RooFit Basics

Basic functionality: fitting, plotting, toy data generation on one-dimensional PDFs.

Table of contents

• Setup the model
• Plot the model and change the parameter values_v
• Generate some data
• Plot the data with the model
• Fit model with the data
• Plot the fit result

Load the Minuit2.RooFit module and other needed modules.

using Minuit2.RooFit
using Plots
theme(:boxed)

Setup the model

# Declare variables, x, mean and sigma with initial value and allowed range
x = RealVar(:x, 0.0, limits=(-10, 10), nbins=30)
mean = RealVar(:mean, 1.0, limits=(-10, 10))
sigma = RealVar(:sigma, 1.0, limits=(0.1, 10))

gauss = Gaussian(:gauss, x, mean, sigma)

Gaussian{gauss} PDF with parameters [:mean, :sigma]

Plot the model and change the parameter values_v

plot(gauss, title="Gaussian pdf")
gauss.sigma.value = 3.0
plot!(gauss, label="new sigma")

Generate some data

data = generate(gauss, 1000);

Plot the data with the model

plot(data, title="gaussian with data", label="data")
plot!(gauss, label="pdf")

Fit model with the data

result = fitTo(gauss, data)
# Print values of mean and sigma (that now reflect fitted values and errors)
println("Mean is $(gauss.mean.value) ± $(gauss.mean.error))")
println("Sigma is $(gauss.sigma.value) ± $(gauss.sigma.error))")

Mean is 0.753383039790873 ± 0.09585191531229353)
Sigma is 3.0101470764104907 ± 0.0699555912664056)

Plot the fit result

plot(result, title="Gaussian fit")

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