/*****************************************************************************
 * Project: RooFit                                                           *
 * Package: RooFitCore                                                       *
 * @(#)root/roofit:$Id$
 * Authors:                                                                  *
 *   WV, Wouter Verkerke, UC Santa Barbara, verkerke@slac.stanford.edu       *
 *   DK, David Kirkby,    UC Irvine,         dkirkby@uci.edu                 *
 *                                                                           *
 * Copyright (c) 2000-2005, Regents of the University of California          *
 *                          and Stanford University. All rights reserved.    *
 *                                                                           *
 * Redistribution and use in source and binary forms,                        *
 * with or without modification, are permitted according to the terms        *
 * listed in LICENSE (http://roofit.sourceforge.net/license.txt)             *
 *****************************************************************************/

//////////////////////////////////////////////////////////////////////////////
//
// BEGIN_HTML
// RooHistFunc implements a real-valued function sampled from a 
// multidimensional histogram. The histogram can have an arbitrary number of real or 
// discrete dimensions and may have negative values
// END_HTML
//

#include "RooFit.h"
#include "Riostream.h"

#include "RooHistFunc.h"
#include "RooDataHist.h"
#include "RooMsgService.h"
#include "RooRealVar.h"
#include "RooCategory.h"
#include "RooWorkspace.h"

#include "TError.h"

using namespace std;

ClassImp(RooHistFunc)
;



//_____________________________________________________________________________
RooHistFunc::RooHistFunc() :
  _dataHist(0),
  _intOrder(0),
  _cdfBoundaries(kFALSE),
  _totVolume(0),
  _unitNorm(kFALSE)
{
  // Default constructor
}


//_____________________________________________________________________________
RooHistFunc::RooHistFunc(const char *name, const char *title, const RooArgSet& vars, 
		       const RooDataHist& dhist, Int_t intOrder) :
  RooAbsReal(name,title), 
  _depList("depList","List of dependents",this),
  _dataHist((RooDataHist*)&dhist), 
  _codeReg(10),
  _intOrder(intOrder),
  _cdfBoundaries(kFALSE),
  _totVolume(0),
  _unitNorm(kFALSE)
{
  // Constructor from a RooDataHist. The variable listed in 'vars' control the dimensionality of the
  // function. Any additional dimensions present in 'dhist' will be projected out. RooDataHist dimensions
  // can be either real or discrete. See RooDataHist::RooDataHist for details on the binning.
  // RooHistFunc neither owns or clone 'dhist' and the user must ensure the input histogram exists
  // for the entire life span of this function.

  _depList.add(vars) ;

  // Verify that vars and dhist.get() have identical contents
  const RooArgSet* dvars = dhist.get() ;
  if (vars.getSize()!=dvars->getSize()) {
    coutE(InputArguments) << "RooHistFunc::ctor(" << GetName() 
			  << ") ERROR variable list and RooDataHist must contain the same variables." << endl ;
    assert(0) ;
  }
  TIterator* iter = vars.createIterator() ;
  RooAbsArg* arg ;
  while((arg=(RooAbsArg*)iter->Next())) {
    if (!dvars->find(arg->GetName())) {
      coutE(InputArguments) << "RooHistFunc::ctor(" << GetName() 
			    << ") ERROR variable list and RooDataHist must contain the same variables." << endl ;
      assert(0) ;
    }
  }
  delete iter ;

}



//_____________________________________________________________________________
RooHistFunc::RooHistFunc(const RooHistFunc& other, const char* name) :
  RooAbsReal(other,name), 
  _depList("depList",this,other._depList),
  _dataHist(other._dataHist),
  _codeReg(other._codeReg),
  _intOrder(other._intOrder),
  _cdfBoundaries(other._cdfBoundaries),
  _totVolume(other._totVolume),
  _unitNorm(other._unitNorm)
{
  // Copy constructor
}



//_____________________________________________________________________________
Double_t RooHistFunc::evaluate() const
{
  // Return the current value: The value of the bin enclosing the current coordinates
  // of the dependents, normalized by the histograms contents. Interpolation
  // is applied if the RooHistFunc is configured to do that

  Double_t ret =  _dataHist->weight(_depList,_intOrder,kFALSE,_cdfBoundaries) ;  
  return ret ;
}

//_____________________________________________________________________________
Int_t RooHistFunc::getMaxVal(const RooArgSet& vars) const 
{
  // Only handle case of maximum in all variables
  RooAbsCollection* common = _depList.selectCommon(vars) ;
  if (common->getSize()==_depList.getSize()) {
    delete common ;
    return 1;
  }
  delete common ;
  return 0 ;
}

//_____________________________________________________________________________
Double_t RooHistFunc::maxVal(Int_t code) const 
{
  R__ASSERT(code==1) ;

  Double_t max(-1) ;
  for (Int_t i=0 ; i<_dataHist->numEntries() ; i++) {
    _dataHist->get(i) ;
    Double_t wgt = _dataHist->weight() ;
    if (wgt>max) max=wgt ;
  }

  return max*1.05 ;
}

//_____________________________________________________________________________
Double_t RooHistFunc::totVolume() const
{
  // Return the total volume spanned by the observables of the RooDataHist

