def efficiencytracking():
hadron_list = ["pion", "proton", "electron", "muon"]
color_list = [1, 2, 4, 6]
fileo2 = TFile("../codeHF/AnalysisResults_O2.root")
c1 = TCanvas("c1", "A Simple Graph Example")
c1.SetCanvasSize(1500, 1500)
c1.cd()
gPad.SetLogx()
gPad.SetLogy()
eff_list = []
hempty = TH1F("hempty", ";p_{T};efficiency", 100, 0.001, 5.0)
hempty.Draw()
leg = TLegend(0.1, 0.7, 0.3, 0.9, "")
leg.SetFillColor(0)
for i, had in enumerate(hadron_list):
hnum = fileo2.Get("qa-tracking-efficiency-%s/num" % had)
hden = fileo2.Get("qa-tracking-efficiency-%s/den" % had)
hnum.Rebin(4)
hden.Rebin(4)
eff = TEfficiency(hnum, hden)
eff.SetLineColor(color_list[i])
eff_list.append(eff)
eff.Draw("same")
leg.AddEntry(eff_list[i], had)
leg.Draw()
c1.SaveAs("efficiency_tracking.pdf")
def draw_geff(t, title, h_bins, to_draw, den_cut, extra_num_cut,
opt = "", color = kBlue, marker_st = 1, marker_sz = 1.):
"""Make an efficiency plot"""
## total numerator selection cut
num_cut = AND(den_cut,extra_num_cut)
## PyROOT works a little different than ROOT when you are plotting
## histograms directly from tree. Hence, this work-around
nBins = int(h_bins[1:-1].split(',')[0])
minBin = float(h_bins[1:-1].split(',')[1])
maxBin = float(h_bins[1:-1].split(',')[2])
num = TH1F("num", "", nBins, minBin, maxBin)
den = TH1F("den", "", nBins, minBin, maxBin)
t.Draw(to_draw + ">>num", num_cut, "goff")
t.Draw(to_draw + ">>den", den_cut, "goff")
debug = False
if debug:
print("Denominator cut", den_cut, den.GetEntries())
print("Numerator cut", num_cut, num.GetEntries())
## check if the number of passed entries larger than total entries
doConsistencyCheck = False
if doConsistencyCheck:
for i in range(0,nBins):
print(i, num.GetBinContent(i), den.GetBinContent(i))
if num.GetBinContent(i) > den.GetBinContent(i):
print(">>>Error: passed entries > total entries")
eff = TEfficiency(num, den)
## plotting options
if not "same" in opt:
num.Reset()
num.GetYaxis().SetRangeUser(0.0,1.1)
num.SetStats(0)
num.SetTitle(title)
num.Draw()
eff.SetLineWidth(2)
eff.SetLineColor(color)
eff.SetMarkerStyle(marker_st)
eff.SetMarkerColor(color)
eff.SetMarkerSize(marker_sz)
eff.Draw(opt + " same")
SetOwnership(eff, False)
return eff
def makeEfficiency(passed, total, title, lineColor):
if TEfficiency.CheckConsistency(passed, total):
efficiency = TEfficiency(passed, total)
#title = std::regex_replace(title, std::regex("\\muCandGenEtaMuons"), "tagging efficiency");
efficiency.SetTitle(title)
efficiency.SetStatisticOption(6)
#TEfficiency.EStatOption.kBUniform
efficiency.SetPosteriorMode()
efficiency.SetLineColor(lineColor)
return efficiency
else:
print(
"makeEfficiency TEfficiency::CheckConsistency(*ptGenPtTTMuonNom, *ptGenPtTTMuonDenom) failed"
)
exit(1)
# ____________________________________________________________________________
# emtf_eff_vs_genpt_l1pt20
hname = "emtf_eff_vs_genpt_l1pt20"
h1a_denom = tfile.Get(hname + "_denom")
h1a_numer = tfile.Get(hname + "_numer")
h1b_denom = tfile.Get(hname2026_f(hname) + "_denom")
h1b_numer = tfile.Get(hname2026_f(hname) + "_numer")
print h1a_denom.GetEntries(), h1a_numer.GetEntries()
print h1b_denom.GetEntries(), h1b_denom.GetEntries()
h1a_eff = TEfficiency(h1a_numer, h1a_denom)
h1a_eff.SetStatisticOption(0) # kFCP
h1a_eff.SetConfidenceLevel(0.682689492137) # one sigma
h1a_eff.SetMarkerColor(632) # kRed
h1a_eff.SetLineColor(632) # kRed
h1a_eff.SetLineWidth(2)
h1b_eff = TEfficiency(h1b_numer, h1b_denom)
h1b_eff.SetStatisticOption(0) # kFCP
h1b_eff.SetConfidenceLevel(0.682689492137) # one sigma
h1b_eff.SetMarkerColor(600) # kBlue
h1b_eff.SetLineColor(600) # kBlue
h1b_eff.SetLineWidth(2)
gr = h1a_eff.CreateGraph()
gr.Draw("ap")
frame = gr.GetHistogram()
frame = frame.Clone(hname + "_frame")
frame.GetYaxis().SetTitle("#varepsilon")
frame.SetMinimum(0.0)
def MakeOneHist(dirName, histogramName):
