doc/v636/rf302__utilfuncs_8py.html

import ROOT


# Create observables, parameters

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


# Create observables

x = ROOT.RooRealVar("x", "x", -5, 5)

y = ROOT.RooRealVar("y", "y", -5, 5)


# Create parameters

a0 = ROOT.RooRealVar("a0", "a0", -1.5, -5, 5)

a1 = ROOT.RooRealVar("a1", "a1", -0.5, -1, 1)

sigma = ROOT.RooRealVar("sigma", "width of gaussian", 0.5)


# Using RooFormulaVar to tailor pdf

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


# Create interpreted function f(y) = a0 - a1*sqrt(10*abs(y))

fy_1 = ROOT.RooFormulaVar("fy_1", "a0-a1*sqrt(10*abs(y))", [y, a0, a1])


# Create gauss(x,f(y),s)

model_1 = ROOT.RooGaussian("model_1", "Gaussian with shifting mean", x, fy_1, sigma)


# Using RooPolyVar to tailor pdf

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


# Create polynomial function f(y) = a0 + a1*y

fy_2 = ROOT.RooPolyVar("fy_2", "fy_2", y, [a0, a1])


# Create gauss(x,f(y),s)

model_2 = ROOT.RooGaussian("model_2", "Gaussian with shifting mean", x, fy_2, sigma)


# Using RooAddition to tailor pdf

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


# Create sum function f(y) = a0 + y

fy_3 = ROOT.RooAddition("fy_3", "a0+y", [a0, y])


# Create gauss(x,f(y),s)

model_3 = ROOT.RooGaussian("model_3", "Gaussian with shifting mean", x, fy_3, sigma)


# Using RooProduct to tailor pdf

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


# Create product function f(y) = a1*y

fy_4 = ROOT.RooProduct("fy_4", "a1*y", [a1, y])


# Create gauss(x,f(y),s)

model_4 = ROOT.RooGaussian("model_4", "Gaussian with shifting mean", x, fy_4, sigma)


# Plot all pdfs

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


# Make two-dimensional plots in x vs y

hh_model_1 = model_1.createHistogram("hh_model_1", x, Binning=50, YVar=dict(var=y, Binning=50))

hh_model_2 = model_2.createHistogram("hh_model_2", x, Binning=50, YVar=dict(var=y, Binning=50))

hh_model_3 = model_3.createHistogram("hh_model_3", x, Binning=50, YVar=dict(var=y, Binning=50))

hh_model_4 = model_4.createHistogram("hh_model_4", x, Binning=50, YVar=dict(var=y, Binning=50))

hh_model_1.SetLineColor("kBlue")

hh_model_2.SetLineColor("kBlue")

hh_model_3.SetLineColor("kBlue")

hh_model_4.SetLineColor("kBlue")


# Make canvas and draw ROOT.RooPlots

c = ROOT.TCanvas("rf302_utilfuncs", "rf302_utilfuncs", 800, 800)

c.Divide(2, 2)

c.cd(1)

ROOT.gPad.SetLeftMargin(0.20)

hh_model_1.GetZaxis().SetTitleOffset(2.5)

hh_model_1.Draw("surf")

c.cd(2)

ROOT.gPad.SetLeftMargin(0.20)

hh_model_2.GetZaxis().SetTitleOffset(2.5)

hh_model_2.Draw("surf")

c.cd(3)

ROOT.gPad.SetLeftMargin(0.20)

hh_model_3.GetZaxis().SetTitleOffset(2.5)

hh_model_3.Draw("surf")

c.cd(4)

ROOT.gPad.SetLeftMargin(0.20)

hh_model_4.GetZaxis().SetTitleOffset(2.5)

hh_model_4.Draw("surf")


c.SaveAs("rf302_utilfuncs.png")

TRangeDynCast
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Definition TCollection.h:358