## \file

## \ingroup tutorial_roofit

## \notebook

##

## 'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #310

##

## Projecting p.d.f and data slices in discrete observables

##

## \macro_code

##

## \date February 2018

## \author Clemens Lange

## \author Wouter Verkerke (C version)

import ROOT

# Create B decay pdf with mixing

# ----------------------------------------------------------

# Decay time observables

dt = ROOT.RooRealVar("dt", "dt", -20, 20)

# Discrete observables mixState (B0tag==B0reco?) and tagFlav

# (B0tag==B0(bar)?)

mixState = ROOT.RooCategory("mixState", "B0/B0bar mixing state")

tagFlav = ROOT.RooCategory("tagFlav", "Flavour of the tagged B0")

# Define state labels of discrete observables

mixState.defineType("mixed", -1)

mixState.defineType("unmixed", 1)

tagFlav.defineType("B0", 1)

tagFlav.defineType("B0bar", -1)

# Model parameters

dm = ROOT.RooRealVar("dm", "delta m(B)", 0.472, 0., 1.0)

tau = ROOT.RooRealVar("tau", "B0 decay time", 1.547, 1.0, 2.0)

w = ROOT.RooRealVar("w", "Flavor Mistag rate", 0.03, 0.0, 1.0)

dw = ROOT.RooRealVar(

"dw", "Flavor Mistag rate difference between B0 and B0bar", 0.01)

# Build a gaussian resolution model

bias1 = ROOT.RooRealVar("bias1", "bias1", 0)

sigma1 = ROOT.RooRealVar("sigma1", "sigma1", 0.01)

gm1 = ROOT.RooGaussModel("gm1", "gauss model 1", dt, bias1, sigma1)

# Construct a decay pdf, with single gaussian resolution model

bmix_gm1 = ROOT.RooBMixDecay("bmix", "decay", dt, mixState,

tagFlav, tau, dm, w, dw, gm1, ROOT.RooBMixDecay.DoubleSided)

# Generate BMixing data with above set of event errors

data = bmix_gm1.generate(ROOT.RooArgSet(dt, tagFlav, mixState), 20000)

# Plot full decay distribution

# ----------------------------------------------------------

# Create frame, data and pdf projection (integrated over tagFlav and

# mixState)

frame = dt.frame(ROOT.RooFit.Title("Inclusive decay distribution"))

data.plotOn(frame)

bmix_gm1.plotOn(frame)

# Plot decay distribution for mixed and unmixed slice of mixState

# -------------------------------------------------------------------------------------------

# Create frame, data (mixed only)

frame2 = dt.frame(ROOT.RooFit.Title("Decay distribution of mixed events"))

data.plotOn(frame2, ROOT.RooFit.Cut("mixState==mixState::mixed"))

# Position slice in mixState at "mixed" and plot slice of pdf in mixstate

# over data (integrated over tagFlav)

bmix_gm1.plotOn(frame2, ROOT.RooFit.Slice(mixState, "mixed"))

# Create frame, data (unmixed only)

frame3 = dt.frame(ROOT.RooFit.Title(

"Decay distribution of unmixed events"))

data.plotOn(frame3, ROOT.RooFit.Cut("mixState==mixState::unmixed"))

# Position slice in mixState at "unmixed" and plot slice of pdf in

# mixstate over data (integrated over tagFlav)

bmix_gm1.plotOn(frame3, ROOT.RooFit.Slice(mixState, "unmixed"))

c = ROOT.TCanvas("rf310_sliceplot", "rf310_sliceplot", 1200, 400)

c.Divide(3)

c.cd(1)

ROOT.gPad.SetLeftMargin(0.15)

frame.GetYaxis().SetTitleOffset(1.4)

ROOT.gPad.SetLogy()

frame.Draw()

c.cd(2)

ROOT.gPad.SetLeftMargin(0.15)

frame2.GetYaxis().SetTitleOffset(1.4)

ROOT.gPad.SetLogy()

frame2.Draw()

c.cd(3)

ROOT.gPad.SetLeftMargin(0.15)

frame3.GetYaxis().SetTitleOffset(1.4)

ROOT.gPad.SetLogy()

frame3.Draw()

c.SaveAs("rf310_sliceplot.png")