/////////////////////////////////////////////////////////////////////////
//
// 'ORGANIZATION AND SIMULTANEOUS FITS' RooFit tutorial macro #510
// 
//  Working with named parameter sets and parameter snapshots in 
//  workspaces
//
//  04/2009 - Wouter Verkerke 
//
/////////////////////////////////////////////////////////////////////////

#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooChebychev.h"
#include "RooAddPdf.h"
#include "RooWorkspace.h"
#include "RooPlot.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "TFile.h"
#include "TH1.h"
using namespace RooFit ;


void fillWorkspace(RooWorkspace& w) ;

void rf510_wsnamedsets()
{
  // C r e a t e   m o d e l   a n d   d a t a s e t
  // -----------------------------------------------

  RooWorkspace* w = new RooWorkspace("w") ;
  fillWorkspace(*w) ;

  // Exploit convention encoded in named set "parameters" and "observables"
  // to use workspace contents w/o need for introspected
  RooAbsPdf* model = w->pdf("model") ;

  // Generate data from p.d.f. in given observables
  RooDataSet* data = model->generate(*w->set("observables"),1000) ;

  // Fit model to data
  model->fitTo(*data) ;
  
  // Plot fitted model and data on frame of first (only) observable
  RooPlot* frame = ((RooRealVar*)w->set("observables")->first())->frame() ;
  data->plotOn(frame) ;
  model->plotOn(frame) ;

  // Overlay plot with model with reference parameters as stored in snapshots
  w->loadSnapshot("reference_fit") ;
  model->plotOn(frame,LineColor(kRed)) ;
  w->loadSnapshot("reference_fit_bkgonly") ;
  model->plotOn(frame,LineColor(kRed),LineStyle(kDashed)) ;


  // Draw the frame on the canvas
  new TCanvas("rf510_wsnamedsets","rf503_wsnamedsets",600,600) ;
  gPad->SetLeftMargin(0.15) ; frame->GetYaxis()->SetTitleOffset(1.4) ; frame->Draw() ;


  // Print workspace contents
  w->Print() ;


  // Workspace will remain in memory after macro finishes
  gDirectory->Add(w) ;

}



void fillWorkspace(RooWorkspace& w) 
{
  // C r e a t e   m o d e l
  // -----------------------

  // Declare observable x
  RooRealVar x("x","x",0,10) ;

  // Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
  RooRealVar mean("mean","mean of gaussians",5,0,10) ;
  RooRealVar sigma1("sigma1","width of gaussians",0.5) ;
  RooRealVar sigma2("sigma2","width of gaussians",1) ;

  RooGaussian sig1("sig1","Signal component 1",x,mean,sigma1) ;  
  RooGaussian sig2("sig2","Signal component 2",x,mean,sigma2) ;  
  
  // Build Chebychev polynomial p.d.f.  
  RooRealVar a0("a0","a0",0.5,0.,1.) ;
  RooRealVar a1("a1","a1",-0.2,0.,1.) ;
  RooChebychev bkg("bkg","Background",x,RooArgSet(a0,a1)) ;

  // Sum the signal components into a composite signal p.d.f.
  RooRealVar sig1frac("sig1frac","fraction of component 1 in signal",0.8,0.,1.) ;
  RooAddPdf sig("sig","Signal",RooArgList(sig1,sig2),sig1frac) ;

  // Sum the composite signal and background 
  RooRealVar bkgfrac("bkgfrac","fraction of background",0.5,0.,1.) ;
  RooAddPdf  model("model","g1+g2+a",RooArgList(bkg,sig),bkgfrac) ;

  // Import model into p.d.f.
  w.import(model) ;


  // E n c o d e   d e f i n i t i o n   o f   p a r a m e t e r s   i n   w o r k s p a c e
  // ---------------------------------------------------------------------------------------


  // Define named sets "parameters" and "observables", which list which variables should be considered
  // parameters and observables by the users convention
  // 
  // Variables appearing in sets _must_ live in the workspace already, or the autoImport flag
  // of defineSet must be set to import them on the fly. Named sets contain only references
  // to the original variables, therefore the value of observables in named sets already
  // reflect their 'current' value
  RooArgSet* params = (RooArgSet*) model.getParameters(x) ;
  w.defineSet("parameters",*params) ;
  w.defineSet("observables",x) ;


  // E n c o d e   r e f e r e n c e   v a l u e   f o r   p a r a m e t e r s   i n   w o r k s p a c e
  // ---------------------------------------------------------------------------------------------------


  // Define a parameter 'snapshot' in the p.d.f.
  // Unlike a named set, a parameter snapshot stores an independent set of values for
  // a given set of variables in the workspace. The values can be stored and reloaded
  // into the workspace variable objects using the loadSnapshot() and saveSnapshot()
  // methods. A snapshot saves the value of each variable, any errors that are stored
  // with it as well as the 'Constant' flag that is used in fits to determine if a 
  // parameter is kept fixed or not.

  // Do a dummy fit to a (supposedly) reference dataset here and store the results
  // of that fit into a snapshot
  RooDataSet* refData = model.generate(x,10000) ;
  model.fitTo(*refData,PrintLevel(-1)) ;
  
  // The kTRUE flag imports the values of the objects in (*params) into the workspace
  // If not set, the present values of the workspace parameters objects are stored
  w.saveSnapshot("reference_fit",*params,kTRUE) ;

  // Make another fit with the signal componentforced to zero
  // and save those parameters too

  bkgfrac.setVal(1) ;
  bkgfrac.setConstant(kTRUE) ;
  bkgfrac.removeError() ;
  model.fitTo(*refData,PrintLevel(-1)) ;  
  
  w.saveSnapshot("reference_fit_bkgonly",*params,kTRUE) ;
  

}