print "normalization precheck:", hcen.Integral(), hdown.Integral(
), hup.Integral(), datascale, datascaleup, datascaledw
if Norm and (hup.Integral() != 0. and hdown.Integral() != 0.):
hcen.Scale(datascale)
hup.Scale(datascaleup)
hdown.Scale(datascaledw)
hup.Scale(hcen.Integral() / hup.Integral())
hdown.Scale(hcen.Integral() / hdown.Integral())
else:
hcen.Scale(datascale)
hup.Scale(datascaleup)
hdown.Scale(datascaledw)
print "normalization check:", hcen.Integral(), hdown.Integral(
), hup.Integral()
if projection == 'Y':
hcen = TH1D(hcen.ProjectionY())
hdown = TH1D(hdown.ProjectionY())
hup = TH1D(hup.ProjectionY())
if projection == 'X':
hcen = TH1D(hcen.ProjectionX())
hdown = TH1D(hdown.ProjectionX())
hup = TH1D(hup.ProjectionX())
self.cumaddhist = []
self.cumaddhist.append(TH1D(self.MCplots[0]))
for hist in self.MCplots[1:]:
self.cumaddhist.append(TH1D(self.cumaddhist[-1]))
self.cumaddhist[-1].Add(hist)
for b in range(1, 1 + self.herr.GetNbinsX()):
cen = hcen.GetBinContent(b)
tot = self.cumaddhist[-1].GetBinContent(b)
if cen == 0 or tot == 0:
continue
up = hup.GetBinContent(b)
down = hdown.GetBinContent(b)
old = self.herr.GetBinContent(b)
errA = (up - cen) * scaleUnc / cen
errB = (down - cen) * scaleUnc / cen
err = (abs(errA) + abs(errB)) / 2.
#err = max(abs(errA), abs(errB))
compWeight = cen / tot
self.herr.SetBinContent(b,
math.sqrt(old**2 + err**2 * compWeight**2))
#self.herr.SetBinContent(b, math.sqrt(old**2 + err**2))
#print scaleUnc
if AsymmetricError:
old = self.herrup.GetBinContent(b)
self.herrup.SetBinContent(
b, math.sqrt(old**2 + errA**2 * compWeight**2))
old = self.herrdw.GetBinContent(b)
self.herrdw.SetBinContent(
b, math.sqrt(old**2 + errB**2 * compWeight**2))
#Those are important !!!
hcen.Scale(1 / datascale)
hup.Scale(1 / datascaleup)
hdown.Scale(1 / datascaledw)
if Norm and (hup.Integral() != 0 and hdown.Integral() != 0):
hup.Scale(1 / (hcen.Integral() / hup.Integral()))
hdown.Scale(1 / (hcen.Integral() / hdown.Integral()))
def addUncerVal(self, val):
if self.unc == False:
self.herr = TH1D(self.DAplots[-1])
self.herr.Reset()
self.herr.SetName('err')
self.unc = True
for b in range(1, 1 + self.herr.GetNbinsX()):
old = self.herr.GetBinContent(b)
self.herr.SetBinContent(b, math.sqrt(old**2 + val**2))
def addUncerValBins(self, valist):
if self.unc == False:
self.herr = TH1D(self.DAplots[-1])
self.herr.Reset()
self.herr.SetName('err')
self.unc = True
for b in range(len(valist)):
old = self.herr.GetBinContent(b + 4)
print old, valist[b], math.sqrt(old**2 + valist[b]**2), b + 1
self.herr.SetBinContent(b + 4, math.sqrt(old**2 + valist[b]**2))
#def addDAplot(self, filename, histpath, title, projection = '', scale = 1.):#close box
def addDAplot(self, filename, histpath, title, scale, projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.DAplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.DAplots.append(TH1D(self.tfiles[filename].Get(histpath)))
