def draw(cfg, isLog=False):
SetTdrStyle()
canvas.SetLogy(isLog)
fIn = [TFile.Open(f) for f in cfi.mergedInputFile]
for dIdx, data in enumerate(cfg['data']):
data['hist'] = [
fIn[data['fileIndex']].Get(cfg['name'] + postfix)
for postfix in data['postfix']
]
for hIdx, hist in enumerate(data['hist']):
hist.GetXaxis().SetTitle(cfg['xTitle'])
hist.GetYaxis().SetTitle(cfg['yTitle'])
if data['isData']:
hist.SetLineColor(data['fillColor'][hIdx][0])
hist.SetMarkerColor(data['fillColor'][hIdx][0])
hist.SetMarkerStyle(data['fillColor'][hIdx][1])
hist.SetMarkerSize(0.75)
else:
hist.SetLineColor(data['fillColor'][hIdx])
hist.SetMarkerColor(data['fillColor'][hIdx])
hist.SetFillColor(data['fillColor'][hIdx])
# Merge total plots
hTotalName = "{0}_total_{1}".format(cfg['name'], dIdx)
for hIdx, hist in enumerate(data['hist']):
if 'hTotal' in data.keys():
data['hTotal'].Add(hist)
else:
if data['isData']:
data['hTotal'] = hist.Clone(hTotalName)
data['hTotal'].SetLineColor(data['fillColor'][-1][0])
data['hTotal'].SetMarkerColor(data['fillColor'][-1][0])
data['hTotal'].SetMarkerStyle(data['fillColor'][-1][1])
else:
data['hTotal'] = THStack(hTotalName, "")
data['hTotal'].Add(hist)
# Post-processing of hTotal
for dIdx, data in enumerate(cfg['data']):
exec data['forceNorm']
if data['hTotal'].InheritsFrom("THStack"):
for h in data['hist']:
h.Scale(forceNormS)
else:
data['hTotal'].Scale(forceNormS)
if isLog:
data['hTotal'].SetMaximum(data['hTotal'].GetMaximum() * 100.)
if data['hTotal'].GetMinimum() * 10**5 > data['hTotal'].GetMaximum(
):
data['hTotal'].SetMinimum(data['hTotal'].GetMinimum() * 0.01)
else:
data['hTotal'].SetMinimum(0)
data['hTotal'].SetMaximum(data['hTotal'].GetMaximum() * 1.5)
# Create ratio plots
if 'hRatio' in cfg.keys() and data['hTotal'].InheritsFrom("TH1"):
cfg['hRatio'].append([
TRatioPlot(cfg['data'][0]['hTotal'], data['hTotal'], opt)
for opt in cfg['ratioOpts']
])
else:
cfg['hRatio'] = [
[],
]
# Legend
stLeg = TLegend(*cfg['stLegPos'])
setDefaultLegend(stLeg)
for data in cfg['data']:
if data['isData']:
stLeg.AddEntry(data['hTotal'], data['legend'][0], "ep")
else:
for hIdx, hist in enumerate(data['hist']):
stLeg.AddEntry(hist, data['legend'][hIdx], "f")
# Draw stack plots
for dIdx, data in enumerate(cfg['data']):
if dIdx == 0:
data['hTotal'].Draw(data['drawOpt'])
data['hTotal'].GetXaxis().SetTitle(cfg['xTitle'])
data['hTotal'].GetYaxis().SetTitle(cfg['yTitle'])
else:
data['hTotal'].Draw("SAME " + data['drawOpt'])
stLeg.Draw()
drawLatexCMS(x=0.10, y=0.91)
drawLatexLumi(x=0.89, y=0.91)
drawLatexJetType(x=0.50, y=0.86)
drawLatexSel(x=0.50, y=0.81)
if "stExtra" in cfg.keys():
exec cfg['stExtra']
# Print files
for oFormat in cfi.outputFormats:
canvas.Update()
canvas.Print(
os.path.join(
cfi.outputDir,
"hstack_{0}{1}.{2}".format(cfg['name'],
"_log" if isLog else "", oFormat)))
# Legend
rpLeg = TLegend(stLeg)
rpLeg.SetX1NDC(cfg['rpLegPos'][0])
rpLeg.SetY1NDC(cfg['rpLegPos'][1])
rpLeg.SetX2NDC(cfg['rpLegPos'][2])
rpLeg.SetY2NDC(cfg['rpLegPos'][3])
for oIdx, rpOpt in enumerate(cfg['ratioOpts']):
for dIdx, rp in enumerate(cfg['hRatio'][1:], start=1):
rp[oIdx].SetH1DrawOpt(cfg['data'][0]['drawOpt'])
rp[oIdx].SetH2DrawOpt(cfg['data'][dIdx]['drawOpt'])
rp[oIdx].SetGraphDrawOpt("P Z 0 2")
rp[oIdx].Draw()
rp[oIdx].GetXaxis().SetTitle(cfg['xTitle'])
rp[oIdx].GetUpperRefYaxis().SetTitle(cfg['yTitle'])
rp[oIdx].GetLowerRefYaxis().SetTitle("Ratio")
rp[oIdx].GetLowerRefYaxis().SetNdivisions(505)
rp[oIdx].GetLowerRefYaxis().SetLabelSize(0.03)
rp[oIdx].GetLowerRefGraph().SetMaximum(1.5)
rp[oIdx].GetLowerRefGraph().SetMinimum(0.5)
rp[oIdx].GetLowerRefGraph().SetFillColor(
cfg['data'][dIdx]['fillColor'][-1][0])
rp[oIdx].GetLowerRefGraph().SetLineColor(
cfg['data'][dIdx]['fillColor'][-1][0])
rp[oIdx].GetLowerRefGraph().SetMarkerColor(
cfg['data'][dIdx]['fillColor'][-1][0])
rp[oIdx].GetLowerRefGraph().SetMarkerStyle(
cfg['data'][dIdx]['fillColor'][-1][1])
if "rpExtra" in cfg.keys():
exec cfg['rpExtra']
cfg['hRatio'][1][oIdx].Draw()
for dIdx, rp in enumerate(cfg['hRatio'][2:], start=2):
cfg['hRatio'][1][oIdx].GetUpperPad().cd()
cfg['data'][dIdx]['hTotal'].Draw(cfg['data'][dIdx]['drawOpt'] +
" SAME")
cfg['hRatio'][1][oIdx].GetLowerPad().cd()
rp[oIdx].GetLowerRefGraph().Draw("0 P SAME")
canvas.cd()
rpLeg.Draw()
drawLatexCMS(x=0.10, y=0.93)
drawLatexLumi(x=0.88, y=0.93)
drawLatexJetType(x=0.50, y=0.89)
drawLatexSel(x=0.50, y=0.84)
for oFormat in cfi.outputFormats:
canvas.Update()
canvas.Print(
os.path.join(
cfi.outputDir,
"hratio_{0}_{1}{2}.{3}".format(rpOpt, cfg['name'],
"_log" if isLog else "",
oFormat)))
pass
def sobWeightedPlot(self,
fileName,
datasetName,
channel,
cat,
log,
mass,
tanb,
blind,
sob=False):
# print 'yuta', channel, cat
c = TCanvas(fileName, '', 600, 600)
c.cd()
if log: c.SetLogy(1)
f = self.openTFile('Plot_' + fileName + '.root')
isEMSM = fileName.find('SM') != -1 and fileName.find('em') != -1
isETSM = fileName.find('SM') != -1 and fileName.find('et') != -1
samples = ['ggH', 'Ztt', 'signal', 'data_obs', 'ttbar', 'EWK', 'Fakes']
if isEMSM:
samples.append('ggH_hww')
if isETSM:
samples.append('Zee')
dataGraph = self.tfileGet(f, 'Graph_from_data_obs')
histDict = {}
for sample in samples:
histDict[sample] = self.tfileGet(f, sample)
# print 'check :', sample, histDict[sample].GetSumOfWeights()
if not histDict[sample]:
print 'Missing histogram', sample, 'in file', 'Plot_' + fileName + '.root'
# original for plots
xminInset = 60 # 0
xmaxInset = 179 # 340 (for full range)
# all range
# xminInset = 0 # 0
# xmaxInset = 350 # 340 (for full range)
# xminInset = 40 # 0
# xmaxInset = 200 # 340 (for full range)
# xminInset = 120 # 0
# xmaxInset = 251 # 340 (for full range)
if tanb > 0:
xminInset = mass - 100
xmaxInset = mass + 100
if sob:
xminInset = 0.4
xmaxInset = 0.7
ztt = histDict['Ztt']
ggH = histDict['ggH']
data = histDict['data_obs']
# This is to fix a weird plotting bug
if sob:
new_data = TH1F('new_data', '', ggH.GetNbinsX(), 0., 0.7)
for i in range(1, new_data.GetNbinsX() + 1):
new_data.SetBinContent(i, data.GetBinContent(i))
# print data.GetBinContent(i)
data = new_data
ggH_hww = 0
zee = 0
signal = histDict['signal']
if isEMSM:
ggH_hww = histDict['ggH_hww']
if isETSM:
print 'retrieve Zee'
zee = histDict['Zee']
tt = histDict['ttbar']
ewk = histDict['EWK']
fakes = histDict['Fakes']
ztt.GetYaxis().SetRangeUser(0., 1.3 * self.findMaxY(data, 0))
if log:
ztt.GetYaxis().SetRangeUser(0.001, 50. * self.findMaxY(data, 0))
ztt.GetXaxis().SetTitle('#bf{m_{#tau#tau} [GeV]}')
ztt.GetYaxis().SetTitle('#bf{S/B Weighted dN/dm_{#tau#tau} [1/GeV]}')
if tanb > 0. and not log:
ztt.GetXaxis().SetRangeUser(0., mass + 200.)