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.697674)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
CMSLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
CMSLabel.SetTextAlign(32)
CMSLabel.SetTextFont(42)
CMSLabel.SetTextSize(0.697674)
CMSLabel.SetBorderSize(0)
CMSLabel.SetFillColor(0)
CMSLabel.SetFillStyle(0)
if makeFancy:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,"CMS Preliminary","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextSize(0.7)
LumiLabel.SetTextAlign(12)
else:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetTextAlign(32)
LumiLabel.SetTextFont(42)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
#legend coordinates, empirically determined :-)
x_left = 0.4
x_right = 0.7
y_min = 0.15
y_max = 0.3
Legend = TLegend(x_left,y_min,x_right,y_max)
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
HistogramClones = []
NBins = []
MaxXValues = []
MinXValues = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],source['dataset'])
inputFile = TFile(dataset_file)
NumHistogramObj = inputFile.Get(source['num_channel'] + "Plotter/" + dirName + "/" + histogramName)
if 'condor_dir_den' in source: # If specified, take the denominator histogram from a different condor directory.
dataset_fileDen = "condor/%s/%s.root" % (source['condor_dir_den'],source['dataset'])
inputFileDen = TFile(dataset_fileDen)
DenHistogramObj = inputFileDen.Get(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source['num_channel'] + "Plotter/" + dirName + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source['den_channel'] + "Plotter/" + dirName + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = NumHistogramObj.Clone()
if Histogram.Class().InheritsFrom("TH2"):
Histogram.SetName(Histogram.GetName() + "__" + source['dataset'])
Histogram.SetDirectory(0)
DenHistogram = DenHistogramObj.Clone()
DenHistogram.SetDirectory(0)
inputFile.Close()
nbinsN = Histogram.GetNbinsX()
nbinsD = DenHistogram.GetNbinsX()
if not noOverFlow:
# Add overflow
Histogram.SetBinContent( nbinsN, Histogram.GetBinContent(nbinsN) + Histogram.GetBinContent(nbinsN+1))
DenHistogram.SetBinContent(nbinsD, DenHistogram.GetBinContent(nbinsD) + DenHistogram.GetBinContent(nbinsD+1))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( nbinsN, math.sqrt(math.pow(Histogram.GetBinError(nbinsN),2) + math.pow(Histogram.GetBinError(nbinsN+1),2)))
DenHistogram.SetBinError(nbinsD, math.sqrt(math.pow(DenHistogram.GetBinError(nbinsD),2) + math.pow(DenHistogram.GetBinError(nbinsD+1),2)))
if not noUnderFlow:
# Add underflow
Histogram.SetBinContent( 1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0))
DenHistogram.SetBinContent(1, DenHistogram.GetBinContent(1) + DenHistogram.GetBinContent(0))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( 1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2)))
DenHistogram.SetBinError(1, math.sqrt(math.pow(DenHistogram.GetBinError(1), 2) + math.pow(DenHistogram.GetBinError(0), 2)))
if arguments.rebinFactor:
RebinFactor = int(arguments.rebinFactor)
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
if Histogram.GetNbinsX() >= RebinFactor*5 and Histogram.GetTitle().find("GenMatch") is -1 and not Histogram.Class().InheritsFrom("TH2"):
Histogram.Rebin(RebinFactor)
DenHistogram.Rebin(RebinFactor)
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex] + " width)"
else:
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
#check if bin content is consistent
TEfficiency.CheckConsistency(Histogram,DenHistogram)
for i in range(1,Histogram.GetNbinsX()+1):
if Histogram.GetBinContent(i) > DenHistogram.GetBinContent(i):
DenHistogram.SetBinContent(i,Histogram.GetBinContent(i))
#HistogramClone and HistogramClones only used for ratio plot
HistogramClone = Histogram.Clone()
HistogramClone.SetDirectory(0)
HistogramClone.Divide(DenHistogram)
Nbins = HistogramClone.GetNbinsX()
