def studyVqqResolution(rootFile):
#get all from file
histos = {}
inF = TFile.Open(rootFile)
keys = inF.GetListOfKeys()
for k in keys:
obj = inF.Get(k.GetName())
obj.SetDirectory(0)
histos[k.GetName()] = obj
inF.Close()
#plot
gROOT.SetBatch()
gROOT.SetStyle('Plain')
gStyle.SetOptStat(0)
gStyle.SetOptFit(1111)
gStyle.SetOptTitle(0)
gStyle.SetStatFont(42)
kin = ['', '30to40', '40to50', '50to75', '75to100', '100toInf']
for k in kin:
c = TCanvas('c', 'c', 600, 600)
c.cd()
c.SetCanvasSize(1000, 500)
c.SetWindowSize(1000, 500)
c.Divide(2, 1)
c.cd(1)
histos['deta' + k + 'barrel'].SetLineWidth(2)
histos['deta' + k + 'barrel'].SetTitle('barrel')
histos['deta' + k + 'barrel'].Draw('hist')
histos['deta' + k + 'endcap'].SetLineWidth(2)
histos['deta' + k + 'endcap'].SetLineStyle(7)
histos['deta' + k + 'endcap'].SetTitle('endcap')
histos['deta' + k + 'endcap'].Draw('histsame')
leg = TLegend(0.6, 0.92, 0.9, 0.98)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.AddEntry(histos['deta' + k + 'barrel'], 'barrel', 'f')
leg.AddEntry(histos['deta' + k + 'endcap'], 'endcap', 'f')
leg.SetNColumns(2)
leg.Draw()
drawHeader()
c.cd(2)
histos['dphi' + k + 'barrel'].SetLineWidth(2)
histos['dphi' + k + 'barrel'].SetTitle('barrel')
histos['dphi' + k + 'barrel'].Draw('hist')
histos['dphi' + k + 'endcap'].SetLineWidth(2)
histos['dphi' + k + 'endcap'].SetLineStyle(7)
histos['dphi' + k + 'endcap'].SetTitle('endcap')
histos['dphi' + k + 'endcap'].Draw('histsame')
c.Modified()
c.Update()
c.SaveAs('dr_%s.png' % k)
labels = []
responseVars = ['dpt', 'den', 'dphi', 'deta', 'dr']
for r in responseVars:
barrelResponse = TGraphErrors()
barrelResponse.SetName(r + 'barrelresponse')
barrelResponse.SetLineWidth(2)
barrelResponse.SetFillStyle(0)
barrelResponse.SetMarkerStyle(20)
barrelCoreResponse = barrelResponse.Clone(r + 'barrelcoreresponse')
endcapResponse = TGraphErrors()
endcapResponse.SetName(r + 'endcapresponse')
endcapResponse.SetLineWidth(2)
endcapResponse.SetFillStyle(0)
endcapResponse.SetMarkerStyle(24)
endcapCoreResponse = endcapResponse.Clone(r + 'endcapresponse')
for k in kin:
c.cd()
c.Clear()
c.SetWindowSize(1000, 500)
c.Divide(2, 1)
for i in [1, 2]:
c.cd(i)
reg = 'barrel'
if i == 2: reg = 'endcap'
h = histos[r + k + reg]
x = RooRealVar("x",
h.GetXaxis().GetTitle(),
h.GetXaxis().GetXmin(),
h.GetXaxis().GetXmax())
data = RooDataHist("data", "dataset with x", RooArgList(x), h)
frame = x.frame()
RooAbsData.plotOn(data, frame,
RooFit.DataError(RooAbsData.SumW2))
mean1 = RooRealVar("mean1", "mean1", 0, -0.5, 0.5)
sigma1 = RooRealVar("sigma1", "sigma1", 0.1, 0.01, 1.0)
gauss1 = RooGaussian("g1", "g", x, mean1, sigma1)
if r == 'dpt' or r == 'den':
mean2 = RooRealVar("mean2", "mean2", 0, -0.5, 0.5)
sigma2 = RooRealVar("sigma2", "sigma2", 0.1, 0.01, 1.0)
alphacb = RooRealVar("alphacb", "alphacb", 1, 0.1, 3)
ncb = RooRealVar("ncb", "ncb", 4, 1, 100)
gauss2 = RooCBShape("cb2", "cb", x, mean2, sigma2, alphacb,
ncb)
else:
mean1.setRange(0, 0.5)
mean2 = RooRealVar("mean2", "mean", 0, 0, 1)
sigma2 = RooRealVar("sigma2", "sigma", 0.1, 0.01, 1.0)
gauss2 = RooGaussian("g2", "g", x, mean2, sigma2)
frac = RooRealVar("frac", "fraction", 0.9, 0.0, 1.0)
if data.sumEntries() < 100:
frac.setVal(1.0)
frac.setConstant(True)
model = RooAddPdf("sum", "g1+g2", RooArgList(gauss1, gauss2),
RooArgList(frac))
status = model.fitTo(data, RooFit.Save()).status()
if status != 0: continue
model_cdf = model.createCdf(RooArgSet(x))
cl = 0.90
ul = 0.5 * (1.0 + cl)
closestToCL = 1.0
closestToUL = -1
closestToMedianCL = 1.0
closestToMedian = -1
for ibin in xrange(1, h.GetXaxis().GetNbins() * 10):
xval = h.GetXaxis().GetXmin() + (
ibin - 1) * h.GetXaxis().GetBinWidth(ibin) / 10.
