def _calc_histo(self, *opt):
self.tot = rt.TH1F( self.name+"_tot_"+aux.randomName(),
";"+self.ytitle+"; Events / bin",
self.ybins,
self.ymin,
self.ymax)
self.pas = rt.TH1F( self.name+"_pas_"+aux.randomName(),
";"+self.ytitle+"; Events / bin",
self.ybins,
self.ymin,
self.ymax)
if not opt:
rng = [0, self.ybins] # TODO: set this to a different range
else:
rng = [opt[0], opt[1]]
for yb in range(self.ybins):
# NOTE:
# The lists with the projection histograms
# have to be looped from 0 to the number of bins,
# but the setted bins in the total and passed histograms
# go from 0 to the number of bins +1,
# thats why there is SetBinContent(yb+1).
val = self.tot_proj[yb].Integral(rng[0], rng[1])
self.tot.SetBinContent(yb+1, val)
val = self.pas_proj[yb].Integral(rng[0], rng[1])
self.pas.SetBinContent(yb+1, val)
self.tot.Sumw2()
self.pas.Sumw2()
return 0
def addFakerate(self, f, name=""):
# fakerate should be of type h2Fakerate
self.h.append(f.ehis)
self.f.append(f.f)
if name=="":
self.names.append(aux.randomName())
else:
self.names.append(name)
return 0
def __init__(self, name, tot, pas, *opt):
# tot and pas are 2d histograms for the total and the passed
# content to determine the efficiency.
self.name = name
self.ybins = tot.GetNbinsY()
self.ymin = tot.GetYaxis().GetXmin()
self.ymax = tot.GetYaxis().GetXmax()
self.ytitle = tot.GetYaxis().GetTitle()
self._calc_proj(tot, pas)
if not opt:
self._calc_histo()
else:
self._calc_histo(opt[0], opt[1])
self.f = aux.randomName()
self.egraph = aux.randomName()
self.ehis = aux.randomName()
def createFitPrediction(self, *opt):
# here, the fitted fakerate function is used
# to make a prediction for the closure test.
bins = self.initial.GetNbinsX()
xmin = self.initial.GetXaxis().GetXmin()
xmax = self.initial.GetXaxis().GetXmax()
for h in self.h:
self.predictionf.append(self.initial.Clone(aux.randomName()))
for i in range(1, bins+1):
val = self.initial.GetBinContent(i)
err = self.initial.GetBinError(i)
x = self.initial.GetBinCenter(i)
count = 0
for f in self.f:
R = self.evalFakerate(f, x)
self.predictionf[count].SetBinContent(i, R*val)
self.predictionf[count].SetBinError(i, R*err)
count = count+1
return 0
def createHistoPrediction(self, *opt):
# here, the fakerate histogram is used
# to make a prediction for the closure test
bins = self.initial.GetNbinsX()
xmin = self.initial.GetXaxis().GetXmin()
xmax = self.initial.GetXaxis().GetXmax()
for h in self.h:
self.predictionh.append(self.initial.Clone(aux.randomName()))
for i in range(1, bins+1):
val = self.initial.GetBinContent(i)
#print i, val,
err = self.initial.GetBinError(i)
count = 0
for h in self.h:
#fr = h.GetBinContent(i)
#fr = 0.0102919054273 # background fit gauss + poly2, global bin
fr = 0.010706 # roofit cms shape, global bin
R = float(fr)/(1-fr)
self.predictionh[count].SetBinContent(i, R*val)
self.predictionh[count].SetBinError(i, R*err)
#print self.predictionh[count].GetBinContent(i)
count = count +1
return 0
def createCanvas(self, fs, yrng="", name="", log=False):
cwidth = 800
cheight = 800
rat = 0.35
c = rt.TCanvas(self.h2f.name, self.h2f.name, cwidth, cheight)
rt.gStyle.SetTitleFontSize(0.07);
c.cd()
#c.SetLeftMargin(0.16)
#c.SetBottomMargin(0.15)
self.egraph.GetXaxis().SetTitleSize(0.05)
self.egraph.GetXaxis().SetLabelSize(0.0)
self.egraph.GetYaxis().SetTitleSize(0.05)
self.egraph.GetYaxis().SetLabelSize(0.05)
self.egraph.GetYaxis().SetTitleOffset(1.3)
self.egraph.SetTitle(self.clabel)
#self.egraph.SetTitleOffset(1.2)
#h1.SetMinimum(-10)
self.ratio.GetXaxis().SetTitleSize(0.15)
self.ratio.GetXaxis().SetLabelSize(0.1)
self.ratio.GetYaxis().SetNdivisions(5)
self.ratio.GetYaxis().SetTitleSize(0.12)
self.ratio.GetYaxis().SetLabelSize(0.09)
self.ratio.GetYaxis().SetTitleOffset(0.6)
self.ratio.SetMinimum(0.5)
self.ratio.SetMaximum(1.5)
pad1 = rt.TPad("pad1","pad1",0,rat,1,1)
pad1.SetGrid()
#pad1.SetTopMargin(0.8)
pad1.SetBottomMargin(0)
pad1.SetLeftMargin(0.16)
pad1.Draw()
pad1.cd()
pad1.Update()
self.egraph.GetYaxis().SetTitle("Fakerate")
self.egraph.GetYaxis().SetTitleOffset(1.3)
self.egraph.GetYaxis().SetTitleSize(0.05)
self.egraph.GetXaxis().SetLabelSize(0.0)
self.egraph.GetXaxis().SetTitleSize(0.05)
#.SetMaximum(0.015)
#eff.GetXaxis().SetRangeUser(0.,210.)
if yrng=="":
self.egraph.SetMinimum(0.)
else:
self.egraph.SetMinimum(yrng[0])
self.egraph.SetMaximum(yrng[1])
#eff.Draw("ap")
self.egraph.Draw("ap")
c.cd()
pad2 = rt.TPad("pad2","pad2",0,0,1,rat)
pad2.SetGridy()
pad2.SetGridx()
pad2.SetTopMargin(0)
pad2.SetBottomMargin(0.35)
pad2.SetLeftMargin(0.16)
pad2.Draw()
pad2.cd()
oneline = rt.TF1("oneline"+aux.randomName(), "1",
self.egraph.GetXaxis().GetXmin(),
self.egraph.GetXaxis().GetXmax())
oneline.SetLineWidth(1)
oneline.SetLineColor(rt.kBlack)
self.ratio.Draw("ap")
oneline.Draw("same")
pad2.Update()
c.Update()
fs.savePdf(c, name)
c.Close()
#drawCMS(c)
#c.Update()
#raw_input()
#self.c = c.Clone()
#self.c.Update()
return 0