print sbf
sbf.Print()
c.setVal(cNom + c.getError())
fitter4.getWorkSpace().pdf("WpJ4BodyPdf").plotOn(sbf, RooFit.LineStyle(2),
RooFit.Name('syst_up'),
RooFit.LineColor(kBlue+1))
c.setVal(cNom - c.getError())
fitter4.getWorkSpace().pdf("WpJ4BodyPdf").plotOn(sbf, RooFit.LineStyle(2),
RooFit.Name('syst_down'),
RooFit.LineColor(kBlue+1))
cWpJ.cd()
sbf.Draw()
pyroot_logon.cmsLabel(cWpJ, pars4.intLumi/1000, prelim=True)
cWpJ.Update()
cWpJ.Modified()
cWpJ.Update()
cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.pdf' % (opts.mH, modeString,
opts.Nj))
cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.png' % (opts.mH, modeString,
opts.Nj))
# cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.root' % (opts.mH, modeString,
# opts.Nj))
sbf.SetMinimum(1e-4)
cWpJ.SetLogy()
cWpJ.Update()
cWpJ.Modified()
if thePlot:
plots[plotName].append(thePlot.Clone())
inF.Close()
print plots
cplots = []
outFile = TFile(opts.output, 'recreate')
for plot in plots:
outPlot = addPlots(plots[plot])
can = TCanvas()
cans.append(can)
cplots.append(outPlot)
outPlot.Draw()
pyroot_logon.cmsLabel(can, opts.lumi / 1000.)
# gPad.WaitPrimitive()
outPlot.Write()
if (plot == '%s_subtracted' % (opts.prefix)):
outPlot.SetMaximum(outPlot.GetMaximum() * 1.3)
outPlot.SetMinimum(outPlot.GetMinimum() * 1.1)
if outPlot.findObject('ErrBand'):
corrPull = plotMjjFit.sub2pull(outPlot.getHist('theData'),
outPlot.findObject('ErrBand'))
else:
corrPull = plotMjjFit.sub2pull(
outPlot.getHist('theData'),
outPlot.findObject('h_dibosonPdf'))
print sbf
sbf.Print()
c.setVal(cNom + c.getError())
fitter4.getWorkSpace().pdf("WpJ4BodyPdf").plotOn(sbf, RooFit.LineStyle(2),
RooFit.Name('syst_up'),
RooFit.LineColor(kBlue+1))
c.setVal(cNom - c.getError())
fitter4.getWorkSpace().pdf("WpJ4BodyPdf").plotOn(sbf, RooFit.LineStyle(2),
RooFit.Name('syst_down'),
RooFit.LineColor(kBlue+1))
cWpJ.cd()
sbf.Draw()
pyroot_logon.cmsLabel(cWpJ, pars4.intLumi/1000, prelim=True)
cWpJ.Update()
cWpJ.Modified()
cWpJ.Update()
cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.pdf' % (opts.mH, modeString,
opts.Nj))
cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.png' % (opts.mH, modeString,
opts.Nj))
# cWpJ.Print('H%i_Mlvjj_%s_%ijets_WpJShape.root' % (opts.mH, modeString,
# opts.Nj))
sbf.SetMinimum(1e-4)
cWpJ.SetLogy()
cWpJ.Update()
cWpJ.Modified()
def plot2BodyDist(theFitter, pars, chi2, ndf, Err=-1, NP=False, Prefix="Mjj", Left=False):
from ROOT import (
gPad,
TLatex,
TCanvas,
kRed,
kCyan,
kBlue,
RooFit,
RooPlot,
RooCurve,
RooAbsReal,
TGraphErrors,
TLine,
RooWjjMjjFitter,
)
if pars.includeMuons and pars.includeElectrons:
modeString = ""
elif pars.includeMuons:
modeString = "Muon"
elif pars.includeElectrons:
modeString = "Electron"
else:
modeString = ""
mf = theFitter.stackedPlot(False, RooWjjMjjFitter.mjj, Left)
mf.SetName("%s_Stacked" % (Prefix))
sf = theFitter.residualPlot(mf, "h_background", "dibosonPdf", False)
sf.SetName("%s_Subtracted" % (Prefix))
pf = theFitter.residualPlot(mf, "h_total", "", True)
pf.SetName("%s_Pull" % (Prefix))
pf2 = pf.emptyClone("%s_Pull_Corrected" % (Prefix))
pf2.SetMinimum(-5.0)
pf2.SetMaximum(5.0)
corrPull = False
lf = theFitter.stackedPlot(True, RooWjjMjjFitter.mjj, Left)
lf.SetName("%s_Stacked_Log" % (Prefix))
if Err > 0:
totalPdf = theFitter.getWorkSpace().pdf("totalPdf")
## Ntotal = totalPdf.expectedEvents(iset)
## print 'Ntotal:',Ntotal
h_dibosonPdf = sf.getCurve("h_dibosonPdf")
totalPdf.plotOn(
sf,
RooFit.ProjWData(theFitter.getWorkSpace().data("data")),
RooFit.Normalization(Err, RooAbsReal.Raw),
# RooFit.AddTo('h_dibosonPdf', 1., 1.),
# RooFit.Invisible(),
RooFit.Name("h_ErrUp"),
RooFit.Range("RangeForPlot"),
RooFit.NormRange("RangeForPlot"),
RooFit.LineColor(kRed),
RooFit.LineStyle(3),
)
h_ErrUp = sf.getCurve("h_ErrUp")
sf.remove("h_ErrUp", False)
ErrBand = TGraphErrors(h_dibosonPdf.GetN(), h_dibosonPdf.GetX(), h_dibosonPdf.GetY())
for pt in range(1, ErrBand.GetN()):
ErrBand.SetPointError(pt, 0, h_ErrUp.interpolate(ErrBand.GetX()[pt]))
ErrBand.SetName("ErrBand")
ErrBand.SetTitle("Uncertainty")
ErrBand.SetLineColor(kRed)
## ErrBand.SetLineWidth(0)
## ErrBand.SetLineStyle(0)
ErrBand.SetFillColor(kRed)
ErrBand.SetFillStyle(3353)