if sob:
ztt.GetXaxis().SetTitle('S/(S+B)')
ztt.GetYaxis().SetTitle('Events')
ztt.SetTitleOffset(1.3, 'Y')
ztt.SetTitleOffset(1., 'X')
ztt.GetYaxis().SetNdivisions(505)
ztt.SetNdivisions(505)
for b in range(0, signal.GetNbinsX() + 2):
if signal.GetBinCenter(
b) < xminInset or xmaxInset < signal.GetBinCenter(b):
signal.SetBinContent(b, 0.)
signal.SetBinError(b, 0.)
signal.SetName('sig')
signal.SetFillStyle(3353) # 1001=solid , 3004,3005=diagonal
signal.SetFillColor(2)
signal.SetLineColor(2)
signal.SetLineStyle(1)
signal.SetLineWidth(0)
ggH.SetBinContent(0, 0) # remove red line on top of y axis in plot
ggH.SetBinContent(ggH.GetNbinsX() + 1, 0)
ggH.SetBinError(0, 0)
ggH.SetBinError(ggH.GetNbinsX() + 1, 0)
ggH.SetName('ggH')
ggH.SetFillStyle(3353) # 1001=solid , 3004,3005=diagonal
ggH.SetFillColor(2)
ggH.SetLineColor(2)
ggH.SetLineStyle(1)
ggH.SetLineWidth(0)
if isEMSM:
errorBand = TH1F(ggH_hww)
else:
errorBand = TH1F(ztt)
errorBand.SetName("errorBand")
errorBand.SetMarkerSize(0)
errorBand.SetFillColor(1)
errorBand.SetFillStyle(3013)
errorBand.SetLineWidth(1)
legend = TLegend()
mssmLabel = ''
if tanb > 0:
mssmLabel = "tan#beta={tanb}".format(tanb=tanb)
higgsLabel = "H(125 GeV)#rightarrow#tau#tau"
if tanb > 0:
higgsLabel = "H(125 GeV)#rightarrow#tau#tau"
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetBorderSize(0)
legend.AddEntry(ggH, higgsLabel, "F")
if tanb > 0:
legend.AddEntry(TObject(0), mssmLabel, "")
legend.AddEntry(data, "observed", "LP")
if isEMSM:
legend.AddEntry(ggH_hww, "H(125 GeV)#rightarrowWW", "F")
legend.AddEntry(ztt, "Z#rightarrow#tau#tau", "F")
legend.AddEntry(tt, "t#bar{t}", "F")
if isETSM:
legend.AddEntry(zee, "Z#rightarrowee", "F")
legend.AddEntry(ewk, "electroweak", "F")
legend.AddEntry(fakes, "QCD", "F")
legend.SetX1NDC(0.63)
legend.SetX2NDC(1.05)
legend.SetY1NDC(0.25)
legend.SetY2NDC(0.46)
if log:
legend.SetX1NDC(0.18)
legend.SetX2NDC(0.60)
legend.SetY1NDC(0.17)
legend.SetY2NDC(0.38)
legend.SetTextSize(.028)
legend.SetTextAlign(12)
if isEMSM:
dataDiff = self.diffPlot(data, ggH_hww, 1)
dataDiffGraph = self.diffGraph(dataGraph, ggH_hww, 1)
errBand = self.getErrorBand(ggH_hww)
else:
dataDiff = self.diffPlot(data, ztt, 1)
dataDiffGraph = self.diffGraph(dataGraph, ztt, 1)
errBand = self.getErrorBand(ztt)
errBand.SetFillStyle(
3013
) # 1001=solid , 3004,3005=diagonal, 3013=hatched official for H.tau tau
errBand.SetFillColor(1)
errBand.SetLineStyle(1)
errBand.SetLineColor(1)
errBand.SetLineWidth(1)
errBandFrame = TH1F(
'errBandFrame', '',
int((xmaxInset - xminInset) / dataDiff.GetBinWidth(1)), xminInset,
xmaxInset)
errBandFrame.GetYaxis().SetTitle("")
errBandFrame.GetYaxis().SetRangeUser(
-1.1 * self.findMinY(dataDiff, blind, 0, xminInset, xmaxInset),
2.0 * self.findMaxY(dataDiff, blind, 0, xminInset, xmaxInset))
# errBandFrame.GetYaxis().SetRangeUser(-1.*self.findMinY(dataDiff,blind,0,xminInset,xmaxInset),1.1*self.findMaxY(dataDiff,blind,0,xminInset,xmaxInset)) # good !
