def distribution(tree, name, nbins=10, min=-0.7, max=1):
h = TH1F(name, ';VBF mva', nbins, min, max)
h.Sumw2()
tree.Project(name, 'VBF_mva', '(VBF_mva>-0.7)*weight')
h.Scale(1/h.Integral())
if name is 'WJets':
sBlue.formatHisto(h)
elif name is 'zdata':
sRed.formatHisto(h)
return h
from ROOT import TH1F, TCanvas, gPad
from CMGTools.RootTools.Style import sBlue, sGreen, sRed, sData, formatPad
plot = DataMCPlot('plot')
mult = 10000
h1 = TH1F('h1', 'h1', 100, -5, 5)
h1.FillRandom('gaus', 1 * mult)
h2 = TH1F('h2', 'h2', 100, -5, 5)
h2.FillRandom('pol0', 1 * mult)
h3 = TH1F('h3', 'h3', 100, -5, 5)
h3.FillRandom('pol0', 1 * mult)
sBlue.formatHisto(h1)
sGreen.formatHisto(h2)
sRed.formatHisto(h3)
plot.AddHistogram('signal', h1)
plot.AddHistogram('bgd1', h2)
plot.AddHistogram('bgd2', h3)
plot.Hist('signal').layer = 4
plot.Hist('bgd1').layer = 1
plot.Hist('bgd2').layer = 2
h4 = TH1F('h4', 'h4', 100, -5, 5)
h4.Sumw2()
sData.formatHisto(h4)
plot._BuildStack(plot.histos)
dataModel = plot.stack.totalHist.obj
from ROOT import TH1F, TCanvas, gPad
from CMGTools.RootTools.Style import sBlue, sGreen, sRed, sData, formatPad
plot = DataMCPlot('plot')
mult = 10000
h1 = TH1F('h1','h1', 100,-5,5)
h1.FillRandom('gaus', 1*mult )
h2 = TH1F('h2','h2', 100,-5,5)
h2.FillRandom('pol0', 1*mult )
h3 = TH1F('h3','h3', 100,-5,5)
h3.FillRandom('pol0', 1*mult )
sBlue.formatHisto(h1)
sGreen.formatHisto(h2)
sRed.formatHisto(h3)
plot.AddHistogram('signal', h1)
plot.AddHistogram('bgd1', h2)
plot.AddHistogram('bgd2', h3)
plot.Hist('signal').layer = 4
plot.Hist('bgd1').layer = 1
plot.Hist('bgd2').layer = 2
h4 = TH1F('h4','h4', 100,-5,5)
h4.Sumw2()
sData.formatHisto(h4)
plot._BuildStack(plot.histos)