MaxXValue = HistogramClone.GetXaxis().GetBinLowEdge(Nbins+1)
MinXValue = HistogramClone.GetXaxis().GetBinLowEdge(1)
#this Histogram becomes the main TEfficiency
if Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
#using default methods (which give correct uncertainties)
#see https://root.cern.ch/doc/master/classTEfficiency.html (c.f. section IV)
Histogram = TEfficiency(Histogram,DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
if len(splitTitle) > 1:
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = splitTitle[0]
else:
histoTitle = ""
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
HistogramClones.append(HistogramClone)
NBins.append(Nbins)
MaxXValues.append(MaxXValue)
MinXValues.append(MinXValue)
### scaling histograms as per user's specifications
for histogram in Histograms:
if arguments.normalizeToUnitArea and histogram.Integral() > 0:
histogram.Scale(1./histogram.Integral())
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
legendIndex = legendIndex+1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 1.1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
addOneToRatio = -1
if arguments.addOneToRatio:
addOneToRatio = arguments.addOneToRatio
dontRebinRatio = -1
if arguments.dontRebinRatio:
dontRebinRatio = arguments.dontRebinRatio
ratioRelErrMax = -1
if arguments.ratioRelErrMax:
ratioRelErrMax = arguments.ratioRelErrMax
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
if makeRatioPlots or makeDiffPlots:
Canvas.SetFillStyle(0)
Canvas.Divide(1,2)
Canvas.cd(1)
gPad.SetPad(0,0.25,1,1)
gPad.SetMargin(0.15,0.05,0.01,0.07)
gPad.SetFillStyle(0)
gPad.Update()
gPad.Draw()
if arguments.setLogY:
gPad.SetLogy()
Canvas.cd(2)
gPad.SetPad(0,0,1,0.25)
#format: gPad.SetMargin(l,r,b,t)
gPad.SetMargin(0.15,0.05,0.4,0.01)
gPad.SetFillStyle(0)
gPad.SetGridy(1)
gPad.Update()
gPad.Draw()
Canvas.cd(1)
histCounter = 0
plotting_options = ""
if arguments.plot_hist:
plotting_options = "HIST"
h = TH2F("h1","",NBins[0],MinXValues[0],MaxXValues[0],110,0.,finalMax)
h.SetTitle(";"+xAxisLabel+";"+yAxisLabel)
h.Draw()
for histogram in Histograms:
if histogram.Class().InheritsFrom("TH2"):
histogram.SetTitle(histoTitle)
histogram.Draw("colz")
DatasetName = histogram.GetName()
DatasetName = DatasetName[DatasetName.rfind('__')+2:] # substring starting with the last underscore
DatasetLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,DatasetName,"NDC")
DatasetLabel.SetBorderSize(0)
DatasetLabel.SetFillColor(0)
DatasetLabel.SetFillStyle(0)
DatasetLabel.Draw()
outputFile.cd()
Canvas.SetName(histogram.GetName())
Canvas.Write()
else:
if histogram.InheritsFrom("TEfficiency") and histCounter==0:
plotting_options = "P SAME"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TEfficiency"):
plotting_options = "P" + " SAME"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,HistogramClones[0],HistogramClones[1])
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
if ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float (ratioRelErrMax))
if dontRebinRatio is True:
makeRatio = functools.partial (makeRatio, dontRebinRatio)
Comparison = makeRatio ()
elif makeDiffPlots:
Comparison = Histograms[0].Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("hist1-hist2")
Comparison.GetXaxis().SetTitle(xAxisLabel)
Comparison.GetYaxis().CenterTitle()
Comparison.GetYaxis().SetTitleSize(0.1)
Comparison.GetYaxis().SetTitleOffset(0.5)
Comparison.GetXaxis().SetTitleSize(0.15)
Comparison.GetYaxis().SetLabelSize(0.1)
Comparison.GetXaxis().SetLabelSize(0.15)
if makeRatioPlots:
RatioYRange = 1.15
if arguments.ratioYRange:
RatioYRange = float(arguments.ratioYRange)
if addOneToRatio == -1: # it gets initialized to this dummy value of -1
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
else:
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange + 1.0, RatioYRange + 1.0)