# errBandFrame.GetYaxis().SetRangeUser(-0.2*self.findMinY(dataDiff,blind,0,xminInset,xmaxInset),0.5*self.findMaxY(dataDiff,blind,0,xminInset,xmaxInset))
print 'Yuta', channel, cat
if (channel == 'e#tau_{h}' and cat == 'vbf') or (channel == 'e#tau_{h}'
and cat == ''):
print 'enter'
errBandFrame.GetYaxis().SetRangeUser(
-2. * self.findMinY(dataDiff, blind, 0, xminInset, xmaxInset),
2.0 * self.findMaxY(dataDiff, blind, 0, xminInset, xmaxInset))
errBandFrame.GetYaxis().SetNdivisions(5)
errBandFrame.GetYaxis().SetLabelSize(0.06)
errBandFrame.GetXaxis().SetTitle("#bf{m_{#tau#tau} [GeV]} ")
errBandFrame.GetXaxis().SetTitleColor(kBlack)
errBandFrame.GetXaxis().SetTitleSize(0.07)
errBandFrame.GetXaxis().SetTitleOffset(0.85)
errBandFrame.GetXaxis().SetLabelSize(0.06)
errBandFrame.GetXaxis().SetNdivisions(506)
# errBandFrame.SetNdivisions(505)
legendDiff = TLegend()
legendDiff.SetFillStyle(0)
legendDiff.SetFillColor(0)
legendDiff.SetBorderSize(0)
legendDiff.AddEntry(signal, higgsLabel, "F")
if tanb > 0:
legendDiff.AddEntry(TObject(0), mssmLabel,
'') # That might not work in python
# legendDiff.AddEntry(dataDiff,"Data - Background","LP")
legendDiff.AddEntry(dataDiffGraph, "Data - Background", "LEP")
legendDiff.AddEntry(errBand, "Bkg. Uncertainty", "F")
legendDiff.SetX1NDC(0.45)
legendDiff.SetX2NDC(0.88)
legendDiff.SetY1NDC(0.67)
legendDiff.SetY2NDC(0.88)
if dataDiff.GetBinContent(dataDiff.FindBin(mass)) < 0.:
legendDiff.SetX1NDC(0.45)
legendDiff.SetX2NDC(0.88)
legendDiff.SetY1NDC(0.24)
legendDiff.SetY2NDC(0.45)
legendDiff.SetTextSize(.045)
legendDiff.SetTextAlign(12)
padBack = TPad(
"padBack", "padBack", 0.57, 0.58, 0.975,
0.956) # TPad must be created after TCanvas otherwise ROOT crashes
padBack.SetFillColor(0)
pad = TPad(
"diff", "diff", 0.45, 0.5, 0.9765,
0.957) # TPad must be created after TCanvas otherwise ROOT crashes
pad.cd()
pad.SetFillColor(0)
pad.SetFillStyle(0)
errBandFrame.Draw()
errBand.Draw("e2lsame")
signal.Draw("histsame")
line = TLine()
line.DrawLine(xminInset, 0, xmaxInset, 0)
# dataDiff.Draw("pe same")
if blind == False:
self.HideBin(dataDiffGraph)
dataDiffGraph.SetMarkerSize(0.5)
dataDiffGraph.Draw('pe same')
for ibin in range(0, dataDiffGraph.GetN()):
x = Double(0.)
y = Double(0.)
dataDiffGraph.GetPoint(ibin, x, y)
print 'Yuta_bin=', ibin, 'x=', x, 'y=', y, dataDiffGraph.GetErrorYhigh(
ibin), dataDiffGraph.GetErrorYlow(ibin)
print 'Yuta_error=', ibin, errBand.GetXaxis().GetBinCenter(
ibin + 1), errBand.GetBinError(ibin + 1)
legendDiff.Draw()
pad.RedrawAxis()
c.cd()
ztt.Draw("hist")
ggH.Draw("hist same")
if isEMSM:
ggH_hww.Draw("hist same")
ztt.Draw("hist same")
errorBand.Draw("e2 same")
tt.Draw("hist same")
if isETSM:
zee.Draw("hist same")
ewk.Draw("hist same")
fakes.Draw("hist same")
# data.Draw("pe same")
dataGraph.SetMarkerSize(1)
dataGraph.Draw('PE same')
if blind == False:
self.HideBin(dataGraph)
print '#####', data.Integral(), data.GetBinContent(1)
legend.Draw()
c.RedrawAxis()
padBack.Draw() # clear the background axe
pad.Draw()
if log: c.SetLogy(1)
self.CMSPrelim(c, datasetName, channel, cat)
savepath = 'figure/Plot_' + fileName
if cat == '':
savepath = savepath + '.pdf'
else:
savepath = savepath + '_' + cat + '.pdf'
# c.Print('figure/Plot_'+fileName+".eps")
# c.Print('figure/Plot_'+fileName+".png")
# c.Print('figure/Plot_'+fileName+".pdf")
c.Print(savepath)
c.Close()
def MakeOneDHist(pathToDir, distribution):
numFittingSamples = 0
HeaderLabel = TPaveLabel(header_x_left, header_y_bottom, header_x_right,
header_y_top, HeaderText, "NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
LumiLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom, topLeft_x_right,
topLeft_y_top, LumiText, "NDC")
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
NormLabel = TPaveLabel()
NormLabel.SetDrawOption("NDC")
NormLabel.SetX1NDC(topLeft_x_left)
NormLabel.SetX2NDC(topLeft_x_right)
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormText = ""
if arguments.normalizeToUnitArea:
NormText = "Scaled to unit area"
elif arguments.normalizeToData:
NormText = "MC scaled to data"
NormLabel.SetLabel(NormText)
YieldsLabel = TPaveText(0.39, 0.7, 0.59, 0.9, "NDC")
YieldsLabel.SetBorderSize(0)
YieldsLabel.SetFillColor(0)
YieldsLabel.SetFillStyle(0)
YieldsLabel.SetTextAlign(12)
RatiosLabel = TPaveText()
RatiosLabel.SetDrawOption("NDC")
RatiosLabel.SetBorderSize(0)
RatiosLabel.SetFillColor(0)
RatiosLabel.SetFillStyle(0)
RatiosLabel.SetTextAlign(32)
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
fittingIntegral = 0
scaleFactor = 1
HistogramsToFit = []
TargetDataset = distribution['target_dataset']
FittingLegendEntries = []
DataLegendEntries = []
FittingHistogramDatasets = []
Stack_list = []
Stack_list.append(THStack("stack_before", distribution['name']))
Stack_list.append(THStack("stack_after", distribution['name']))
fileName = condor_dir + "/" + distribution['target_dataset'] + ".root"
if not os.path.exists(fileName):
return
inputFile = TFile(fileName)
if inputFile.IsZombie() or not inputFile.GetNkeys():
return
Target = inputFile.Get("OSUAnalysis/" + distribution['channel'] + "/" +
distribution['name']).Clone()
Target.SetDirectory(0)
inputFile.Close()
Target.SetMarkerStyle(20)
Target.SetMarkerSize(0.8)
Target.SetFillStyle(0)
Target.SetLineColor(colors[TargetDataset])
Target.SetLineStyle(1)
Target.SetLineWidth(2)
targetIntegral = Target.Integral()
if (arguments.normalizeToUnitArea and Target.Integral() > 0):
Target.Scale(1. / Target.Integral())
if arguments.rebinFactor:
RebinFactor = int(arguments.rebinFactor)
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
if Target.GetNbinsX() >= RebinFactor * 5 and Target.GetName().find(
"GenMatch") is -1:
Target.Rebin(RebinFactor)
### formatting target histogram and adding to legend
legendIndex = 0
Legend.AddEntry(Target, labels[TargetDataset], "LEP")
legendIndex = legendIndex + 1
if not outputFile.Get("OSUAnalysis"):
outputFile.mkdir("OSUAnalysis")
if not outputFile.Get("OSUAnalysis/" + distribution['channel']):
outputFile.Get("OSUAnalysis").mkdir(distribution['channel'])
for sample in distribution[
'datasets']: # loop over different samples requested to be fit
dataset_file = "%s/%s.root" % (condor_dir, sample)
inputFile = TFile(dataset_file)
HistogramObj = inputFile.Get(pathToDir + "/" +
distribution['channel'] + "/" +
distribution['name'])
if not HistogramObj:
print "WARNING: Could not find histogram " + pathToDir + "/" + distribution[
'channel'] + "/" + distribution[
'name'] + " in file " + dataset_file + ". Will skip it and continue."
