//////////////////////////////////////////////////////////////////////////
//
// 'DATA AND CATEGORIES' RooFit tutorial macro #401
// 
// Overview of advanced option for importing data from ROOT TTree and THx histograms
// Basic import options are demonstrated in rf102_dataimport.C
//
//
// 07/2008 - Wouter Verkerke 
// 
/////////////////////////////////////////////////////////////////////////

#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooDataHist.h"
#include "RooCategory.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
#include "TH1.h"
#include "TTree.h"
#include "TRandom.h"

using namespace RooFit ;

struct testst{ 
               double px;
               double py;
               double pz;
//               int pi;
};

TTree* makeTTree(bool usestruct) ;

void rf401_importttreethx(bool usestruct)
{
  TTree* tree = makeTTree(usestruct) ;

  RooRealVar px("xyz.x","xyz.x",-10,10) ;
  RooRealVar py("xyz.y","xyz.y",-10,10) ;
  RooRealVar pz("xyz.z","xyz.z",-10,10) ;

  RooDataSet ds("ds","ds",RooArgSet(px, py, pz),Import(*tree)) ;
  ds.Print() ;
  
  RooPlot* p1=px.frame();
  ds.plotOn(p1);
  RooPlot* p2=py.frame();
  ds.plotOn(p2);
  RooPlot* p3=pz.frame();
  ds.plotOn(p3);
  
  new TCanvas();
  p1->Draw();
  new TCanvas();
  p2->Draw();
  new TCanvas();
  p3->Draw();
}

TTree* makeTTree(bool usestruct) 
{
  // Create ROOT TTree filled with a Gaussian distribution in x and a uniform distribution in y
  TTree* tree = new TTree("tree","tree") ;
  testst pxyz;
  if (usestruct)
      tree->Branch("xyz", &pxyz,"x/D:y/D:z/D") ;
  else {
      tree->Branch("xyz.x",&pxyz.px,"x/D") ;
      tree->Branch("xyz.y",&pxyz.py,"y/D") ;
      tree->Branch("xyz.z",&pxyz.pz,"z/D") ;\
  }

  for (int i=0 ; i<10000 ; i++) {
    pxyz.px = gRandom->Gaus(0,3) ;
    pxyz.py = gRandom->Uniform()*30 - 15 ;
    pxyz.pz = gRandom->Gaus(0,5) ;
    tree->Fill() ;
  }
  return tree ;
}