/* 
* <main.cpp>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, INRIA, 2007
*
* Clive Canape
*
* This software is governed by the CeCILL license under French law and
* abiding by the rules of distribution of free software.  You can  use,
* modify and/ or redistribute the software under the terms of the CeCILL
* license as circulated by CEA, CNRS and INRIA at the following URL
* "http://www.cecill.info".
*
* As a counterpart to the access to the source code and  rights to copy,
* modify and redistribute granted by the license, users are provided only
* with a limited warranty  and the software's author,  the holder of the
* economic rights,  and the successive licensors  have only  limited liability.
*
* In this respect, the user's attention is drawn to the risks associated
* with loading,  using,  modifying and/or developing or reproducing the
* software by the user in light of its specific status of free software,
* that may mean  that it is complicated to manipulate,  and  that  also
* therefore means  that it is reserved for developers  and  experienced
* professionals having in-depth computer knowledge. Users are therefore
* encouraged to load and test the software's suitability as regards their
* requirements in conditions enabling the security of their systems and/or
* data to be ensured and,  more generally, to use and operate it in the
* same conditions as regards security.
* The fact that you are presently reading this means that you have had
* knowledge of the CeCILL license and that you accept its terms.
*
* ParadisEO WebSite : http://paradiseo.gforge.inria.fr
* Contact: paradiseo-help@lists.gforge.inria.fr
*          
*/

#include <peo>
#include <es.h>

typedef eoReal<double> Indi;

//Evaluation function

double f (const Indi & _indi)
{  
    // Rosenbrock function f(x) = 100*(x[1]-x[0]^2)^2+(1-x[0])^2 
    // => optimal : f* = 0 , with x* =(1,1)
    
    double sum;
    sum=_indi[1]-pow(_indi[0],2);
    sum=100*pow(sum,2);
    sum+=pow((1-_indi[0]),2);
    return (-sum);
}

int main (int __argc, char *__argv[])
{


// Initialization of the parallel environment : thanks this instruction, ParadisEO-PEO can initialize himself
    peo :: init( __argc, __argv );

//Parameters

    const unsigned int VEC_SIZE = 2;  // Don't change this parameter when you are resolving the Rosenbrock function      
    const unsigned int POP_SIZE = 20; // As with a sequential algorithm, you change the size of the population       
    const unsigned int MAX_GEN = 300; // Define the number of maximal generation
    const double INIT_POSITION_MIN = -2.0;  // For initialize x
    const double INIT_POSITION_MAX = 2.0;   // In the case of the Rosenbrock function : -2 < x[i] < 2
    const float CROSS_RATE = 0.8; // Crossover rate
    const double EPSILON = 0.01;  // Range for real uniform mutation
    const float MUT_RATE = 0.3;   // Mutation rate
    rng.reseed (time(0));
          
// Stopping
    eoGenContinue < Indi > genContPara (MAX_GEN);
    eoCombinedContinue <Indi> continuatorPara (genContPara);
    eoCheckPoint<Indi> checkpoint(continuatorPara);  
    
    
 /* In this lesson, you should define a peoEvalFunc witch will allow to initialize :
  * 
  *    - peoSeqPopEval : using to the sequential evaluation
  * 
  *   OR
  * 
  *    - peoParaPopEval : using to the parallel evaluation
  * 
  */   

// For a parallel evaluation
	peoEvalFunc<Indi> plainEval(f);
	peoParaPopEval< Indi > eval(plainEval);
  
                 
// Initialization 
    eoUniformGenerator < double >uGen (INIT_POSITION_MIN, INIT_POSITION_MAX);
    eoInitFixedLength < Indi > random (VEC_SIZE, uGen);
    
// Selection
	eoRankingSelect<Indi> selectionStrategy;
	eoSelectNumber<Indi> select(selectionStrategy,POP_SIZE);
    
// Transformation
    eoSegmentCrossover<Indi> crossover; // Crossover
    eoUniformMutation<Indi>  mutation(EPSILON);  // Mutation
    eoSGATransform<Indi> transform(crossover,CROSS_RATE,mutation,MUT_RATE);
	peoSeqTransform<Indi> eaTransform(transform); 
	
// Replacement
	eoPlusReplacement<Indi> replace;  
	
// Creation of the population
    eoPop < Indi > pop;
    pop.append (POP_SIZE, random);    

//Parallel algorithm
	peoEA<Indi> Algo(checkpoint,eval,select,eaTransform,replace);
	Algo(pop);
   
    peo :: run(); 
    peo :: finalize();
    if(getNodeRank()==1)
		std::cout << "Final population :\n" << pop << std::endl;
}