continue
Histogram = HistogramObj.Clone()
Histogram.SetDirectory(0)
inputFile.Close()
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.GetName(
).find("GenMatch") is -1:
Histogram.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 = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(
1)) + " " + xAxisLabel[unitBeginIndex + 1:unitEndIndex]
else:
yAxisLabel = "Entries per bin (" + str(
Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if not arguments.makeFancy:
histoTitle = Histogram.GetTitle()
else:
histoTitle = ""
legLabel = labels[sample]
if (arguments.printYields):
yieldHist = Histogram.Integral()
legLabel = legLabel + " (%.1f)" % yieldHist
FittingLegendEntries.append(legLabel)
if (types[sample] == "bgMC"):
numFittingSamples += 1
fittingIntegral += Histogram.Integral()
Histogram.SetLineStyle(1)
if (arguments.noStack):
Histogram.SetFillStyle(0)
Histogram.SetLineColor(colors[sample])
Histogram.SetLineWidth(2)
else:
Histogram.SetFillStyle(1001)
Histogram.SetFillColor(colors[sample])
Histogram.SetLineColor(1)
Histogram.SetLineWidth(1)
elif (types[sample] == "signalMC"):
numFittingSamples += 1
Histogram.SetFillStyle(0)
Histogram.SetLineColor(colors[sample])
Histogram.SetLineStyle(1)
Histogram.SetLineWidth(2)
if (arguments.normalizeToUnitArea and Histogram.Integral() > 0):
Histogram.Scale(1. / Histogram.Integral())
HistogramsToFit.append(Histogram)
FittingHistogramDatasets.append(sample)
#scaling histograms as per user's specifications
if targetIntegral > 0 and fittingIntegral > 0:
scaleFactor = targetIntegral / fittingIntegral
for fittingHist in HistogramsToFit:
if arguments.normalizeToData:
fittingHist.Scale(scaleFactor)
if arguments.normalizeToUnitArea and not arguments.noStack and fittingIntegral > 0:
fittingHist.Scale(1. / fittingIntegral)
elif arguments.normalizeToUnitArea and arguments.noStack and fittingHist.Integral(
) > 0:
fittingHist.Scale(1. / fittingHist.Integral())
def fitf(x, par):
xBin = HistogramsToFit[0].FindBin(x[0])
value = 0.0
for i in range(0, len(HistogramsToFit)):
value += par[i] * HistogramsToFit[i].GetBinContent(xBin) + par[
i +
len(HistogramsToFit)] * HistogramsToFit[i].GetBinError(xBin)
return value
lowerLimit = Target.GetBinLowEdge(1)
upperLimit = Target.GetBinLowEdge(Target.GetNbinsX()) + Target.GetBinWidth(
Target.GetNbinsX())
if 'lowerLimit' in distribution:
lowerLimit = distribution['lowerLimit']
if 'upperLimit' in distribution:
upperLimit = distribution['upperLimit']
func = TF1("fit", fitf, lowerLimit, upperLimit, 2 * len(HistogramsToFit))
for i in range(0, len(HistogramsToFit)):
if 'fixed_datasets' in distribution and distribution['datasets'][
i] in distribution['fixed_datasets']:
func.FixParameter(i, 1.0)
else:
func.SetParameter(i, 1.0)
# func.SetParLimits (i, 0.0, 1.0e2) # comment this out so we don't have to pre-normalize the QCD input sample
func.SetParName(i, labels[FittingHistogramDatasets[i]])
shiftedScaleFactors = []
if arguments.parametricErrors:
# loop over all input histograms and shift them +- 1 sigma
for i in range(0, len(HistogramsToFit)):
sfs = []
# -1 => -1 sigma, +1 => +1 sigma
for j in [-1, 1]:
# loop over the parameters holding the errors for each dataset, fixing all to 0
for k in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
func.FixParameter(k, 0)
# fix the error of the dataset of interest to +-1
func.FixParameter(i + len(HistogramsToFit), j)
# perform new fit
for k in range(0, distribution['iterations'] - 1):
if j == -1:
print "Scale down " + labels[FittingHistogramDatasets[
i]] + " iteration " + str(k + 1) + "..."
if j == 1:
print "Scale up " + labels[FittingHistogramDatasets[
i]] + " iteration " + str(k + 1) + "..."
Target.Fit("fit", "QEMR0")
Target.Fit("fit", "VEMR0")
# save the new scale factors for each dataset
for k in range(0, len(HistogramsToFit)):
sfs.append(func.GetParameter(k))
shiftedScaleFactors.append(sfs)
# reset the parameters with the errors of each dataset to 0
for i in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
func.FixParameter(i, 0)
# do the fit to get the central values
for i in range(0, distribution['iterations'] - 1):
print "Iteration " + str(i + 1) + "..."
Target.Fit("fit", "QEMR0")
Target.Fit("fit", "VEMR0")
if arguments.parametricErrors:
# make a list of the largest errors on each contribution by shifting any other contribution
parErrors = []
# loop over all the datasets
for i in range(0, len(HistogramsToFit)):
centralValue = func.GetParameter(i)
maxError = 0
# find the maximum deviation from the central value and save that
for shiftedScaleFactor in shiftedScaleFactors[i]:
currentError = abs(shiftedScaleFactor - centralValue)
if currentError > maxError:
maxError = currentError
parErrors.append(maxError)
finalMax = 0
if not arguments.noStack:
for fittingHist in HistogramsToFit:
finalMax += fittingHist.GetMaximum()
else:
for fittingHist in HistogramsToFit:
if (fittingHist.GetMaximum() > finalMax):
finalMax = fittingHist.GetMaximum()
if (Target.GetMaximum() > finalMax):
finalMax = Target.GetMaximum()
Target.SetMaximum(1.1 * finalMax)
Target.SetMinimum(0.0001)
Canvas = TCanvas(distribution['name'] + "_FitFunction")
Canvas.cd(1)
Target.Draw()
func.Draw("same")
outputFile.cd("OSUAnalysis/" + distribution['channel'])
Canvas.Write()
if arguments.savePDFs:
if histogram == input_histograms[0]:
Canvas.Print(pdfFileName + "(", "pdf")
else:
Canvas.Print(pdfFileName, "pdf")
Target.SetStats(0)
### formatting bgMC histograms and adding to legend
legendIndex = numFittingSamples - 1
for Histogram in reversed(HistogramsToFit):
if (arguments.noStack):
Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "L")
else:
Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "F")