# ErrBand.Draw('ap3')
# h_ErrUp.Draw('lp')
# gPad.Update()
# gPad.WaitPrimitive()
## h_ErrUp.Draw("al")
## h_ErrUp.GetXaxis().Set(36, 40., 400.)
## gPad.Update()
## gPad.WaitPrimitive()
## h_UpBand = RooCurve("h_UpBand", "Uncertainty", h_dibosonPdf, h_ErrUp,
## 1., 1.)
## h_UpBand.SetLineStyle(3)
## h_UpBand.SetLineColor(kBlue+1)
## h_DownBand = RooCurve("h_DownBand", "Uncertainty", h_dibosonPdf, h_ErrUp,
## 1., -1.)
## h_DownBand.SetLineStyle(3)
## h_DownBand.SetLineColor(kBlue+1)
## sf.addPlotable(h_UpBand, "L")
## sf.addPlotable(h_DownBand, "L")
sf.addObject(ErrBand, "3")
# sf.Print("v")
sf.drawAfter("h_dibosonPdf", "ErrBand")
# sf.Print("v")
sf.drawAfter("ErrBand", "theData")
# sf.Print("v")
sf.findObject("theLegend").AddEntry(ErrBand, "Uncertainty", "f")
sf.findObject("theLegend").SetY1NDC(sf.findObject("theLegend").GetY1NDC() - 0.057)
sf.findObject("theLegend").SetY1(sf.findObject("theLegend").GetY1NDC())
corrPull = True
pf2.addObject(sub2pull(sf.getHist("theData"), sf.findObject("ErrBand")), "p0")
for item in range(0, int(pf.numItems())):
firstItem = pf.getObject(item)
if type(firstItem) == TLine:
newLine = TLine(firstItem)
newLine.SetY1(4.0)
newLine.SetY2(-4.0)
pf2.addObject(newLine, "l")
# SetOwnership(newLine, False)
if NP:
NPPdf = theFitter.makeNPPdf()
NPNorm = 4.0 * 0.11 * 46.8 / 12.0 * pars.intLumi
if modeString == "Electron":
if pars.njets == 2:
NPNorm *= 0.0381
elif pars.njets == 3:
NPNorm *= 0.0123
else:
if pars.njets == 2:
NPNorm *= 0.0550
elif pars.njets == 3:
NPNorm *= 0.0176
print "**** N_NP:", NPNorm, "****"
NPPdf.plotOn(
sf,
RooFit.ProjWData(theFitter.getWorkSpace().data("data")),
RooFit.Normalization(NPNorm, RooAbsReal.Raw),
RooFit.AddTo("h_dibosonPdf", 1.0, 1.0),
RooFit.Name("h_NP"),
RooFit.Range("RangeForPlot"),
RooFit.NormRange("RangeForPlot"),
RooFit.LineColor(kBlue),
RooFit.LineStyle(2),
)
h_NP = sf.getCurve("h_NP")
sf.drawBefore("h_dibosonPdf", "h_NP")
# sf.Print("v")
sf.findObject("theLegend").AddEntry(h_NP, "CDF-like Signal", "L")
