rf305_condcorrprod.C File Reference

Detailed Description

Multidimensional models: 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

 
 
␛[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby␛[0m 
                Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
                All rights reserved, please read http://roofit.sourceforge.net/license.txt
 
[#1] INFO:Plotting -- RooAbsReal::plotOn(model) plot on x integrates over variables (y)
[#1] INFO:NumericIntegration -- RooRealIntegral::init([gaussy_NORM[y]_X_gaussx_NORM[x]]_Int[y]) using numeric integrator RooIntegrator1D to calculate Int(y)
[#1] INFO:Plotting -- RooAbsReal::plotOn(model) plot on y integrates over variables (x)

 
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooPolyVar.h"
#include "RooProdPdf.h"
#include "RooPlot.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "TH1.h"
using namespace RooFit;
 
void 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
   RooRealVar x("x", "x", -5, 5);
   RooRealVar y("y", "y", -5, 5);
 
   // Create function f(y) = a0 + a1*y
   RooRealVar a0("a0", "a0", -0.5, -5, 5);
   RooRealVar a1("a1", "a1", -0.5, -1, 1);
   RooPolyVar fy("fy", "fy", y, RooArgSet(a0, a1));
 
   // Create gaussx(x,f(y),sx)
   RooRealVar sigmax("sigma", "width of gaussian", 0.5);
   RooGaussian gaussx("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)
   RooGaussian gaussy("gaussy", "Gaussian in y", y, RooConst(0), 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)
   RooProdPdf model("model", "gaussx(x|y)*gaussy(y)", gaussy, Conditional(gaussx, x));
 
   // S a m p l e ,   f 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
   RooDataSet *data = model.generate(RooArgSet(x, y), 10000);
 
   // Plot x distribution of data and projection of model on x = Int(dy) model(x,y)
   RooPlot *xframe = x.frame();
   data->plotOn(xframe);
   model.plotOn(xframe);
 
   // Plot x distribution of data and projection of model on y = Int(dx) model(x,y)
   RooPlot *yframe = y.frame();
   data->plotOn(yframe);
   model.plotOn(yframe);
 
   // Make two-dimensional plot in x vs y
   TH1 *hh_model = model.createHistogram("hh_model", x, Binning(50), YVar(y, Binning(50)));
   hh_model->SetLineColor(kBlue);
 
   // Make canvas and draw RooPlots
   TCanvas *c = new TCanvas("rf305_condcorrprod", "rf05_condcorrprod", 1200, 400);
   c->Divide(3);
   c->cd(1);
   gPad->SetLeftMargin(0.15);
   xframe->GetYaxis()->SetTitleOffset(1.6);
   xframe->Draw();
   c->cd(2);
   gPad->SetLeftMargin(0.15);
   yframe->GetYaxis()->SetTitleOffset(1.6);
   yframe->Draw();
   c->cd(3);
   gPad->SetLeftMargin(0.20);
   hh_model->GetZaxis()->SetTitleOffset(2.5);
   hh_model->Draw("surf");
}

Author

07/2008 - Wouter Verkerke

Definition in file rf305_condcorrprod.C.