legendIndex = legendIndex - 1
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
### Draw everything to the canvases !!!!
for i in range(0, 2): # 0 => before, 1 => after
integrals = []
ratios = []
errors = []
if i == 1:
# loop over each dataset, saving it's yield and the errors on it
for j in range(0, len(HistogramsToFit)):
integrals.append(HistogramsToFit[j].Integral())
HistogramsToFit[j].Scale(func.GetParameter(j))
ratios.append(func.GetParameter(j))
errors.append(func.GetParError(j))
for fittingHist in HistogramsToFit:
if not arguments.noStack:
Stack_list[i].Add(fittingHist)
#creating the histogram to represent the statistical errors on the stack
if not arguments.noStack:
ErrorHisto = HistogramsToFit[0].Clone("errors")
ErrorHisto.SetFillStyle(3001)
ErrorHisto.SetFillColor(13)
ErrorHisto.SetLineWidth(0)
if i == 1:
Legend.AddEntry(ErrorHisto, "Stat. Errors", "F")
for Histogram in HistogramsToFit:
if Histogram is not HistogramsToFit[0]:
ErrorHisto.Add(Histogram)
if i == 0:
Canvas = TCanvas(distribution['name'] + "_Before")
if i == 1:
Canvas = TCanvas(distribution['name'] + "_After")
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)
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
if numFittingSamples is not 0 and not arguments.noStack:
finalMax = ErrorHisto.GetMaximum() + ErrorHisto.GetBinError(
ErrorHisto.GetMaximumBin())
else:
for bgMCHist in HistogramsToFit:
if (bgMCHist.GetMaximum() > finalMax):
finalMax = bgMCHist.GetMaximum()
if (Target.GetMaximum() > finalMax):
finalMax = Target.GetMaximum() + Target.GetBinError(
Target.GetMaximumBin())
finalMax = 1.15 * finalMax
if arguments.setYMax:
finalMax = float(arguments.setYMax)
if not arguments.noStack: # draw stacked background samples
Stack_list[i].SetTitle(histoTitle)
Stack_list[i].Draw("HIST")
Stack_list[i].GetXaxis().SetTitle(xAxisLabel)
Stack_list[i].GetYaxis().SetTitle(yAxisLabel)
Stack_list[i].SetMaximum(finalMax)
Stack_list[i].SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
Stack_list[i].GetHistogram().GetXaxis().SetLabelSize(0)
#draw shaded error bands
ErrorHisto.Draw("A E2 SAME")
else: #draw the unstacked backgrounds
HistogramsToFit[0].SetTitle(histoTitle)
HistogramsToFit[0].Draw("HIST")
HistogramsToFit[0].GetXaxis().SetTitle(xAxisLabel)
HistogramsToFit[0].GetYaxis().SetTitle(yAxisLabel)
HistogramsToFit[0].SetMaximum(finalMax)
HistogramsToFit[0].SetMinimum(yAxisMin)
for bgMCHist in HistogramsToFit:
bgMCHist.Draw("A HIST SAME")
Target.Draw("A E X0 SAME")
#legend coordinates, empirically determined :-)
x_left = 0.6761745
x_right = 0.9328859
x_width = x_right - x_left
y_max = 0.9
entry_height = 0.05
if (numFittingSamples is not 0): #then draw the data & bgMC legend
numExtraEntries = 2 # count the target and (lack of) title
Legend.SetX1NDC(x_left)
numExtraEntries = numExtraEntries + 1 # count the stat. errors entry
Legend.SetY1NDC(y_max - entry_height *
(numExtraEntries + numFittingSamples))
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
RatiosLabel.SetX1NDC(x_left - 0.1)
RatiosLabel.SetX2NDC(x_right)
RatiosLabel.SetY2NDC(Legend.GetY1NDC() - 0.1)
RatiosLabel.SetY1NDC(RatiosLabel.GetY2NDC() - entry_height *
(numFittingSamples))
# Deciding which text labels to draw and drawing them
drawLumiLabel = False
drawNormLabel = False
offsetNormLabel = False
drawHeaderLabel = False
if not arguments.normalizeToUnitArea: #don't draw the lumi label if there's no data and it's scaled to unit area
drawLumiLabel = True
# move the normalization label down before drawing if we drew the lumi. label
offsetNormLabel = True
if arguments.normalizeToUnitArea or arguments.normalizeToData:
drawNormLabel = True
if arguments.makeFancy:
drawHeaderLabel = True
drawLumiLabel = False
# now that flags are set, draw the appropriate labels
if drawLumiLabel:
LumiLabel.Draw()
if drawNormLabel:
if offsetNormLabel:
NormLabel.SetY1NDC(topLeft_y_bottom - topLeft_y_offset)
NormLabel.SetY2NDC(topLeft_y_top - topLeft_y_offset)
else:
NormLabel.SetY1NDC(topLeft_y_bottom)
NormLabel.SetY2NDC(topLeft_y_top)
NormLabel.Draw()
if drawHeaderLabel:
HeaderLabel.Draw()
YieldsLabel.Clear()
mcYield = Stack_list[i].GetStack().Last().Integral()
dataYield = Target.Integral()
if i == 0:
YieldsLabel.AddText("Before Fit to Data")
if i == 1:
YieldsLabel.AddText("After Fit to Data")
YieldsLabel.AddText("data yield: " + '%.1f' % dataYield)
YieldsLabel.AddText("bkgd yield: " + '%.1f' % mcYield)
YieldsLabel.AddText("data/bkgd: " + '%.2f' % (dataYield / mcYield))
if i == 1:
for j in range(0, len(FittingLegendEntries)):
if abs(ratios[j] - 1) < 0.001 and abs(
errors[j]
) < 0.001: #then it probably was held fixed
continue
if arguments.showFittedYields:
yield_ = ratios[j] * integrals[j]
yielderror_ = errors[j] * yield_
text = FittingLegendEntries[
j] + " yield: " + '%.0f' % yield_ + ' #pm %.0f' % yielderror_
else:
text = FittingLegendEntries[
j] + " ratio: " + '%.2f' % ratios[
j] + ' #pm %.2f' % errors[j]
text = text + " (fit)"
if arguments.parametricErrors:
yield_ = ratios[j] * integrals[j]
yieldParError_ = parErrors[j] * yield_
if arguments.showFittedYields:
text += ' #pm %.2f' % yieldParError_
else:
text += ' #pm %.2f' % parErrors[j]
text = text + " (sys)"
RatiosLabel.AddText(text)
YieldsLabel.Draw()
RatiosLabel.Draw()
# drawing the ratio or difference plot if requested
if (makeRatioPlots or makeDiffPlots):
Canvas.cd(2)
BgSum = Stack_list[i].GetStack().Last()
if makeRatioPlots:
if arguments.ratioRelErrMax:
Comparison = ratioHistogram(Target, BgSum,
arguments.ratioRelErrMax)
else:
Comparison = ratioHistogram(Target, BgSum)
elif makeDiffPlots:
Comparison = Target.Clone("diff")
Comparison.Add(BgSum, -1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("Data-Bkgd")
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)
Comparison.GetYaxis().SetRangeUser(-1 * RatioYRange,
RatioYRange)
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")
if i == 0:
Canvas.Write(distribution['name'] + "_Before")
if arguments.savePDFs:
pathToDirString = plainTextString(pathToDir)
Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
pathToDirString + "/" + distribution['name'] +
"_Before.pdf")
if i == 1:
Canvas.Write(distribution['name'] + "_After")
if arguments.savePDFs:
pathToDirString = plainTextString(pathToDir)
Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
pathToDirString + "/" + distribution['name'] +
"_After.pdf")
def MakeOneHist(histogramName):
HeaderLabel = TPaveLabel(header_x_left, header_y_bottom, header_x_right,
header_y_top, HeaderText, "NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
LumiLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom, topLeft_x_right,
topLeft_y_top, LumiText, "NDC")
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
NormLabel = TPaveLabel()
NormLabel.SetDrawOption("NDC")
NormLabel.SetX1NDC(topLeft_x_left)
NormLabel.SetX2NDC(topLeft_x_right)
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormText = ""
if arguments.normalizeToUnitArea:
NormText = "Scaled to unit area"
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
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("OSUAnalysis/" +
source['num_channel'] + "/" +
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("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source[
'num_channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source[
'den_channel'] + "/" + 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()
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.)"
