rf310_sliceplot.py

## \ingroup tutorial_roofit_main

## \notebook

## Multidimensional models: projecting pdf and data slices in discrete observables

##

## \macro_image

## \macro_code

## \macro_output

##

## \date February 2018

## \authors Clemens Lange, 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)?)

# Define state labels of discrete observables

mixState = ROOT.RooCategory("mixState", "B0/B0bar mixing state", {"mixed": -1, "unmixed": 1})

tagFlav = ROOT.RooCategory("tagFlav", "Flavour of the tagged B0", {"B0": 1, "B0bar": -1})

# Model parameters

dm = ROOT.RooRealVar("dm", "delta m(B)", 0.472, 0.0, 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, type="DoubleSided")

# Generate BMixing data with above set of event errors

data = bmix_gm1.generate({dt, tagFlav, mixState}, 20000)

# Plot full decay distribution

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

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

# mixState)

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

data.plotOn(frame2, 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, Slice=(mixState, "mixed"))

# Create frame, data (unmixed only)

frame3 = dt.frame(Title="Decay distribution of unmixed events")

data.plotOn(frame3, 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, 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")