doc/v626/rf203__ranges_8py.html

from __future__ import print_function

import ROOT


# Set up model

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


# Construct observables x

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


# Construct gaussx(x,mx,1)

mx = ROOT.RooRealVar("mx", "mx", 0, -10, 10)

gx = ROOT.RooGaussian("gx", "gx", x, mx, ROOT.RooFit.RooConst(1))


# px = 1 (flat in x)

px = ROOT.RooPolynomial("px", "px", x)


# model = f*gx + (1-f)px

f = ROOT.RooRealVar("f", "f", 0.0, 1.0)

model = ROOT.RooAddPdf("model", "model", [gx, px], [f])


# Generated 10000 events in (x,y) from pdf model

modelData = model.generate({x}, 10000)


# Fit full range

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


# Fit pdf to all data

r_full = model.fitTo(modelData, Save=True)


# Fit partial range

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


# Define "signal" range in x as [-3,3]

x.setRange("signal", -3, 3)


# Fit pdf only to data in "signal" range

r_sig = model.fitTo(modelData, Save=True, Range="signal")


# Plot/print results

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


# Make plot frame in x and add data and fitted model

frame = x.frame(Title="Fitting a sub range")

modelData.plotOn(frame)

model.plotOn(frame, Range="Full", LineColor="r", LineStyle="--")  # Add shape in full ranged dashed

model.plotOn(frame)  # By default only fitted range is shown


# Print fit results

print("result of fit on all data ")

r_full.Print()

print("result of fit in in signal region (note increased error on signal fraction)")

r_sig.Print()


# Draw frame on canvas

c = ROOT.TCanvas("rf203_ranges", "rf203_ranges", 600, 600)

ROOT.gPad.SetLeftMargin(0.15)

frame.GetYaxis().SetTitleOffset(1.4)

frame.Draw()


c.SaveAs("rf203_ranges.png")