#Histogram = ROOT.TGraphAsymmErrors(NumHistogramObj,DenHistogramObj)
if arguments.noTGraph or Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
Histogram = TGraphAsymmErrors(Histogram, DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
histoTitle = splitTitle[1].lstrip(" ")
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)
### 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 = 0
if arguments.noTGraph:
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(
histogram.GetMaximumBin())
if (currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5 * finalMax
if finalMax is 0:
finalMax = 1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
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"
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()
if arguments.makeFancy:
HeaderLabel.Draw()
else:
if histogram.InheritsFrom("TGraph") and histCounter == 0:
plotting_options = "AP"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TGraph"):
plotting_options = "P"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
Comparison = ratioHistogram(Histograms[0], Histograms[1])
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)
Comparison.GetYaxis().SetRangeUser(-1 * RatioYRange, RatioYRange)
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()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/" + histogramName + ".pdf")
def MakeOneDHist(histogramDirectory, histogramName,integrateDir):
if arguments.verbose:
print "Creating histogram", histogramName, "in directory", histogramDirectory
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 = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
canvasName = histogramName
if integrateDir is "left":
canvasName += "_CumulativeLeft"
elif integrateDir is "right":
canvasName += "_CumulativeRight"
Canvas = TCanvas(canvasName)
Histograms = []
RefIndex = -99
LegendEntries = []
colorIndex = 0
markerStyleIndex = 0
fillIndex = 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)
if arguments.generic:
if histogramDirectory == "":
histPath = histogramName
else:
histPath = histogramDirectory + "/" + histogramName
HistogramObj = inputFile.Get(histPath)
else:
HistogramObj = inputFile.Get(source['channel'] + "Plotter/" + histogramDirectory + "/" + histogramName)
if not HistogramObj:
print "WARNING: Could not find histogram " + source['channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = HistogramObj.Clone()
Histogram.SetDirectory(0)
inputFile.Close()
Histogram.Sumw2()
if arguments.verbose:
print " Got histogram", Histogram.GetName(), "from file", dataset_file
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:
Histogram.Rebin(RebinFactor)
# correct bin contents of object multiplcity plots
if Histogram.GetName().startswith("num") and "PV" not in Histogram.GetName():
# include overflow bin
for bin in range(2,Histogram.GetNbinsX()+2):
content = Histogram.GetBinContent(bin)
Histogram.SetBinContent(bin, content/float(bin-1))
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
xAxisLabelVar = xAxisLabel
if "_pfx" in Histogram.GetName() or "_pfy" in Histogram.GetName() or "_sigma" in Histogram.GetName():
yAxisLabel = Histogram.GetYaxis().GetTitle()
else:
if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
yAxisLabel = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex]
xAxisLabelVar = xAxisLabel[0:unitBeginIndex]
else:
yAxisLabel = "Entries per bin (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
if arguments.normalizeToUnitArea and arguments.makeSignificancePlots:
unit = "Efficiency"
else:
unit = "Yield"
if integrateDir is "left":
yAxisLabel = unit + ", " + xAxisLabelVar + "< x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
if integrateDir is "right":
yAxisLabel = unit + ", " + xAxisLabelVar + "> x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
nbins = Histogram.GetNbinsX()
if not noOverFlow:
Histogram.SetBinContent(nbins, Histogram.GetBinContent(nbins) + Histogram.GetBinContent(nbins+1)) # Add overflow
Histogram.SetBinError(nbins, math.sqrt(math.pow(Histogram.GetBinError(nbins),2) + math.pow(Histogram.GetBinError(nbins+1),2))) # Set the errors to be the sum in quadrature
if not noUnderFlow:
Histogram.SetBinContent(1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0)) # Add underflow
Histogram.SetBinError(1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2))) # Set the errors to be the sum in quadrature
if not arguments.makeFancy and not arguments.generic:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
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
markerStyleIndex = markerStyleIndex + 1
if markerStyleIndex is len(markerStyleList):
markerStyleIndex = 0
fillIndex = fillIndex + 1
if 'scale' in source:
Histogram.Scale(source['scale'])
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
else:
markerStyle = markers[markerStyleList[markerStyleIndex]]
fillStyle = 0
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
else:
markerStyle = markerStyle + fills[fillList[fillIndex]]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetMarkerSize(0.5)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
if arguments.normalizeToUnitArea and Histogram.Integral() > 0:
Histogram.Scale(1./Histogram.Integral())
Histogram = MakeIntegralHist(Histogram, integrateDir)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
if 'reference' in source:
if source['reference']:
RefIndex = len(Histograms)-1
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
legendIndex = legendIndex+1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
if(currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5*finalMax
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
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.generic:
plotting_options = "p,e"
if arguments.plot_hist:
plotting_options = "HIST"
for histogram in Histograms:
histogram.SetTitle(histoTitle)
if arguments.verbose:
print " Drawing hist " + histogram.GetName() + ", with plotting_options = " + plotting_options + ", with mean = " + str(histogram.GetMean()) + ", with color = " + str(histogram.GetLineColor())
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
histogram.SetMaximum(finalMax)
if "_pfx" not in Histogram.GetName() and "_pfy" not in Histogram.GetName() and "_sigma" not in Histogram.GetName():
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
plotting_options = plotting_options + " SAME"
histCounter = histCounter + 1
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
# Deciding which text labels to draw and drawing them
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Comparisons = []
Canvas.cd(2)
if RefIndex == -99:
Reference = Histograms[0]
else:
Reference = Histograms[RefIndex]
for Histogram in Histograms:
if Histogram is Reference:
continue
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,Histogram, Reference)
if arguments.ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float(arguments.ratioRelErrMax))
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
Comparison = makeRatio()
elif makeDiffPlots:
Comparison = Reference.Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("X-ref")
Comparison.SetLineColor(Histogram.GetLineColor())
Comparison.SetFillColor(Histogram.GetFillColor())
Comparison.SetFillStyle(Histogram.GetFillStyle())
Comparison.SetMarkerColor(Histogram.GetMarkerColor())
Comparison.SetMarkerStyle(Histogram.GetMarkerStyle())
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)
Comparisons.append(Comparison)
option = "E0"
for index,Comparison in enumerate(Comparisons):
if index == 0:
option += " SAME"
Comparison.Draw(option)
outputFile.cd(histogramDirectory)
Canvas.Write()
if arguments.verbose:
print " Finished writing canvas: ", Canvas.GetName()
if arguments.savePDFs:
Canvas.SaveAs("comparison_histograms_pdfs/"+histogramName+".pdf")
def MakeOneHist(varXaxis, varConst, xvalues, constval):
if len(xvalues)<=1:
return # Do not make plot if there is only 1 xvalue
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas("sigEff_"+varConst+str(constval)+"_vs_"+varXaxis)
Histograms = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
# print "Debug: running over input_source from: ", source['condor_dir'], " for varXaxis=", varXaxis, ", varConst=", varConst
# Create histogram of efficiencies with appropriate binning
xAxisBins = array('d')
xBinWidth = xvalues[1] - xvalues[0]
for xval in xvalues:
xAxisBins.append(xval - xBinWidth/2.0)
xAxisBins.append(xvalues[-1] + xBinWidth/2.0) # add an extra bin boundary for the last bin.