self.DAplots[-1].SetTitle(title)
self.DAplots[-1].Scale(scale)
#self.DAplots[-1].Scale(1., 'width')
self.DAplots[-1].Scale(1.) #//close box
def addOtherplot(self,
filename,
histpath,
title,
scale,
color,
style=1,
projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.Otherplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.Otherplots.append(TH1D(self.tfiles[filename].Get(histpath)))
#self.NOplots[-1].SetFillColor(color)
self.Otherplots[-1].SetLineColor(color)
self.Otherplots[-1].SetLineStyle(style)
self.Otherplots[-1].SetTitle(title)
self.Otherplots[-1].Scale(scale)
def addNormplot(self, filename, histpath, title, color, projection=''):
if filename not in self.tfiles:
self.tfiles[filename] = TFile(filename, 'read')
if projection == 'Y':
self.NOplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionY()))
elif projection == 'X':
self.NOplots.append(
TH1D(self.tfiles[filename].Get(histpath).ProjectionX()))
else:
self.NOplots.append(TH1D(self.tfiles[filename].Get(histpath)))
#self.NOplots[-1].SetFillColor(color)
self.NOplots[-1].SetLineColor(color)
self.NOplots[-1].SetTitle(title)
def drawAddWithRatio(self,
options='hist',
rebin=1,
legtitle='',
title='',
ratio=False,
rangemin=0.,
rangemax=0.,
printbinwidth=True,
xtitle='',
ytitle='',
logy=False,
xlabels=[],
AsymmetricError=False):
self.cumaddhist = []
self.cumaddhist.append(TH1D(self.MCplots[0]))
for hist in self.MCplots[1:]:
self.cumaddhist.append(TH1D(self.cumaddhist[-1]))
self.cumaddhist[-1].Add(hist)
self.cumaddhist[-1].SetFillColor(hist.GetFillColor())
self.cumaddhist[-1].SetLineColor(hist.GetLineColor())
self.cumaddhist[-1].SetTitle(hist.GetTitle())
totalevents = 0.
for hist in self.MCplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total MC events: ', totalevents
totalevents = 0.
for hist in self.DAplots:
if rangemin != rangemax:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
totalevents += hist.Integral()
print 'Total DA events: ', totalevents
mymax = 0.
self.Canvases.append(
TCanvas('CanvasAdd_' + self.cumaddhist[-1].GetName(),
'CanvasAdd_' + self.cumaddhist[-1].GetName(), 800, 600))
if ratio == True:
split = 0.3
spaceleft = 0.15
spaceright = 0.05
self.Pads.append(TPad("histpad", "histpad", 0, split, 1., 1.))
self.Pads[-1].SetTopMargin(0.05)
self.Pads[-1].SetBottomMargin(0.022)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Canvases[-1].cd()
self.Pads.append(TPad("divpad", "divpad", 0, 0, 1., split))
self.Pads[-1].SetTopMargin(0.0)
self.Pads[-1].SetBottomMargin(0.4)
self.Pads[-1].SetLeftMargin(spaceleft)
self.Pads[-1].SetRightMargin(spaceright)
self.Pads[-1].Draw()
self.Pads[-2].cd()
if len(title) > 0:
ROOT.gPad.SetTopMargin(0.1)
self.legend(legtitle)
if len(xlabels) != 0:
b = 0
for label in xlabels:
b += 1
self.cumaddhist[-1].GetXaxis().SetBinLabel(b, label)
if ratio == True:
self.cumaddhist[-1].GetXaxis().SetTitleOffset(5.)
self.cumaddhist[-1].GetXaxis().SetLabelOffset(5.)
