rf305_condcorrprod.py

# /
#
# 'MULTIDIMENSIONAL MODELS' ROOT.RooFit tutorial macro #305
#
# Multi-dimensional p.d.f.s with conditional p.d.fs in product
#
# pdf = gauss(x,f(y),sx | y ) * gauss(y,ms,sx)    with f(y) = a0 + a1*y
#
#
# 07/2008 - Wouter Verkerke
#
# /


import ROOT


def rf305_condcorrprod():
    # C r e a t e   c o n d i t i o n a l   p d f   g x ( x | y )
    # -----------------------------------------------------------

    # Create observables
    x = ROOT.RooRealVar("x", "x", -5, 5)
    y = ROOT.RooRealVar("y", "y", -5, 5)

    # Create function f(y) = a0 + a1*y
    a0 = ROOT.RooRealVar("a0", "a0", -0.5, -5, 5)
    a1 = ROOT.RooRealVar("a1", "a1", -0.5, -1, 1)
    fy = ROOT.RooPolyVar("fy", "fy", y, ROOT.RooArgList(a0, a1))

    # Create gaussx(x,f(y),sx)
    sigmax = ROOT.RooRealVar("sigma", "width of gaussian", 0.5)
    gaussx = ROOT.RooGaussian(
        "gaussx", "Gaussian in x with shifting mean in y", x, fy, sigmax)

    # C r e a t e   p d f   g y ( y )
    # -----------------------------------------------------------

    # Create gaussy(y,0,5)
    gaussy = ROOT.RooGaussian(
        "gaussy", "Gaussian in y", y, ROOT.RooFit.RooConst(0), ROOT.RooFit.RooConst(3))

    # C r e a t e   p r o d u c t   g x ( x | y ) * g y ( y )
    # -------------------------------------------------------

    # Create gaussx(x,sx|y) * gaussy(y)
    model = ROOT.RooProdPdf(
        "model", "gaussx(x|y)*gaussy(y)", ROOT.RooArgSet(gaussy), ROOT.RooFit.Conditional(ROOT.RooArgSet(gaussx), ROOT.RooArgSet(x)))

    # S a m p l e , i t   a n d   p l o t   p r o d u c t   p d f
    # ---------------------------------------------------------------

    # Generate 1000 events in x and y from model
    data = model.generate(ROOT.RooArgSet(x, y), 10000)

    # Plot x distribution of data and projection of model x = Int(dy)
    # model(x,y)
    xframe = x.frame()
    data.plotOn(xframe)
    model.plotOn(xframe)

    # Plot x distribution of data and projection of model y = Int(dx)
    # model(x,y)
    yframe = y.frame()
    data.plotOn(yframe)
    model.plotOn(yframe)

    # Make two-dimensional plot in x vs y
    hh_model = model.createHistogram("hh_model", x, ROOT.RooFit.Binning(
        50), ROOT.RooFit.YVar(y, ROOT.RooFit.Binning(50)))
    hh_model.SetLineColor(ROOT.kBlue)

    # Make canvas and draw ROOT.RooPlots
    c = ROOT.TCanvas("rf305_condcorrprod", "rf05_condcorrprod", 1200, 400)
    c.Divide(3)
    c.cd(1)
    ROOT.gPad.SetLeftMargin(0.15)
    xframe.GetYaxis().SetTitleOffset(1.6)
    xframe.Draw()
    c.cd(2)
    ROOT.gPad.SetLeftMargin(0.15)
    yframe.GetYaxis().SetTitleOffset(1.6)
    yframe.Draw()
    c.cd(3)
    ROOT.gPad.SetLeftMargin(0.20)
    hh_model.GetZaxis().SetTitleOffset(2.5)
    hh_model.Draw("surf")

    c.SaveAs("rf305_condcorrprod.png")


if __name__ == "__main__":
    rf305_condcorrprod()