sf.findObject("theLegend").SetY1NDC(sf.findObject("theLegend").GetY1NDC() - 0.057)
sf.findObject("theLegend").SetY1(sf.findObject("theLegend").GetY1NDC())
l = TLatex()
l.SetNDC()
l.SetTextSize(0.045)
l.SetTextFont(42)
cstacked = TCanvas("cstacked", "stacked")
mf.Draw()
if chi2 > 0:
l.DrawLatex(0.55, 0.49, "#chi^{2}/dof = %0.3f/%d" % (chi2, ndf))
pyroot_logon.cmsLabel(cstacked, pars.intLumi / 1000, prelim=True)
cstacked.Print("Wjj_%s_%s_%ijets_Stacked.pdf" % (Prefix, modeString, pars.njets))
cstacked.Print("Wjj_%s_%s_%ijets_Stacked.png" % (Prefix, modeString, pars.njets))
c2 = TCanvas("c2", "stacked_log")
c2.SetLogy()
lf.Draw()
pyroot_logon.cmsPrelim(c2, pars.intLumi / 1000)
c2.Print("Wjj_%s_%s_%ijets_Stacked_log.pdf" % (Prefix, modeString, pars.njets))
c2.Print("Wjj_%s_%s_%ijets_Stacked_log.png" % (Prefix, modeString, pars.njets))
c3 = TCanvas("c3", "subtracted")
sf.Draw()
pyroot_logon.cmsLabel(c3, pars.intLumi / 1000, prelim=True)
c3.Print("Wjj_%s_%s_%ijets_Subtracted.pdf" % (Prefix, modeString, pars.njets))
c3.Print("Wjj_%s_%s_%ijets_Subtracted.png" % (Prefix, modeString, pars.njets))
c4 = TCanvas("c4", "pull")
pf.Draw()
c4.SetGridy()
pyroot_logon.cmsPrelim(c4, pars.intLumi / 1000)
c4.Print("Wjj_%s_%s_%ijets_Pull.pdf" % (Prefix, modeString, pars.njets))
c4.Print("Wjj_%s_%s_%ijets_Pull.png" % (Prefix, modeString, pars.njets))
c5 = None
if corrPull:
c5 = TCanvas("c5", "corrected pull")
pf2.Draw()
c5.SetGridy()
pyroot_logon.cmsPrelim(c5, pars.intLumi / 1000)
c5.Print("Wjj_%s_%s_%ijets_Pull_Corrected.pdf" % (Prefix, modeString, pars.njets))
c5.Print("Wjj_%s_%s_%ijets_Pull_Corrected.png" % (Prefix, modeString, pars.njets))
return ([mf, sf, pf2, lf], [cstacked, c2, c3, c5])
if thePlot:
plots[plotName].append(thePlot.Clone())
inF.Close()
print plots
cplots = []
outFile = TFile(opts.output, 'recreate')
for plot in plots:
outPlot = addPlots(plots[plot])
can = TCanvas()
cans.append(can)
cplots.append(outPlot)
outPlot.Draw()
pyroot_logon.cmsLabel(can, opts.lumi/1000.)