elif makeDiffPlots:
YMax = Comparison.GetMaximum()
YMin = Comparison.GetMinimum()
if YMax <= 0 and YMin <= 0:
Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
elif YMax >= 0 and YMin >= 0:
Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
else: #axis crosses y=0
if abs(YMax) > abs(YMin):
Comparison.GetYaxis().SetRangeUser(-1.2*YMax,1.2*YMax)
else:
Comparison.GetYaxis().SetRangeUser(-1.2*YMin,1.2*YMin)
Comparison.GetYaxis().SetNdivisions(205)
Comparison.Draw("E0")
outputFile.cd(dirName)
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
hAll.Sumw2()
hPass.Sumw2()
tree.Draw(var + '>>hAll', 'ht>450 && nBJets>1 && triggerBit[7]')
tree.Draw(
var + '>>hPass',
'ht>450 && nBJets>1 && triggerBit[7] && (triggerBit[0] || triggerBit[2])')
print hAll.Integral()
print hPass.Integral()
eff = TEfficiency('Efficiency', 'Efficiency', bins, xmin, xmax)
eff.SetPassedHistogram(hPass, "f")
eff.SetTotalHistogram(hAll, "f")
eff.SetMarkerColor(ROOT.kBlack)
eff.SetLineColor(ROOT.kBlack)
eff.SetMarkerStyle(20)
x = []
y = []
exl = []
exh = []
eyl = []
eyh = []
for i in xrange(hAll.GetNbinsX()):
x.append(hAll.GetBinCenter(i + 1))
exl.append(0)
exh.append(0)
y.append(eff.GetEfficiency(i + 1))
eyl.append(eff.GetEfficiencyErrorLow(i + 1))
def makeCombinedEtaPlot(self, tight=False):
hist = self.makeL1TimeVsEtaPlot(('tight_' if tight else '') +
'dtOnly_bxidVsEta')[2]
countsInL1 = []
for x in np.arange(-.95, 1.05, 0.1):
totalCounter = 0
zeroCount = 0
for y in range(-2, 3):
totalCounter += hist.GetBinContent(hist.FindBin(x, y))
if y == 0:
zeroCount = hist.GetBinContent(hist.FindBin(x, y))
countsInL1.append({
'total': totalCounter,
'zero': zeroCount,
'eta': x
})
#Graph for results
graph1 = TEfficiency(hist.GetName(), "", 8, -9.195, -.5)
graph2 = TEfficiency(hist.GetName(), "", 8, .5, 9.195)
for item in countsInL1:
if item['total'] == 0:
continue
print item['total'], item['zero'], item['eta']
if item['eta'] < 0:
graph1.SetTotalEvents(
graph1.FindFixBin(-0.5 + item['eta'] / 0.087),
int(item['total']))
graph1.SetPassedEvents(
graph1.FindFixBin(-0.5 + item['eta'] / 0.087),
int(item['zero']))
else:
graph2.SetTotalEvents(
graph2.FindFixBin(0.5 + item['eta'] / 0.087),
int(item['total']))
graph2.SetPassedEvents(
graph2.FindFixBin(0.5 + item['eta'] / 0.087),
int(item['zero']))
histHo = None
if tight:
histHo = self.plotTightHoTimeVsEta()[3][1]
else:
histHo = self.plotHoTimeVsEta()[3][1]
histHo.SetTitle(('Tight ' if tight else '') + 'Unmatched DT + HO')
canvas = TCanvas(
'combinedPlot' + ('Tight ' if tight else '') + hist.GetName(),
'combinedPlot')
canvas.cd().SetTopMargin(.15)
histHo.Draw('ap')
canvas.Update()
canvas.cd().SetTicks(0, 0)
histHo.SetMarkerStyle(2)
histHo.SetLineColor(colorRwthDarkBlue)
histHo.SetMarkerColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetRangeUser(-12, 12)
histHo.GetPaintedGraph().GetXaxis().SetLabelColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetTitleColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetAxisColor(colorRwthDarkBlue)
yMax = gPad.GetFrame().GetY2()
yMin = gPad.GetFrame().GetY1()
#Print average Fraction excluding iEta +/-2
x = Double(0)
y = Double(0)
mean = 0
var = 0
for i in range(0, histHo.GetPaintedGraph().GetN()):
histHo.GetPaintedGraph().GetPoint(i, x, y)
if abs(x) == 2:
continue
mean += y
var += histHo.GetPaintedGraph().GetErrorY(
i) * histHo.GetPaintedGraph().GetErrorY(i)
mean /= histHo.GetPaintedGraph().GetN() - 2
sigma = sqrt(var / (histHo.GetPaintedGraph().GetN() - 2))
self.debug(
"Average fraction excluding iEta +/- 2 %s: %5.2f%% +/- %5.2f%%" %
('[Tight]' if tight else '', mean * 100, sigma * 100))
nTotal = 0
nPassed = 0
for item in countsInL1:
if fabs(item['eta']) == 2 or fabs(item['eta'] == 0):
continue
nTotal += item['total']
nPassed += item['zero']
#Print again with ClopperPearson uncertainty, the counts are for L1!!!