Histogram = TH1F("Histogram", ";x title;signal efficiency", len(xvalues), xAxisBins)
Histogram.SetDirectory(0)
# Now fill the histogram of efficiencies:
for xval in xvalues:
if varXaxis=="mass" and varConst=="lifetime":
mass = xval
lifetime = constval
elif varXaxis=="lifetime" and varConst=="mass":
lifetime = xval
mass = constval
else:
print "Unrecognized value of varXaxis=", varXaxis
return
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],dataset)
dataset_file = dataset_file.replace("MASS", str(mass))
dataset_file = dataset_file.replace("LIFETIME", str(lifetime))
inputFile = TFile(dataset_file)
HistCutflow = inputFile.Get("OSUAnalysis/" + source['channel'] + "CutFlow")
if not HistCutflow:
print "WARNING: Could not find histogram OSUAnalysis/" + source['channel'] + "CutFlow in file " + dataset_file + ". Will skip it and continue."
return
# calculate efficiency
nbinsCutflow = HistCutflow.GetNbinsX()
if arguments.xsecFile:
xsec = float(signal_cross_sections[str(mass)]['value'])
denom = xsec * intLumi
else:
denom = HistCutflow.GetBinContent(1) # denominator is the first entry in the cutflow histogram
eff = HistCutflow.GetBinContent(nbinsCutflow) / denom
effErr = HistCutflow.GetBinError (nbinsCutflow) / denom
ibin = Histogram.FindBin(xval)
Histogram.SetBinContent(ibin, eff)
Histogram.SetBinError (ibin, effErr)
print "Setting bin content for varConst = ", varConst, " = ", constval, " in ibin=", ibin, ", xval=", xval, ", eff=", eff, " +- ", effErr, ", fractional error =", effErr/eff, " numerator = ", HistCutflow.GetBinContent(nbinsCutflow), " denom = ", denom, " from file: ", dataset_file
inputFile.Close()
if varXaxis=="mass":
xAxisLabel = "chargino mass [GeV]"
elif varXaxis=="lifetime":
xAxisLabel = "chargino c#tau [cm]"
else:
print "Unrecognized value of varXaxis=", varXaxis
return
yAxisLabel = "efficiency"
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.SetMarkerSize(1)
# Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
# Finish loop over input_sources
# formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
# print "Adding entry to legend: ", LegendEntries[legendIndex]
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
legendIndex = legendIndex+1
# finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
for histogram in Histograms:
# currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
currentMax = histogram.GetMaximum()
if(currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5*finalMax
if finalMax is 0:
finalMax = 1
## if arguments.setYMax:
## finalMax = float(arguments.setYMax)
# Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0
## 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 = "pe, x0" # x0 suppresses the error bar along x
## if arguments.plot_hist:
## plotting_options = "HIST"
for histogram in Histograms:
# histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TGraph"):
plotting_options = "P"
histCounter = histCounter + 1
x_left = 0.15
x_right = 0.55
y_min = 0.6
y_max = 0.8
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
customText = "chargino " + varConst + " " + str(constval)
if varConst == "mass":
customText += " GeV"
elif varConst == "lifetime":
customText += " cm"
customText = customText.replace("lifetime", "c#tau")
CustomLabel = TPaveLabel(x_left, 0.8, x_right, 0.9, customText, "NDC")
CustomLabel.SetBorderSize(0)
CustomLabel.SetFillColor(0)
CustomLabel.SetFillStyle(0)
CustomLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
# Comparison = ratioHistogram(Histograms[0],Histograms[1], 1000)
Comparison = Histograms[0].Clone()
Comparison.Divide(Histograms[1])
Comparison.GetYaxis().SetTitle("ratio")
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)
Comparison.GetYaxis().SetRangeUser(0.7, 1.3)
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")
Comparison.Draw("PE, X0") # X0 suppresses error bar in x direction
outputFile.cd()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
def MCSPlot(self, pname):
#print self.fname
f = TFile(self.fname)
self.RMS = {}
self.RMSErr = {}
self.Chi2 = {}
self.RMSsysdiff = {}
self.RMSsyserr = {}
# create a plot for each histvarname
for histvar in self.histvarnames:
self.RMS[histvar] = {}
self.RMSErr[histvar] = {}
self.RMSsysdiff[histvar] = {}
self.RMSsyserr[histvar] = {}
self.Chi2[histvar] = {}
names = [histvar + '_' + x for x in self.histstatenames]
print names
hists = [f.Get(histvar + '_' + x) for x in self.histstatenames]
print hists[0]
hists[0].SetTitle("")
# hists[3].Scale(norm)
# self.formatHist(hist[0], 0)
resplots = [x.Clone() for x in hists]
resplots[0].SetTitle('')
resplots[0].GetYaxis().SetTitle("Normalized Residuals")
# if histvar == 'thetaScatt':
leg = TLegend(0.55, 0.73, 0.89, 0.92)
leg.SetLineColor(10)
# else:
# leg = TLegend(0.35,0.2,0.65,0.5)
for i in range(len(self.histstatedesc)):
hists[i].Sumw2()
if histvar == 'theta2Scatt':
hists[i].Rebin(8)
resplots[i].Rebin(8)
elif histvar == 'thetaScatt':
hists[i].Rebin(1)
resplots[i].Rebin(1)
else:
hists[i].Rebin(1)
resplots[i].Rebin(1)
self.formatHists(hists[i], i)
self.formatHists(resplots[i], i)
self.addToRMS(i, hists[i], hists[0], resplots[i], histvar)
if histvar == 'theta2Scatt':
hists[i].GetYaxis().SetTitle('Probability per ' + str(
round(1000 * 1000 *
hists[i].GetXaxis().GetBinWidth(4), 2)) +
' mrad^{2}')
else:
hists[i].GetYaxis().SetTitle('Probability per ' + str(
round(1000 * hists[i].GetXaxis().GetBinWidth(4), 2)) +
' mrad')
leg.AddEntry(hists[i], self.histstatedesc[i], self.histopts[i])
#print hists[0]
self.calculateChi2(i, hists[i], hists[0], resplots[i], histvar,
pname)
c = TCanvas(self.fname[:-5] + '_' + histvar + '_c1')
if self.desc[0] == 'XePion':
t1 = TText(0.18, 0.885, "MICE ISIS cycle 2015/03")
t2 = TText(0.18, 0.85,
"Xe, " + self.desc[1][2:5] + ", MAUS v3.1.2")
else:
t1 = TText(0.18, 0.885, "MICE ISIS cycle 2015/04")
t2 = TText(0.18, 0.85,
"LiH, " + self.desc[1][2:5] + ", MAUS v3.1.2")
t1.SetNDC(1)
t1.SetTextSize(0.04)
t1.SetTextFont(42)
t2.SetNDC(1)
t2.SetTextSize(0.03)
t2.SetTextFont(42)
hists[0].GetYaxis().SetRangeUser(4e-4, 2.0)
hists[0].SetTitle(";" + hists[0].GetXaxis().GetTitle() +
" (radians);" + hists[0].GetYaxis().GetTitle())
hists[0].Draw('ep')
c.SetBottomMargin(0.15)
c.SetTopMargin(0.075)
for h in hists[1:len(self.histstatedesc)]:
h.Draw('epsame')
leg.SetTextSize(0.04)
leg.Draw('same')
t1.Draw()
t2.Draw()
c.SetLogy()
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys.eps')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys.root')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_pq.jpg')
c.Clear()
c.SetLogy(0)
resplots[0].GetYaxis().SetRangeUser(-2, 2)
resplots[0].SetTitle(";" + resplots[0].GetXaxis().GetTitle() +
" (radians);" +
resplots[0].GetYaxis().GetTitle())
leg.SetX1NDC(0.5)
leg.SetX2NDC(0.89)
leg.SetY1NDC(0.2)
leg.SetY2NDC(0.4)
resplots[0].Draw("p")
for r in resplots:
r.Draw('psame')
leg.SetTextSize(0.04)
leg.Draw('same')
t1.Draw()
t2.Draw()
# pblock.Draw()
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_res_T.eps')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_res_pq.jpg')
momhist = f.Get("cor_mom")
#mom = [momhist.GetMean() + 19.468, momhist.GetMeanError()]
#if self.fname.find("LiHMuon_03172") >= 0:
# mom = [momhist.GetMean()*1.107 + 1.05, momhist.GetMeanError()]
#elif self.fname.find("LiHMuon_03200") >= 0:
# mom = [momhist.GetMean()*1.104 + 1.139, momhist.GetMeanError()]
#elif self.fname.find("LiHMuon_03240") >= 0:
# mom = [momhist.GetMean()*1.17 - 9.41, momhist.GetMeanError()]
if self.fname.find("LiHMuon_03172") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
elif self.fname.find("LiHMuon_03200") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
elif self.fname.find("LiHMuon_03240") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
rms = [momhist.GetRMS(), momhist.GetRMSError()]