x.setVal(xval)
cdfValToCL = math.fabs(model_cdf.getVal() - ul)
if cdfValToCL < closestToCL:
closestToCL = cdfValToCL
closestToUL = xval
cdfValToCL = math.fabs(model_cdf.getVal() - 0.5)
if cdfValToCL < closestToMedianCL:
closestToMedianCL = cdfValToCL
closestToMedian = xval
RooAbsPdf.plotOn(model, frame)
frame.Draw()
if i == 1: drawHeader()
labels.append(TPaveText(0.6, 0.92, 0.9, 0.98, 'brNDC'))
ilab = len(labels) - 1
labels[ilab].SetName(r + k + 'txt')
labels[ilab].SetBorderSize(0)
labels[ilab].SetFillStyle(0)
labels[ilab].SetTextFont(42)
labels[ilab].SetTextAlign(12)
kinReg = k.replace('to', '-')
kinReg = kinReg.replace('Inf', '#infty')
labels[ilab].AddText('[' + reg + '] ' + kinReg)
labels[ilab].Draw()
resolutionVal = math.fabs(closestToUL - closestToMedian)
responseGr = barrelResponse
responseCoreGr = barrelCoreResponse
coreResolutionVal = sigma1.getVal()
coreResolutionErr = sigma1.getError()
if frac.getVal() < 0.7 and (sigma2.getVal() < sigma1.getVal()):
coreResolutionVal = sigma2.getVal()
coreResolutionErr = sigma2.getError()
if i == 2:
responseGr = endcapResponse
responseCoreGr = endcapCoreResponse
if k != '':
nrespPts = responseGr.GetN()
kinAvg = 150
kinWidth = 50
if k == '30to40':
kinAvg = 35
kinWidth = 5
if k == '40to50':
kinAvg = 45
kinWidth = 5
if k == '50to75':
kinAvg = 62.5
kinWidth = 12.5
elif k == '75to100':
kinAvg = 87.5
kinWidth = 12.5
responseGr.SetPoint(nrespPts, kinAvg, resolutionVal)
responseCoreGr.SetPoint(nrespPts, kinAvg,
coreResolutionVal)
responseCoreGr.SetPointError(nrespPts, kinWidth,
coreResolutionErr)
labels.append(TPaveText(0.15, 0.7, 0.4, 0.9, 'brNDC'))
ilab = len(labels) - 1
labels[ilab].SetName(r + k + 'fitrestxt')
labels[ilab].SetBorderSize(0)
labels[ilab].SetFillStyle(0)
labels[ilab].SetTextFont(42)
labels[ilab].SetTextAlign(12)
labels[ilab].AddText('Gaussian #1 (f=%3.3f)' % frac.getVal())
labels[ilab].AddText('#mu=%3.3f#pm%3.3f' %
(mean1.getVal(), mean1.getError()))
labels[ilab].AddText('#sigma=%3.3f#pm%3.3f' %
(sigma1.getVal(), sigma1.getError()))
labels[ilab].AddText('Gaussian #2 (f=%3.3f)' %
(1 - frac.getVal()))
labels[ilab].AddText('#mu=%3.3f#pm%3.3f' %
(mean2.getVal(), mean2.getError()))
labels[ilab].AddText('#sigma=%3.3f#pm%3.3f' %
(sigma2.getVal(), sigma2.getError()))
labels[ilab].Draw()
c.Modified()
c.Update()
c.SaveAs(r + 'res_' + k + '.png')
frame = TGraphErrors()
frame.SetPoint(0, 0, 0)
frame.SetPoint(1, 200, 0.3)
frame.SetMarkerStyle(1)
frame.SetFillStyle(0)
frame.SetName('frame')
cresp = TCanvas('cresp', 'cresp', 500, 500)
cresp.cd()
frame.Draw('ap')
barrelResponse.Draw('pl')
endcapResponse.Draw('pl')
frame.GetXaxis().SetTitle("Quark transverse momentum [GeV]")
frame.GetYaxis().SetTitle("Resolution %3.2f C.L." % cl)
frame.GetYaxis().SetTitleOffset(1.4)
frame.GetYaxis().SetNdivisions(10)
drawHeader()
leg = TLegend(0.6, 0.92, 0.9, 0.98)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.AddEntry(barrelResponse, 'barrel', 'fp')
leg.AddEntry(endcapResponse, 'endcap', 'fp')
leg.SetNColumns(2)
leg.Draw()
cresp.Modified()
cresp.Update()
cresp.SaveAs(r + 'res_evol.png')
