Rf 7 0 1_Efficiencyfit¶

Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function to a dataset D(x,cut), cut is a category encoding a selection, which the efficiency as function of x should be described by eff(x)

Author: Clemens Lange, Wouter Verkerke (C++ version)
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Monday, January 17, 2022 at 10:15 AM.

In [ ]:
import ROOT

Construct efficiency function e(x)¶

Declare variables x,mean, with associated name, title, value and allowed range

In [ ]:
x = ROOT.RooRealVar("x", "x", -10, 10)

Efficiency function eff(x;a,b)

In [ ]:
a = ROOT.RooRealVar("a", "a", 0.4, 0, 1)
b = ROOT.RooRealVar("b", "b", 5)
c = ROOT.RooRealVar("c", "c", -1, -10, 10)
effFunc = ROOT.RooFormulaVar("effFunc", "(1-a)+a*cos((x-c)/b)", [a, b, c, x])

Construct conditional efficiency pdf E(cut|x)¶

Acceptance state cut (1 or 0)

In [ ]:
cut = ROOT.RooCategory("cut", "cutr", {"accept": 1, "reject": 0})

Construct efficiency pdf eff(cut|x)

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effPdf = ROOT.RooEfficiency("effPdf", "effPdf", effFunc, cut, "accept")

Generate data (x, cut) from a toy model¶

Construct global shape pdf shape(x) and product model(x,cut) = eff(cut|x)*shape(x) (These are only needed to generate some toy MC here to be used later)

In [ ]:
shapePdf = ROOT.RooPolynomial("shapePdf", "shapePdf", x, [-0.095])
model = ROOT.RooProdPdf("model", "model", {shapePdf}, Conditional=({effPdf}, {cut}))

Generate some toy data from model

In [ ]:
data = model.generate({x, cut}, 10000)

Fit conditional efficiency pdf to data¶

Fit conditional efficiency pdf to data

In [ ]:
effPdf.fitTo(data, ConditionalObservables={x})

Plot fitted, data efficiency¶

Plot distribution of all events and accepted fraction of events on frame

In [ ]:
frame1 = x.frame(Bins=20, Title="Data (all, accepted)")
data.plotOn(frame1)
data.plotOn(frame1, Cut="cut==cut::accept", MarkerColor="r", LineColor="r")

Plot accept/reject efficiency on data overlay fitted efficiency curve

In [ ]:
frame2 = x.frame(Bins=20, Title="Fitted efficiency")
data.plotOn(frame2, Efficiency=cut)  # needs ROOT version >= 5.21
effFunc.plotOn(frame2, LineColor="r")

Draw all frames on a canvas

In [ ]:
ca = ROOT.TCanvas("rf701_efficiency", "rf701_efficiency", 800, 400)
ca.Divide(2)
ca.cd(1)
frame1.GetYaxis().SetTitleOffset(1.6)
frame1.Draw()
ca.cd(2)