# gPad.WaitPrimitive()
outPlot.Write()
if (plot == '%s_subtracted' % (opts.prefix)):
outPlot.SetMaximum(outPlot.GetMaximum()*1.3)
outPlot.SetMinimum(outPlot.GetMinimum()*1.1)
if outPlot.findObject('ErrBand'):
corrPull = plotMjjFit.sub2pull(outPlot.getHist('theData'),
outPlot.findObject('ErrBand'))
else:
corrPull = plotMjjFit.sub2pull(outPlot.getHist('theData'),
outPlot.findObject('h_dibosonPdf'))
corrPull.SetMinimum(-5.)
scaleFunction = TF2("scaleFunction", "y*%.3f" % opts.scaler,
mjj_plot.GetXaxis().GetXmin(),
mjj_plot.GetXaxis().GetXmax(),
mjj_plot.GetMinimum(), mjj_plot.GetMaximum())
sigCurve.Apply(scaleFunction)
sigEntry = mjj_plot.findObject('theLegend').GetListOfPrimitives().Last().SetLabel('H(%i)#times%.0f' %(mH,opts.scaler*2))
# SetOwnership(sigEntry, False)
# # print sigEntry
# # sigEntry.Print()
# sigEntry.SetLabel('H(%i)#times%.0f' %(mH,opts.scaler*2))
cs.cd()
cs.SetLogy(False)
mjj_plot.Draw()
pyroot_logon.cmsLabel(cs, lumi = 19.2, prelim = opts.prelim)
gPad.Update()
gPad.Print('%s%s_%s_mjj_stacked.pdf' % (fname_path,fname_parts[0],
fname_parts[1]))
gPad.Print('%s%s_%s_mjj_stacked.png' % (fname_path,fname_parts[0],
fname_parts[1]))
mjj_pull = f.Get('Mass2j_PFCor_pull')
cp.cd()
mjj_pull.Draw('ap')
pyroot_logon.cmsLabel(cp, lumi = 19.2, prelim = opts.prelim)
gPad.Update()
gPad.Print('%s%s_%s_mjj_pull.pdf' % (fname_path,fname_parts[0],
fname_parts[1]))
gPad.Print('%s%s_%s_mjj_pull.png' % (fname_path,fname_parts[0],
fname_parts[1]))
def plot2BodyDist(theFitter, pars, chi2, ndf,
Err = -1, NP = False, Prefix = "Mjj", Left = False):
from ROOT import gPad, TLatex, TCanvas, kRed, kCyan, kBlue, \
RooFit, RooPlot, RooCurve, RooAbsReal, TGraphErrors, TLine, \
RooWjjMjjFitter
if pars.includeMuons and pars.includeElectrons:
modeString = ''
elif pars.includeMuons:
modeString = 'Muon'
elif pars.includeElectrons:
modeString = 'Electron'
else:
modeString = ''
mf = theFitter.stackedPlot(False, RooWjjMjjFitter.mjj, Left)
mf.SetName("%s_Stacked" % (Prefix));
sf = theFitter.residualPlot(mf, "h_background", "dibosonPdf", False)
sf.SetName("%s_Subtracted" % (Prefix));
pf = theFitter.residualPlot(mf, "h_total", "", True)
pf.SetName("%s_Pull" % (Prefix))
pf2 = pf.emptyClone("%s_Pull_Corrected" % (Prefix))
pf2.SetMinimum(-5.)
