FunctionMinEvalOp.cpp

#include <ECF/ECF.h>
#include "FunctionMinEvalOp.h"
#include <float.h>
#include <fstream>
 
 
// CEC externals
extern void cec14_test_func(double *, double *, int, int, int);
double *OShift,*M,*y,*z,*x_bound;
int ini_flag=0,n_flag,func_flag,*SS;
 
 
void FunctionMinEvalOp::registerParameters(StateP state)
{
    state->getRegistry()->registerEntry("cec.function", (voidP) (new uint(1)), ECF::UINT, 
        "Sets the CEC test function number, 1-30 (default: 1)");
}
 
 
bool FunctionMinEvalOp::initialize(StateP state)
{
    voidP sptr = state->getRegistry()->getEntry("cec.function"); // get parameter value
    iFunction_ = *((uint*) sptr.get()); // convert from voidP to user defined type
 
    // check function index (CEC does not abort on invalid id)
    if(iFunction_ < 1 || iFunction_ > 30) {
        ECF_LOG_ERROR(state, "CEC EvalOp: There are only 30 test functions in this test suite!");
        throw("");
    }
 
    // check for CEC input files
    std::string fileName("input_data/M_" + uint2str(iFunction_) + "_D2.txt");
    ifstream m_file(fileName.c_str());
    if (!m_file) {
        std::string msg("\nError: the CEC input data folder must be in path to run the experiments.\n");
        msg += "DOWNLOAD the required data and place them in \"input_data\" folder from http://web.mysites.ntu.edu.sg/epnsugan/PublicSite/Shared%20Documents/CEC-2014/cec14-c-code.zip.\n";
        msg += "Since the data size is 35MB, it is NOT included in the ECF package.";
        ECF_LOG_ERROR(state, msg);
        throw("");
    }
 
    return true;
}
 
 
FitnessP FunctionMinEvalOp::evaluate(IndividualP individual)
{
    // evaluation creates a new fitness object using a smart pointer
    // in our case, we try to minimize the function value, so we use FitnessMin fitness (for minimization problems)
    FitnessP fitness (new FitnessMin);
 
    // we define FloatingPoint as the only genotype (in the configuration file)
    FloatingPoint::FloatingPoint* gen = (FloatingPoint::FloatingPoint*) individual->getGenotype().get();
    // (you can also use boost smart pointers:)
    //FloatingPointP gen = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (individual->getGenotype());
 
    // alternative encoding: Binary Genotype
    //Binary::Binary* gen = (Binary::Binary*) individual->getGenotype().get();
    //BinaryP gen = boost::dynamic_pointer_cast<Binary::Binary> (individual->getGenotype());
 
    // we implement the fitness function 'as is', without any translation
    // the number of variables is read from the genotype itself (size of 'realValue' vactor)
    double realTemp = 0, value = 0;
 
    int n = (int) gen->realValue.size();
 
    // call external CEC 2014 evaluator
    cec14_test_func(&gen->realValue[0], &value, n, 1, iFunction_);
 
    fitness->setValue(value);
    return fitness;
}