  // Return previously calculated value, if any
  if (_totVolume>0) {
    return _totVolume ;
  }
  _totVolume = 1. ;
  TIterator* iter = _depList.createIterator() ;
  RooAbsArg* arg ;
  while((arg=(RooAbsArg*)iter->Next())) {
    RooRealVar* real = dynamic_cast<RooRealVar*>(arg) ;
    if (real) {
      _totVolume *= (real->getMax()-real->getMin()) ;
    } else {
      RooCategory* cat = dynamic_cast<RooCategory*>(arg) ;
      if (cat) {
	_totVolume *= cat->numTypes() ;
      }
    }
  }
  delete iter ;
  return _totVolume ;
}



//_____________________________________________________________________________
Int_t RooHistFunc::getAnalyticalIntegral(RooArgSet& allVars, RooArgSet& analVars, const char* rangeName) const 
{
  // Determine integration scenario. If no interpolation is used,
  // RooHistFunc can perform all integrals over its dependents
  // analytically via partial or complete summation of the input
  // histogram. If interpolation is used, only the integral
  // over all RooHistPdf observables is implemented.


  // Only analytical integrals over the full range are defined
  if (rangeName!=0) {
    return 0 ;
  }

  // Simplest scenario, integrate over all dependents
  RooAbsCollection *allVarsCommon = allVars.selectCommon(_depList) ;  
  Bool_t intAllObs = (allVarsCommon->getSize()==_depList.getSize()) ;  
  delete allVarsCommon ;
  if (intAllObs && matchArgs(allVars,analVars,_depList)) {
    return 1000 ;
  }

  // Disable partial analytical integrals if interpolation is used
  if (_intOrder>0) {
    return 0 ;
  }

  // Find subset of _depList that integration is requested over
  RooArgSet* allVarsSel = (RooArgSet*) allVars.selectCommon(_depList) ;
  if (allVarsSel->getSize()==0) {
    delete allVarsSel ;
    return 0 ;
  }

  // Partial integration scenarios.
  // Build unique code from bit mask of integrated variables in depList
  Int_t code(0),n(0) ;
  TIterator* iter = _depList.createIterator() ;
  RooAbsArg* arg ;
  while((arg=(RooAbsArg*)iter->Next())) {
    if (allVars.find(arg->GetName())) code |= (1<<n) ;
    n++ ;
  }
  delete iter ;
  analVars.add(*allVarsSel) ;

  return code ;

}



//_____________________________________________________________________________
Double_t RooHistFunc::analyticalIntegral(Int_t code, const char* /*rangeName*/) const 
{
  // Return integral identified by 'code'. The actual integration
  // is deferred to RooDataHist::sum() which implements partial
  // or complete summation over the histograms contents

  // WVE needs adaptation for rangeName feature

  // Simplest scenario, integration over all dependents
  if (code==1000) {
    return _dataHist->sum(kTRUE) ;
  }

  // Partial integration scenario, retrieve set of variables, calculate partial sum
  RooArgSet intSet ;
  TIterator* iter = _depList.createIterator() ;
  RooAbsArg* arg ;
  Int_t n(0) ;
  while((arg=(RooAbsArg*)iter->Next())) {
    if (code & (1<<n)) {
      intSet.add(*arg) ;
    }
    n++ ;
  }
  delete iter ;

  Double_t ret =  _dataHist->sum(intSet,_depList,kTRUE) ;
  return ret ;
}



//_____________________________________________________________________________
list<Double_t>* RooHistFunc::plotSamplingHint(RooAbsRealLValue& obs, Double_t xlo, Double_t xhi) const
{
  // Return sampling hint for making curves of (projections) of this function
  // as the recursive division strategy of RooCurve cannot deal efficiently
  // with the vertical lines that occur in a non-interpolated histogram

  // No hints are required when interpolation is used
  if (_intOrder>1) {
    return 0 ;
  }

  // Check that observable is in dataset, if not no hint is generated
  RooAbsLValue* lvarg = dynamic_cast<RooAbsLValue*>(_dataHist->get()->find(obs.GetName())) ;
  if (!lvarg) {
    return 0 ;
  }

  // Retrieve position of all bin boundaries
  const RooAbsBinning* binning = lvarg->getBinningPtr(0) ;
  Double_t* boundaries = binning->array() ;

  list<Double_t>* hint = new list<Double_t> ;

  // Widen range slighty
  xlo = xlo - 0.01*(xhi-xlo) ;
  xhi = xhi + 0.01*(xhi-xlo) ;

  Double_t delta = (xhi-xlo)*1e-8 ;
 