mean = nPassed / nTotal * 100
sigmaPlus = TEfficiency.ClopperPearson(int(nTotal), int(nPassed), .68,
1) * 100 - mean
sigmaMinus = mean - TEfficiency.ClopperPearson(
int(nTotal), int(nPassed), .68, 0) * 100
#self.debug("Average fraction excluding iEta +/- 2 %s with Clop.Pear.: %5.2f%% +%5.2f%% -%5.2f%%"
# % ('[Tight]' if tight else '',mean,sigmaPlus,sigmaMinus))
#Left axis part
f1 = TF1("f1", "x", -0.87, 0)
A1 = TGaxis(-10, yMax, -0.5, yMax, "f1", 010, "-")
A1.SetLineColor(colorRwthRot)
A1.SetLabelColor(colorRwthRot)
A1.Draw()
#Right axis part
f2 = TF1("f2", "x", 0, 0.87)
A2 = TGaxis(0.5, yMax, 10, yMax, "f2", 010, "-")
A2.SetLineColor(colorRwthRot)
A2.SetLabelColor(colorRwthRot)
A2.Draw()
#Box for shading out 0
box = TBox(-.5, yMin, 0.5, yMax)
box.SetLineColor(colorRwthDarkGray)
box.SetFillColor(colorRwthDarkGray)
box.SetFillStyle(3013)
box.Draw('same')
#Left L1 eta
graph1.SetMarkerColor(colorRwthRot)
graph1.SetLineColor(colorRwthRot)
graph1.SetMarkerStyle(20)
graph1.Draw('same,p')
#Right L1Eta
graph2.SetMarkerColor(colorRwthRot)
graph2.SetLineColor(colorRwthRot)
graph2.SetMarkerStyle(20)
graph2.Draw('same,p')
#Label for extra axis
axisLabel = TPaveText(0.83, 0.85, 0.89, 0.9, "NDC")
axisLabel.AddText('#eta_{L1}')
axisLabel.SetBorderSize(0)
axisLabel.SetFillStyle(0)
axisLabel.SetTextColor(colorRwthRot)
axisLabel.SetTextSize(0.05)
axisLabel.Draw()
#Legend
legend = getLegend(x1=0.1, y1=0.1, x2=0.4, y2=.35)
legend.AddEntry(histHo, 'HO #in #pm12.5 ns', 'pe')
legend.AddEntry(graph1, ('Tight ' if tight else '') + 'L1 BXID = 0',
'pe')
legend.Draw()
canvas.Update()
self.storeCanvas(canvas,
"combinedFractionL1AndHo" +
('Tight' if tight else ''),
drawMark=False)
return histHo, graph1, canvas, A1, f1, A2, f2, box, graph2, axisLabel, legend
eff_e_shower_only = TEfficiency(h_correct_shower_only, h_total)
print "1 shower", h_correct_shower_only.Integral() / h_total.Integral()
eff_e_more_showers_only = TEfficiency(h_correct_more_showers_only, h_total)
print "1+ showers", h_correct_more_showers_only.Integral() / h_total.Integral()
eff_e.Draw("apl")
eff_e_more.Draw("pl same")
eff_e_shower_only.Draw("pl same")
eff_e_more_showers_only.Draw("pl same")
gPad.Update()
eff_e.GetPaintedGraph().SetMinimum(0.001)
eff_e.GetPaintedGraph().SetMaximum(1.3)
eff_e.GetPaintedGraph().GetXaxis().SetRangeUser(0, 3)
eff_e.SetLineColor(kBlue + 1)
eff_e.SetMarkerStyle(20)
eff_e_more.SetLineColor(kRed + 1)
eff_e_more.SetMarkerStyle(21)
eff_e_shower_only.SetLineColor(kBlue + 1)
eff_e_shower_only.SetLineStyle(2)
eff_e_shower_only.SetMarkerStyle(24)
eff_e_more_showers_only.SetLineColor(kRed + 1)
eff_e_more_showers_only.SetLineStyle(2)
eff_e_more_showers_only.SetMarkerStyle(25)
eff_e.SaveAs("plots/pandoraNu_eff.root")
eff_e_more.SaveAs("plots/pandoraNu_more_eff.root")
eff_e_shower_only.SaveAs("plots/pandoraNu_s_eff.root")
eff_e_more_showers_only.SaveAs("plots/pandoraNu_s_more_eff.root")
leg_e = TLegend(0.16, 0.76, 0.84, 0.84)