pf2.SetMaximum(5.)
corrPull = False
lf = theFitter.stackedPlot(True, RooWjjMjjFitter.mjj, Left)
lf.SetName("%s_Stacked_Log" % (Prefix));
if Err > 0:
totalPdf = theFitter.getWorkSpace().pdf('totalPdf')
## Ntotal = totalPdf.expectedEvents(iset)
## print 'Ntotal:',Ntotal
h_dibosonPdf = sf.getCurve('h_dibosonPdf')
totalPdf.plotOn(sf,
RooFit.ProjWData(theFitter.getWorkSpace().data('data')),
RooFit.Normalization(Err, RooAbsReal.Raw),
#RooFit.AddTo('h_dibosonPdf', 1., 1.),
#RooFit.Invisible(),
RooFit.Name('h_ErrUp'),
RooFit.Range('RangeForPlot'),
RooFit.NormRange('RangeForPlot'),
RooFit.LineColor(kRed), RooFit.LineStyle(3))
h_ErrUp = sf.getCurve('h_ErrUp')
sf.remove('h_ErrUp', False)
ErrBand = TGraphErrors(h_dibosonPdf.GetN(), h_dibosonPdf.GetX(),
h_dibosonPdf.GetY())
for pt in range(1, ErrBand.GetN()):
ErrBand.SetPointError(pt, 0,
h_ErrUp.interpolate(ErrBand.GetX()[pt]))
ErrBand.SetName("ErrBand")
ErrBand.SetTitle("Uncertainty")
ErrBand.SetLineColor(kRed)
## ErrBand.SetLineWidth(0)
## ErrBand.SetLineStyle(0)
ErrBand.SetFillColor(kRed)
ErrBand.SetFillStyle(3353)
#ErrBand.Draw('ap3')
#h_ErrUp.Draw('lp')
#gPad.Update()
#gPad.WaitPrimitive()
## h_ErrUp.Draw("al")
## h_ErrUp.GetXaxis().Set(36, 40., 400.)
## gPad.Update()
## gPad.WaitPrimitive()
## h_UpBand = RooCurve("h_UpBand", "Uncertainty", h_dibosonPdf, h_ErrUp,
## 1., 1.)
## h_UpBand.SetLineStyle(3)
## h_UpBand.SetLineColor(kBlue+1)
## h_DownBand = RooCurve("h_DownBand", "Uncertainty", h_dibosonPdf, h_ErrUp,
## 1., -1.)
## h_DownBand.SetLineStyle(3)
## h_DownBand.SetLineColor(kBlue+1)
## sf.addPlotable(h_UpBand, "L")
## sf.addPlotable(h_DownBand, "L")
sf.addObject(ErrBand, "3")
#sf.Print("v")
sf.drawAfter('h_dibosonPdf', 'ErrBand')
#sf.Print("v")
sf.drawAfter('ErrBand', 'theData')
#sf.Print("v")
sf.findObject('theLegend').AddEntry(ErrBand, 'Uncertainty', 'f')
sf.findObject('theLegend').SetY1NDC(sf.findObject('theLegend').GetY1NDC() - 0.057)
sf.findObject('theLegend').SetY1(sf.findObject('theLegend').GetY1NDC())
corrPull = True
pf2.addObject(sub2pull(sf.getHist('theData'),
sf.findObject('ErrBand')),
'p0')
for item in range(0, int(pf.numItems())):
firstItem = pf.getObject(item)
if (type(firstItem) == TLine):
newLine = TLine(firstItem)
newLine.SetY1(4.)
newLine.SetY2(-4.)
