#ifndef NUMMODEL_HH
#define NUMMODEL_HH
////////////////////////////////////////////////////////////////////////////
//! author="Robert Crida"
//! lib=NumModel
//! date="2/2/1998"
//! userlevel=Normal
//! example=testNumModel.cc
//! file="amma/PatternRec/FuncTools/Model/BaseBody/NumModel.hh"
//! docentry="Numerical Methods.Multidimensional Models"
//! rcsid="$Id: NumModel.hh,v 1.8 2000/10/04 13:01:12 ees1cg Exp $"

#include "amma/Num/NumFunc.hh"
#include "amma/Num/NumModelB.hh"

// --------------------------------------------------------------------------
// **********  NumModelC  ***************************************************
// --------------------------------------------------------------------------
//: Handle class for numerical models of the form Y=f(X).
//
// Handle class for numerical models of the form Y=f(X) which are derived
// from NumFuncC so Y and X are vectors. The behaviour that is added over
// NumFuncC is that the relationship can be learnt using the Fit member
// function.

class NumModelC: public NumFuncC
{
public:
  NumModelC ();
  //: Default constructor

  NumModelC (istream &in);
  //: Constructs from stream

  NumModelC (const NumModelC &oth);
  //: Copy constructor

  NumModelC (NumModelBC &oth);
  //: Constructs from base class

protected:
  inline NumModelBC & Body()
    { return static_cast<NumModelBC&>(DPEntityC::Body()); }
  //: Access body.
  
  inline const NumModelBC & Body() const 
    { return static_cast<const NumModelBC&>(DPEntityC::Body()); }
  //: Access body.

public:

  NumModelC Copy () const;
  //: Makes a deep copy

  inline void Initialise (const NumVVDataSetC &train)
    { Body().Initialise(train); }
  //: Initialises model to an untrained state
  //!param: train - data set provided to give model example of data
  // Must be overloaded in derived class that train incrementally and provides
  // a mechanism for restarting training from scratch. Default behaviour is
  // to do nothing.
  
  inline void Fit (const NumVVDataSetC &train)
    { Body().Fit(train); }
  //: Used to train the model using set of input/output vectors
  // It should be assumed that the same sort of data will be provided for
  // fitting as was presented to the Initialise function previously. ie same
  // preprocessing should be applied as was appropriate for the initialisation
  // sample set.
};

//: Provides >> and << operators to streams
NUM_IO_OPERATORS(NumModelC);

///////////////////////////////////////////



#endif