frameCore = frame.Clone('framecore')
cresp.Clear()
frameCore.Draw('ap')
barrelCoreResponse.Draw('pl')
endcapCoreResponse.Draw('pl')
frameCore.GetXaxis().SetTitle("Quark transverse momentum [GeV]")
frameCore.GetYaxis().SetTitle("Core resolution")
frameCore.GetYaxis().SetTitleOffset(1.4)
frameCore.GetYaxis().SetNdivisions(10)
frameCore.GetYaxis().SetRangeUser(0, 0.2)
drawHeader()
leg = TLegend(0.6, 0.92, 0.9, 0.98)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.AddEntry(barrelCoreResponse, 'barrel', 'fp')
leg.AddEntry(endcapCoreResponse, 'endcap', 'fp')
leg.SetNColumns(2)
leg.Draw()
cresp.Modified()
cresp.Update()
cresp.SaveAs(r + 'rescore_evol.png')
bosons = ['h', 'z', 'w']
kin = ['', '50', '100']
region = ['', 'bb', 'eb', 'ee']
for k in kin:
for r in region:
c = TCanvas('c', 'c', 600, 600)
c.cd()
histos['mjj' + k + r].Rebin()
histos['mjj' + k + r].Draw()
ic = 1
leg = TLegend(0.6, 0.92, 0.9, 0.98)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.AddEntry(histos['mjj' + k + r], 'inclusive', 'f')
for b in bosons:
if histos[b + 'mjj' + k + r].Integral() <= 0: continue
ic = ic + 1
histos[b + 'mjj' + k + r].Rebin()
histos[b + 'mjj' + k + r].SetLineColor(ic)
histos[b + 'mjj' + k + r].SetLineWidth(2)
histos[b + 'mjj' + k + r].SetMarkerColor(ic)
histos[b + 'mjj' + k + r].SetMarkerStyle(1)
histos[b + 'mjj' + k + r].SetFillStyle(3000 + ic)
histos[b + 'mjj' + k + r].SetFillColor(ic)
histos[b + 'mjj' + k + r].Draw('histsame')
leg.AddEntry(histos[b + 'mjj' + k + r], b, "f")
leg.SetNColumns(ic)
leg.Draw()
drawHeader()
labels.append(TPaveText(0.65, 0.8, 0.9, 0.9, 'brNDC'))
ilab = len(labels) - 1
labels[ilab].SetName(k + r + 'mjj')
labels[ilab].SetBorderSize(0)
labels[ilab].SetFillStyle(0)
labels[ilab].SetTextFont(42)
labels[ilab].SetTextAlign(12)
regionTitle = "inclusive"
if r == 'bb': regionTitle = 'barrel-barrel'
if r == 'eb': regionTitle = 'endcap-barrel'
if r == 'ee': regionTitle = 'endcap-endcap'
labels[ilab].AddText(regionTitle)
ptthreshold = 30
if k != '': ptthreshold = float(k)
labels[ilab].AddText('p_{T}>%3.0f GeV' % ptthreshold)
labels[ilab].Draw()
c.Modified()
c.Update()
c.SaveAs('mjj' + k + r + '.png')
massResolutionGrs = []
for r in region:
massResolution = TGraphErrors()
massResolution.SetName(r + 'dm')
massResolution.SetLineWidth(2)
massResolution.SetFillStyle(0)
massResolution.SetMarkerStyle(20 + len(massResolutionGrs))
massResolution.SetMarkerColor(1 + len(massResolutionGrs))
massResolution.SetLineColor(1 + len(massResolutionGrs))
massResolution.SetFillColor(1 + len(massResolutionGrs))
massResolutionGrs.append(massResolution)
for k in kin:
c = TCanvas('c', 'c', 600, 600)
c.cd()
h = histos['dmjj' + k + r]
x = RooRealVar("x",
h.GetXaxis().GetTitle(),
h.GetXaxis().GetXmin(),
h.GetXaxis().GetXmax())
data = RooDataHist("data", "dataset with x", RooArgList(x), h)
frame = x.frame()
RooAbsData.plotOn(data, frame, RooFit.DataError(RooAbsData.SumW2))
mean1 = RooRealVar("mean1", "mean1", 0, -0.5, 0.5)
sigma1 = RooRealVar("sigma1", "sigma1", 0.1, 0.01, 1.0)
gauss1 = RooGaussian("g1", "g", x, mean1, sigma1)
