Rf 5 0 2_Wspacewrite

Organization and simultaneous fits: creating and writing a workspace

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 Sunday, July 05, 2020 at 08:28 AM.

In [ ]:
import ROOT

Create model and dataset

Declare observable x

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x = ROOT.RooRealVar("x", "x", 0, 10)

Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters

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mean = ROOT.RooRealVar("mean", "mean of gaussians", 5, 0, 10)
sigma1 = ROOT.RooRealVar("sigma1", "width of gaussians", 0.5)
sigma2 = ROOT.RooRealVar("sigma2", "width of gaussians", 1)

sig1 = ROOT.RooGaussian("sig1", "Signal component 1", x, mean, sigma1)
sig2 = ROOT.RooGaussian("sig2", "Signal component 2", x, mean, sigma2)

Build Chebychev polynomial p.d.f.

In [ ]:
a0 = ROOT.RooRealVar("a0", "a0", 0.5, 0., 1.)
a1 = ROOT.RooRealVar("a1", "a1", -0.2, 0., 1.)
bkg = ROOT.RooChebychev("bkg", "Background", x, ROOT.RooArgList(a0, a1))

Sum the signal components into a composite signal p.d.f.

In [ ]:
sig1frac = ROOT.RooRealVar(
    "sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.)
sig = ROOT.RooAddPdf(
    "sig", "Signal", ROOT.RooArgList(sig1, sig2), ROOT.RooArgList(sig1frac))

Sum the composite signal and background

In [ ]:
bkgfrac = ROOT.RooRealVar("bkgfrac", "fraction of background", 0.5, 0., 1.)
model = ROOT.RooAddPdf(
    "model", "g1+g2+a", ROOT.RooArgList(bkg, sig), ROOT.RooArgList(bkgfrac))

Generate a data sample of 1000 events in x from model

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data = model.generate(ROOT.RooArgSet(x), 1000)

Create workspace, import data and model

Create a empty workspace

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w = ROOT.RooWorkspace("w", "workspace")

Import model and all its components into the workspace

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w.Import(model)

Import data into the workspace

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w.Import(data)

Print workspace contents

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w.Print()

Save workspace in file

Save the workspace into a ROOT file

In [ ]:
w.writeToFile("rf502_workspace.root")