  // Construct array with pairs of points positioned epsilon to the left and
  // right of the bin boundaries
  for (Int_t i=0 ; i<binning->numBoundaries() ; i++) {
    if (boundaries[i]>=xlo && boundaries[i]<=xhi) {
      hint->push_back(boundaries[i]-delta) ;
      hint->push_back(boundaries[i]+delta) ;
    }
  }

  return hint ;
}


//______________________________________________________________________________
std::list<Double_t>* RooHistFunc::binBoundaries(RooAbsRealLValue& obs, Double_t xlo, Double_t xhi) const 
{
  // Return sampling hint for making curves of (projections) of this function
  // as the recursive division strategy of RooCurve cannot deal efficiently
  // with the vertical lines that occur in a non-interpolated histogram

  // No hints are required when interpolation is used
  if (_intOrder>1) {
    return 0 ;
  }

  // Check that observable is in dataset, if not no hint is generated
  RooAbsLValue* lvarg = dynamic_cast<RooAbsLValue*>(_dataHist->get()->find(obs.GetName())) ;
  if (!lvarg) {
    return 0 ;
  }

  // Retrieve position of all bin boundaries
  const RooAbsBinning* binning = lvarg->getBinningPtr(0) ;
  Double_t* boundaries = binning->array() ;

  list<Double_t>* hint = new list<Double_t> ;

  // Construct array with pairs of points positioned epsilon to the left and
  // right of the bin boundaries
  for (Int_t i=0 ; i<binning->numBoundaries() ; i++) {
    if (boundaries[i]>=xlo && boundaries[i]<=xhi) {
      hint->push_back(boundaries[i]) ;
    }
  }

  return hint ;
}


//_____________________________________________________________________________
Bool_t RooHistFunc::importWorkspaceHook(RooWorkspace& ws) 
{  
  // Check if our datahist is already in the workspace
  std::list<RooAbsData*> allData = ws.allEmbeddedData() ;
  std::list<RooAbsData*>::const_iterator iter ;
  for (iter = allData.begin() ; iter != allData.end() ; ++iter) {
    // If your dataset is already in this workspace nothing needs to be done
    if (*iter == _dataHist) {
      return kFALSE ;
    }
  }

  // Check if dataset with given name already exists
  RooAbsData* wsdata = ws.embeddedData(_dataHist->GetName()) ;

  if (wsdata) {

    // Yes it exists - now check if it is identical to our internal histogram 
    if (wsdata->InheritsFrom(RooDataHist::Class())) {

      // Check if histograms are identical
      if (areIdentical((RooDataHist&)*wsdata,*_dataHist)) {

	// Exists and is of correct type, and identical -- adjust internal pointer to WS copy
	_dataHist = (RooDataHist*) wsdata ;
      } else {

	// not identical, clone rename and import
	TString uniqueName = Form("%s_%s",_dataHist->GetName(),GetName()) ;
	Bool_t flag = ws.import(*_dataHist,RooFit::Rename(uniqueName.Data()),RooFit::Embedded()) ;
	if (flag) {
	  coutE(ObjectHandling) << " RooHistPdf::importWorkspaceHook(" << GetName() << ") unable to import clone of underlying RooDataHist with unique name " << uniqueName << ", abort" << endl ;
	  return kTRUE ;
	}
	_dataHist = (RooDataHist*) ws.embeddedData(uniqueName.Data()) ;
      }

    } else {

      // Exists and is NOT of correct type: clone rename and import
      TString uniqueName = Form("%s_%s",_dataHist->GetName(),GetName()) ;
      Bool_t flag = ws.import(*_dataHist,RooFit::Rename(uniqueName.Data()),RooFit::Embedded()) ;
      if (flag) {
	coutE(ObjectHandling) << " RooHistPdf::importWorkspaceHook(" << GetName() << ") unable to import clone of underlying RooDataHist with unique name " << uniqueName << ", abort" << endl ;
	return kTRUE ;
      }
      _dataHist = (RooDataHist*) ws.embeddedData(uniqueName.Data()) ;
      
    }
    return kFALSE ;
  }
  
  // We need to import our datahist into the workspace
  ws.import(*_dataHist,RooFit::Embedded()) ;
  
  // Redirect our internal pointer to the copy in the workspace
  _dataHist = (RooDataHist*) ws.embeddedData(_dataHist->GetName()) ;
  return kFALSE ;
}


//_____________________________________________________________________________
Bool_t RooHistFunc::areIdentical(const RooDataHist& dh1, const RooDataHist& dh2) 
{
  if (fabs(dh1.sumEntries()-dh2.sumEntries())>1e-8) return kFALSE ;
  if (dh1.numEntries() != dh2.numEntries()) return kFALSE ;
  for (int i=0 ; i < dh1.numEntries() ; i++) {
    dh1.get(i) ;
    dh2.get(i) ;
    if (fabs(dh1.weight()-dh2.weight())>1e-8) return kFALSE ;
  }
  return kTRUE ;
}



//______________________________________________________________________________
void RooHistFunc::Streamer(TBuffer &R__b)
{
   // Stream an object of class RooHistFunc.

   if (R__b.IsReading()) {
      R__b.ReadClassBuffer(RooHistFunc::Class(),this);
      // WVE - interim solution - fix proxies here
      _proxyList.Clear() ;
      registerProxy(_depList) ;
   } else {
      R__b.WriteClassBuffer(RooHistFunc::Class(),this);
   }
}