rf301_composition.cxx

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/////////////////////////////////////////////////////////////////////////
//
// 'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #301
// 
// Multi-dimensional p.d.f.s through composition, e.g. substituting a 
// p.d.f parameter with a function that depends on other observables
// 
// pdf = gauss(x,f(y),s) with f(y) = a0 + a1*y
// 
//
// 07/2008 - Wouter Verkerke 
//
/////////////////////////////////////////////////////////////////////////

#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooPolyVar.h"
#include "RooPlot.h"
#include "TCanvas.h"
#include "TH1.h"
using namespace RooFit ;



class TestBasic301 : public RooFitTestUnit
{
public: 
  TestBasic301(TFile* refFile, Bool_t writeRef, Int_t verbose) : RooFitTestUnit("Composition extension of basic p.d.f",refFile,writeRef,verbose) {} ;
  Bool_t testCode() {

  // S e t u p   c o m p o s e d   m o d e l   g a u s s ( x , m ( y ) , s )
  // -----------------------------------------------------------------------

  // 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)) ;

  // Creat gauss(x,f(y),s)
  RooRealVar sigma("sigma","width of gaussian",0.5) ;
  RooGaussian model("model","Gaussian with shifting mean",x,fy,sigma) ;  


  // S a m p l e   d a t a ,   p l o t   d a t a   a n d   p d f   o n   x   a n d   y 
  // ---------------------------------------------------------------------------------

  // Generate 10000 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) ;


  regPlot(xframe,"rf301_plot1") ;
  regPlot(yframe,"rf302_plot2") ;
  regTH(hh_model,"rf302_model2d") ;

  delete data ;
  return kTRUE ;
  }
} ;

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