mean2 = RooRealVar("mean2", "mean2", 0, -0.5, 0.5)
sigma2 = RooRealVar("sigma2", "sigma2", 0.1, 0.01, 1.0)
alphacb = RooRealVar("alphacb", "alphacb", 1, 0.1, 3)
ncb = RooRealVar("ncb", "ncb", 4, 1, 100)
gauss2 = RooCBShape("cb2", "cb", x, mean2, sigma2, alphacb, ncb)
frac = RooRealVar("frac", "fraction", 0.9, 0.0, 1.0)
model = RooAddPdf("sum", "g1+g2", RooArgList(gauss1, gauss2),
RooArgList(frac))
status = model.fitTo(data, RooFit.Save()).status()
if status != 0: continue
RooAbsPdf.plotOn(model, frame)
frame.Draw()
labels.append(TPaveText(0.6, 0.65, 0.85, 0.9, 'brNDC'))
ilab = len(labels) - 1
labels[ilab].SetName(r + k + 'dmfitrestxt')
labels[ilab].SetBorderSize(0)
labels[ilab].SetFillStyle(0)
labels[ilab].SetTextFont(42)
labels[ilab].SetTextAlign(12)
labels[ilab].AddText('Gaussian #1 (f=%3.3f)' % frac.getVal())
labels[ilab].AddText('#mu=%3.3f#pm%3.3f' %
(mean1.getVal(), mean1.getError()))
labels[ilab].AddText('#sigma=%3.3f#pm%3.3f' %
(sigma1.getVal(), sigma1.getError()))
labels[ilab].AddText('Gaussian #2 (f=%3.3f)' % (1 - frac.getVal()))
labels[ilab].AddText('#mu=%3.3f#pm%3.3f' %
(mean2.getVal(), mean2.getError()))
labels[ilab].AddText('#sigma=%3.3f#pm%3.3f' %
(sigma2.getVal(), sigma2.getError()))
labels[ilab].Draw()
drawHeader()
labels.append(TPaveText(0.15, 0.8, 0.4, 0.9, 'brNDC'))
ilab = len(labels) - 1
labels[ilab].SetName(k + r + 'dmjj')
labels[ilab].SetBorderSize(0)
labels[ilab].SetFillStyle(0)
labels[ilab].SetTextFont(42)
labels[ilab].SetTextAlign(12)
regionTitle = "inclusive"
if r == 'bb': regionTitle = 'barrel-barrel'
if r == 'eb': regionTitle = 'endcap-barrel'
if r == 'ee': regionTitle = 'endcap-endcap'
labels[ilab].AddText(regionTitle)
ptthreshold = 30
if k != '': ptthreshold = float(k)
labels[ilab].AddText('p_{T}>%3.0f GeV' % ptthreshold)
labels[ilab].Draw()
c.Modified()
c.Update()
c.SaveAs('dmjj' + k + r + '.png')
massResolution.SetTitle(regionTitle)
ip = massResolution.GetN()
x = 40
xerr = 10
if k == '50':
x = 75
xerr = 25
elif k == '100':
x = 150
xerr = 50
y = sigma1.getVal()
yerr = sigma1.getError()
if frac.getVal() < 0.8:
if sigma2.getVal() < sigma1.getVal():
y = sigma2.getVal()
ey = sigma2.getError()
massResolution.SetPoint(ip, x, y)
massResolution.SetPointError(ip, xerr, yerr)
frame = TGraphErrors()
frame.SetPoint(0, 0, 0)
frame.SetPoint(1, 200, 0.2)
frame.SetMarkerStyle(1)
frame.SetFillStyle(0)
frame.SetName('dmframe')
cdmevol = TCanvas('cdmevol', 'cdmevol', 500, 500)
cdmevol.cd()
frame.Draw('ap')
leg = TLegend(0.6, 0.92, 0.9, 0.98)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
for dmGr in massResolutionGrs:
dmGr.Draw('pl')
leg.AddEntry(dmGr, dmGr.GetTitle(), 'fp')
frame.GetXaxis().SetTitle("Leading quark transverse momentum [GeV]")
frame.GetYaxis().SetTitle("Core resolution")
frame.GetYaxis().SetTitleOffset(1.4)
frame.GetYaxis().SetNdivisions(10)
drawHeader()
leg.SetNColumns(2)
leg.Draw()
cdmevol.Modified()
cdmevol.Update()
cdmevol.SaveAs('dm_evol.png')
c = TCanvas('c', 'c', 600, 600)
c.cd()
histos['sel'].Draw('histtext')
drawHeader()
c.Modified()
c.Update()
c.SaveAs('selection.png')
return