summary = []
syssummary = []
def sigfig(x):
if math.fabs(x) > 1e-5:
return int(math.ceil(math.fabs(math.log(math.fabs(x), 10))))
else:
return 1
# syssummary.append("p (MeV/c) & "+self.histvarnames[0]+"&"+self.histvarnames[1]+"&"+self.histvarnames[3]+"\\\\")
if pname != "Truth":
for sys in self.sysFiles:
# if sys[3] == 'Material': stindx = 1
# else:
stindx = 0
# print sys[3], self.histstatenames[stindx]
difference0 = self.RMSsysdiff[self.histvarnames[0]][
self.histstatenames[stindx]][sys[3]]
difference1 = self.RMSsysdiff[self.histvarnames[1]][
self.histstatenames[stindx]][sys[3]]
difference3 = self.RMSsysdiff[self.histvarnames[3]][
self.histstatenames[stindx]][sys[3]]
syserr0 = self.RMSsyserr[self.histvarnames[0]][
self.histstatenames[stindx]][sys[3]]
syserr1 = self.RMSsyserr[self.histvarnames[1]][
self.histstatenames[stindx]][sys[3]]
syserr3 = self.RMSsyserr[self.histvarnames[3]][
self.histstatenames[stindx]][sys[3]]
relerr0 = syserr0 / self.RMS[self.histvarnames[0]][
self.histstatenames[0]]
relerr1 = syserr1 / self.RMS[self.histvarnames[1]][
self.histstatenames[0]]
relerr3 = syserr3 / self.RMS[self.histvarnames[3]][
self.histstatenames[0]]
syssummary.append(str(round(mom[0],sigfig(mom[1])))+"$\pm$"+str(round(mom[1],sigfig(mom[1])))+\
" & "+str(round(difference0,sigfig(difference0)))+\
" & "+str(round(syserr0,sigfig(syserr0)))+\
" & "+str(round(relerr0,sigfig(relerr0)))+\
" & "+str(round(difference1,sigfig(difference1)))+\
" & "+str(round(syserr1,sigfig(syserr1)))+\
" & "+str(round(relerr1,sigfig(relerr1)))+\
" & "+str(round(difference3,sigfig(difference3)))+\
" & "+str(round(syserr3,sigfig(syserr3)))+\
" & "+str(round(relerr3,sigfig(relerr3)))+"\\\\")
# print syssummary[-1]
syssummary.append(str(round(mom[0],2))+"$\pm$"+str(round(mom[1],2))+\
" & "+ str(round(rms[0],2))+"$\pm$"+str(round(rms[1],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[0]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[0]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[0]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[0]][self.histstatenames[0]],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[1]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[1]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[1]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[1]][self.histstatenames[0]],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[3]][self.histstatenames[0]]['Sum'],2))+
" & "+str(round(self.RMSsyserr[self.histvarnames[3]][self.histstatenames[0]]['Sum'],2))+
" & "+str(round(self.RMSsyserr[self.histvarnames[3]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[2]][self.histstatenames[0]],2))+"\\\\")
# summary.append("p (MeV/c) & &"+str(self.histstatenames[0])+" & "+str(self.histstatenames[1])+" & $\chi^{2}$/ndf & "+
# +str(self.histstatenames[2])+" & $\chi^{2}$/ndf \\\\")
# print mom, self.RMS, self.RMSErr, self.Chi2
for histvar in self.histvarnames:
summary.append(str(round(mom[0],2))+"$\pm$"+str(round(mom[1],2))+\
"& $\ "+histvar+"$ & "+str(round(self.RMS[histvar][self.histstatenames[0]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[0]],2))+ \
"$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[0]]["Sum"],2))+ \
" & "+str(round(self.RMS[histvar][self.histstatenames[1]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[1]],2))+ \
# "$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[1]]["Sum"],2))+\
" & "+str(round(self.Chi2[histvar][self.histstatenames[1]][0],1))+ \
" / "+ str(self.Chi2[histvar][self.histstatenames[1]][1])+ \
" & "+str(round(self.RMS[histvar][self.histstatenames[2]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[2]],2))+ \
#"$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[2]]["Sum"],2))+\
" & "+str(round(self.Chi2[histvar][self.histstatenames[2]][0],1))+ \
" / "+ str(self.Chi2[histvar][self.histstatenames[2]][1])
+"\\\\")
# print summary[-1]
f.Close()
return [summary, syssummary]
def MakeOneDHist(histogramName,integrateDir):
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
NormLabel = TPaveLabel()
NormLabel.SetDrawOption("NDC")
NormLabel.SetX1NDC(topLeft_x_left)
NormLabel.SetX2NDC(topLeft_x_right)
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormText = ""
if arguments.normalizeToUnitArea:
NormText = "Scaled to unit area"
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
canvasName = histogramName
if integrateDir is "left":
canvasName += "_CumulativeLeft"
elif integrateDir is "right":
canvasName += "_CumulativeRight"
Canvas = TCanvas(canvasName)
Histograms = []
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)
if arguments.generic:
HistogramObj = inputFile.Get(source['channel'] + "/" +histogramName)
else:
HistogramObj = inputFile.Get("OSUAnalysis/" + source['channel'] + "/" +histogramName)
if not HistogramObj:
print "WARNING: Could not find histogram " + source['channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = HistogramObj.Clone()
Histogram.SetDirectory(0)
inputFile.Close()
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:
Histogram.Rebin(RebinFactor)
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
xAxisLabelVar = xAxisLabel
if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
yAxisLabel = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex]
xAxisLabelVar = xAxisLabel[0:unitBeginIndex]
else:
yAxisLabel = "Entries per bin (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
if arguments.normalizeToUnitArea and arguments.makeSignificancePlots:
unit = "Efficiency"
else:
unit = "Yield"
if integrateDir is "left":
yAxisLabel = unit + ", " + xAxisLabelVar + "< x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
if integrateDir is "right":
yAxisLabel = unit + ", " + xAxisLabelVar + "> x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
if not arguments.makeFancy and not arguments.generic:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
histoTitle = splitTitle[1].lstrip(" ")
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)
if arguments.normalizeToUnitArea and Histogram.Integral() > 0:
Histogram.Scale(1./Histogram.Integral())
Histogram = MakeIntegralHist(Histogram, integrateDir)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
### 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 = 0
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
if(currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5*finalMax
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
#makeSignifPlots = arguments.makeSignificancePlots
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.generic:
plotting_options = "p,e"
if arguments.plot_hist:
plotting_options = "HIST"
for histogram in Histograms:
histogram.SetTitle(histoTitle)
if arguments.verbose:
print "Debug: drawing hist " + histogram.GetName() + ", with plotting_options = " + plotting_options + ", with mean = " + str(histogram.GetMean()) + ", with color = " + str(histogram.GetLineColor())
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
plotting_options = plotting_options + " SAME"
histCounter = histCounter + 1
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
# Deciding which text labels to draw and drawing them
drawHeaderLabel = False
if arguments.makeFancy:
drawHeaderLabel = True
#now that flags are set, draw the appropriate labels
if drawHeaderLabel:
HeaderLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
if arguments.ratioRelErrMax:
Comparison = ratioHistogram(Histograms[0],Histograms[1],float(arguments.ratioRelErrMax))
else:
Comparison = ratioHistogram(Histograms[0],Histograms[1])
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)
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
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()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("comparison_histograms_pdfs/"+histogramName+".pdf")
