/*
The Evolving Distribution Objects framework (EDO) is a template-based, 
ANSI-C++ evolutionary computation library which helps you to write your 
own estimation of distribution algorithms.

This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.

This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA

Copyright (C) 2010 Thales group
*/
/*
Authors:
    Johann Dréo <johann.dreo@thalesgroup.com>
    Caner Candan <caner.candan@thalesgroup.com>
*/

#ifndef _edoSampler_h
#define _edoSampler_h

#include <eoFunctor.h>

#include "edoBounder.h"
#include "edoBounderNo.h"

template < typename D >
class edoSampler : public eoUF< D&, typename D::EOType >
{
public:
    typedef typename D::EOType EOType;

    edoSampler(edoBounder< EOType > & bounder)
	: /*_dummy_bounder(),*/ _bounder(bounder)
    {}

    /*
    edoSampler()
	: _dummy_bounder(), _bounder( _dummy_bounder )
    {}
    */

    // virtual EOType operator()( D& ) = 0 (provided by eoUF< A1, R >)

    virtual EOType sample( D& ) = 0;

    EOType operator()( D& distrib )
    {
	unsigned int size = distrib.size();
	assert(size > 0);


	//-------------------------------------------------------------
	// Point we want to sample to get higher a set of points
	// (coordinates in n dimension)
	// x = {x1, x2, ..., xn}
	// the sample method is implemented in the derivated class
	//-------------------------------------------------------------

	EOType solution(sample(distrib));

	//-------------------------------------------------------------


	//-------------------------------------------------------------
	// Now we are bounding the distribution thanks to min and max
	// parameters.
	//-------------------------------------------------------------

	_bounder(solution);

	//-------------------------------------------------------------


	return solution;
    }

private:
    //edoBounderNo<EOType> _dummy_bounder;

    //! Bounder functor
    edoBounder< EOType > & _bounder;

};

#endif // !_edoSampler_h