pf2.addObject(newLine, 'l')
#SetOwnership(newLine, False)
if NP:
NPPdf = theFitter.makeNPPdf();
NPNorm = 4.*0.11*46.8/12.*pars.intLumi
if (modeString == 'Electron'):
if pars.njets == 2:
NPNorm *= 0.0381
elif pars.njets == 3:
NPNorm *= 0.0123
else:
if pars.njets == 2:
NPNorm *= 0.0550
elif pars.njets == 3:
NPNorm *= 0.0176
print '**** N_NP:', NPNorm,'****'
NPPdf.plotOn(sf, RooFit.ProjWData(theFitter.getWorkSpace().data('data')),
RooFit.Normalization(NPNorm, RooAbsReal.Raw),
RooFit.AddTo('h_dibosonPdf', 1., 1.),
RooFit.Name('h_NP'),
RooFit.Range('RangeForPlot'),
RooFit.NormRange('RangeForPlot'),
RooFit.LineColor(kBlue), RooFit.LineStyle(2))
h_NP = sf.getCurve('h_NP')
sf.drawBefore('h_dibosonPdf', 'h_NP')
#sf.Print("v")
sf.findObject('theLegend').AddEntry(h_NP, "CDF-like Signal", "L")
sf.findObject('theLegend').SetY1NDC(sf.findObject('theLegend').GetY1NDC() - 0.057)
sf.findObject('theLegend').SetY1(sf.findObject('theLegend').GetY1NDC())
l = TLatex()
l.SetNDC()
l.SetTextSize(0.045)
l.SetTextFont(42)
cstacked = TCanvas("cstacked", "stacked")
mf.Draw()
if (chi2 > 0):
l.DrawLatex(0.55, 0.49,
'#chi^{2}/dof = %0.3f/%d' % (chi2, ndf)
)
pyroot_logon.cmsLabel(cstacked, pars.intLumi/1000, prelim = True)
cstacked.Print('Wjj_%s_%s_%ijets_Stacked.pdf' % (Prefix, modeString,
pars.njets))
cstacked.Print('Wjj_%s_%s_%ijets_Stacked.png' % (Prefix, modeString,
pars.njets))
c2 = TCanvas("c2", "stacked_log")
c2.SetLogy()
lf.Draw()
pyroot_logon.cmsPrelim(c2, pars.intLumi/1000)
c2.Print('Wjj_%s_%s_%ijets_Stacked_log.pdf' % (Prefix, modeString,
pars.njets))
c2.Print('Wjj_%s_%s_%ijets_Stacked_log.png' % (Prefix, modeString,
pars.njets))
c3 = TCanvas("c3", "subtracted")
sf.Draw()
pyroot_logon.cmsLabel(c3, pars.intLumi/1000, prelim = True)
c3.Print('Wjj_%s_%s_%ijets_Subtracted.pdf' % (Prefix, modeString,
pars.njets))
c3.Print('Wjj_%s_%s_%ijets_Subtracted.png' % (Prefix, modeString,
pars.njets))
c4 = TCanvas("c4", "pull")
pf.Draw()
c4.SetGridy()
pyroot_logon.cmsPrelim(c4, pars.intLumi/1000)
c4.Print('Wjj_%s_%s_%ijets_Pull.pdf' % (Prefix, modeString, pars.njets))
c4.Print('Wjj_%s_%s_%ijets_Pull.png' % (Prefix, modeString, pars.njets))
c5 = None
if corrPull:
c5 = TCanvas("c5", "corrected pull")
pf2.Draw()
c5.SetGridy()
pyroot_logon.cmsPrelim(c5, pars.intLumi/1000)
c5.Print('Wjj_%s_%s_%ijets_Pull_Corrected.pdf' % (Prefix, modeString,
pars.njets))
c5.Print('Wjj_%s_%s_%ijets_Pull_Corrected.png' % (Prefix, modeString,
pars.njets))
return ([mf,sf,pf2,lf],[cstacked,c2,c3,c5])