xList, yList = array('d'), array('d')
errleftList, errightList = array('d'), array('d')
errupList, errdwList = array('d'), array('d')
relupList, reldwList = array('d'), array('d')
for hist in reversed(self.cumaddhist):
hist.Rebin(rebin)
hist.Draw(options)
mymax = max(mymax, hist.GetMaximum())
if rangemin != 0 or rangemax != 0:
hist.GetXaxis().SetRangeUser(rangemin, rangemax)
if 'same' not in options:
if self.unc:
self.herr.Rebin(rebin)
self.herr.Scale(1. / rebin)
self.errprint = TH1D(hist)
self.errprint.SetName('errprint')
for b in range(1, self.errprint.GetNbinsX() + 1):
self.errprint.SetBinError(
b,
self.herr.GetBinContent(b) * hist.GetBinContent(b))
self.errprint.SetFillColor(1)
self.errprint.SetLineColor(1)
self.errprint.SetLineWidth(0)
self.errprint.SetFillStyle(3354)
#self.errprint.SetFillStyle(3344)
self.errprint.Draw('E2same') #//close box
if AsymmetricError:
self.herrup.Rebin(rebin)
self.herrup.Scale(1. / rebin)
self.herrdw.Rebin(rebin)
self.herrdw.Scale(1. / rebin)
#self.DAplots[0].Rebin(rebin)
for b in range(1, 1 + self.herr.GetNbinsX()):
xList.append(self.cumaddhist[-1].GetBinCenter(b))
yList.append(self.cumaddhist[-1].GetBinContent(b))
#yList.append(self.DAplots[0].GetBinContent(b))
errleftList.append(self.cumaddhist[-1].GetXaxis(
).GetBinCenter(b) - self.cumaddhist[-1].GetXaxis().
GetBinLowEdge(b))
errightList.append(
self.cumaddhist[-1].GetXaxis().GetBinUpEdge(
b) -
self.cumaddhist[-1].GetXaxis().GetBinCenter(b))
#errupList.append(self.herrup.GetBinContent(b)*self.cumaddhist[-1].GetBinContent(b))
#errdwList.append(self.herrdw.GetBinContent(b)*self.cumaddhist[-1].GetBinContent(b))
errupList.append(
self.herrup.GetBinContent(b) *
self.DAplots[0].GetBinContent(b))
errdwList.append(
self.herrdw.GetBinContent(b) *
self.DAplots[0].GetBinContent(b))
relupList.append(self.herrup.GetBinContent(b))
reldwList.append(self.herrdw.GetBinContent(b))
self.gerr = TGraphAsymmErrors(len(xList), xList, yList,
errleftList, errightList,
errdwList, errupList)
self.gerr.SetName('gerr')
self.gerr.SetFillColor(1)
self.gerr.SetLineColor(1)
self.gerr.SetLineWidth(0)
self.gerr.SetFillStyle(3354)
self.gerr.Draw('E2same') #//close box
#else:
#self.errprint.Draw('E2same')#//close box
units = re.findall('\[.*\]', hist.GetXaxis().GetTitle())
unit = ''
if len(units) == 1:
unit = units[0][1:-1]
if ytitle == '':
if len(hist.GetYaxis().GetTitle()) == 0:
ytitle = 'Events'
else:
ytitle = hist.GetYaxis().GetTitle()
#ytitle = ytitle.lower()
if printbinwidth == True:
hist.GetYaxis().SetTitle(
ytitle +
' / {0:g}'.format(hist.GetXaxis().GetBinWidth(1)) +
' ' + unit)
else:
hist.GetYaxis().SetTitle(ytitle)
if (xtitle != ''):
hist.GetXaxis().SetTitle(xtitle)
options += ' same'
#if not AsymmetricError:
# self.errprint.Draw('E2same')#//close box
for np in self.NOplots:
np.Rebin(rebin)
np.Scale(self.DAplots[0].Integral() / np.Integral())
np.SetLineWidth(2)
np.Draw('sameE0') #//close box
mymax = max(mymax, np.GetMaximum())
for op in self.Otherplots:
op.Rebin(rebin)
op.SetLineWidth(2)
op.Draw('sameE0') #//close box
mymax = max(mymax, op.GetMaximum())
if len(self.DAplots) == 1:
self.DAplots[0].Rebin(rebin)
self.DAplots[0].SetMarkerStyle(20)
self.DAplots[0].SetMarkerSize(1.1)
self.DAplots[0].SetLineWidth(2)
self.DAplots[0].Draw('E1X0same')
mymax = max(mymax, self.DAplots[0].GetMaximum())
if len(self.DAplots) == 1:
self.lg.AddEntry(self.DAplots[0], self.DAplots[0].GetTitle(), 'p')
for hist in reversed(self.cumaddhist):
if len(hist.GetTitle()) != 0:
self.lg.AddEntry(hist, hist.GetTitle(), 'f')
for np in self.NOplots:
self.lg.AddEntry(np, np.GetTitle() + ' (Scaled)', 'l')
for op in self.Otherplots:
self.lg.AddEntry(op, op.GetTitle(), 'l')
if len(self.unctitle) != 0:
self.lg.AddEntry(self.errprint, self.unctitle, 'f')
self.lg.Draw()
self.settitle(title)
self.setchannel()
self.cmstext()
if logy == False:
self.cumaddhist[-1].GetYaxis().SetRangeUser(0, mymax * 1.5)
if logy == True:
self.cumaddhist[-1].GetYaxis().SetRangeUser(10, mymax * 50)
self.Pads[-2].SetLogy(True)
self.Pads[-2].RedrawAxis()
if ratio == True:
self.Pads[-1].cd()
self.Pads[-1].SetGridy()
self.DIVplots.append(TH1D(self.DAplots[0]))
if (xtitle != ''):
self.DIVplots[-1].GetXaxis().SetTitle(xtitle)
#self.DIVplots[-1].Divide(self.cumaddhist[-1])
printList = []
for b in range(1, self.DIVplots[-1].GetNbinsX() + 1):
if (self.cumaddhist[-1].GetBinContent(b) > 0.):
divval = self.DIVplots[-1].GetBinContent(
b) / self.cumaddhist[-1].GetBinContent(b)
divvalerr = self.DIVplots[-1].GetBinError(
b) / self.cumaddhist[-1].GetBinContent(b)
printList.append(divval)
self.DIVplots[-1].SetBinContent(b, divval)
#self.DIVplots[-1].SetBinError(b, divvalerr)
self.DIVplots[-1].SetBinError(
b,
math.sqrt(divvalerr**2 +
(self.cumaddhist[-1].GetBinError(b) /
self.cumaddhist[-1].GetBinContent(b))**2))
else:
printList.append(0)
self.DIVplots[-1].SetBinContent(b, 0.)
self.DIVplots[-1].SetBinError(b, 0.)
print printList
self.DIVplots[-1].SetMarkerSize(1.1)
if len(xlabels) != 0:
b = 0
for label in xlabels:
b += 1
self.DIVplots[-1].GetXaxis().SetBinLabel(b, label)
self.DIVplots[-1].Draw('E1X0same')
self.DIVplots[-1].GetXaxis().SetTitleOffset(3)
self.DIVplots[-1].GetYaxis().SetTitle('#frac{Data}{MC}')
self.DIVplots[-1].GetYaxis().SetTitleOffset(1.3)
self.DIVplots[-1].GetYaxis().SetRangeUser(0.5, 1.5)
self.DIVplots[-1].GetYaxis().SetNdivisions(105)
if rangemin != 0 or rangemax != 0:
self.DIVplots[-1].GetXaxis().SetRangeUser(rangemin, rangemax)
if self.unc:
self.errprintratio = TH1D(self.herr)
for b in range(1, self.errprintratio.GetNbinsX() + 1):
self.errprintratio.SetBinError(b,
self.herr.GetBinContent(b))
self.errprintratio.SetBinContent(b, 1.)
self.errprintratio.SetFillColor(1)
#self.errprintratio.SetFillStyle(3002)
self.errprintratio.SetFillStyle(3354)
#self.errprintratio.Draw('E2same')#//close box
if AsymmetricError:
self.gerratio = TGraphAsymmErrors(
len(xList), xList, array('d', [1] * len(xList)),
errleftList, errightList, reldwList, relupList)
self.gerratio.SetFillColor(1)
self.gerratio.SetFillStyle(3354)
self.gerratio.Draw('E2same')
else:
self.errprintratio.Draw('E2same') #//close box
self.DIVplots[-1].Draw('E1X0same')
self.Pads[-1].RedrawAxis()
return (self.Canvases[-1])
