225 lines
7.9 KiB
C++
225 lines
7.9 KiB
C++
//-----------------------------------------------------------------------------
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/** autocorrelation.cpp
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*
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* SV - 03/05/10
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*
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*/
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//-----------------------------------------------------------------------------
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// standard includes
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#define HAVE_SSTREAM
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#include <stdexcept> // runtime_error
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#include <iostream> // cout
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#include <sstream> // ostrstream, istrstream
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#include <fstream>
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#include <string.h>
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// the general include for eo
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#include <eo>
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// declaration of the namespace
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using namespace std;
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//-----------------------------------------------------------------------------
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// representation of solutions, and neighbors
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#include <ga/eoBit.h> // bit string : see also EO tutorial lesson 1: FirstBitGA.cpp
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#include <problems/bitString/moBitNeighbor.h> // neighbor of bit string
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//-----------------------------------------------------------------------------
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// fitness function, and evaluation of neighbors
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#include <eval/oneMaxEval.h>
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#include <problems/eval/moOneMaxIncrEval.h>
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#include <eval/moFullEvalByModif.h>
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//-----------------------------------------------------------------------------
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// neighborhood description
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#include <neighborhood/moRndWithReplNeighborhood.h> // visit one random neighbor possibly the same one several times
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//-----------------------------------------------------------------------------
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// the sampling class
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#include <sampling/moAutocorrelationSampling.h>
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//-----------------------------------------------------------------------------
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// the statistics class
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#include <sampling/moStatistics.h>
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// Declaration of types
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//-----------------------------------------------------------------------------
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// Indi is the typedef of the solution type like in paradisEO-eo
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typedef eoBit<unsigned int> Indi; // bit string with unsigned fitness type
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// Neighbor is the typedef of the neighbor type,
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// Neighbor = How to compute the neighbor from the solution + information on it (i.e. fitness)
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// all classes from paradisEO-mo use this template type
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typedef moBitNeighbor<unsigned int> Neighbor ; // bit string neighbor with unsigned fitness type
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void main_function(int argc, char **argv)
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{
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/* =========================================================
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*
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* Parameters
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*
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* ========================================================= */
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// more information on the input parameters: see EO tutorial lesson 3
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// but don't care at first it just read the parameters of the bit string size and the random seed.
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// First define a parser from the command-line arguments
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eoParser parser(argc, argv);
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// For each parameter, define Parameter, read it through the parser,
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// and assign the value to the variable
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// random seed parameter
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eoValueParam<uint32_t> seedParam(time(0), "seed", "Random number seed", 'S');
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parser.processParam( seedParam );
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unsigned seed = seedParam.value();
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// length of the bit string
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eoValueParam<unsigned int> vecSizeParam(20, "vecSize", "Genotype size", 'V');
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parser.processParam( vecSizeParam, "Representation" );
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unsigned vecSize = vecSizeParam.value();
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// the number of steps of the random walk
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eoValueParam<unsigned int> stepParam(100, "nbStep", "Number of steps of the random walk", 'n');
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parser.processParam( stepParam, "Representation" );
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unsigned nbStep = stepParam.value();
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// the name of the output file
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string str_out = "out.dat"; // default value
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eoValueParam<string> outParam(str_out.c_str(), "out", "Output file of the sampling", 'o');
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parser.processParam(outParam, "Persistence" );
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// the name of the "status" file where all actual parameter values will be saved
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string str_status = parser.ProgramName() + ".status"; // default value
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eoValueParam<string> statusParam(str_status.c_str(), "status", "Status file");
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parser.processParam( statusParam, "Persistence" );
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// do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
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// i.e. in case you need parameters somewhere else, postpone these
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if (parser.userNeedsHelp()) {
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parser.printHelp(cout);
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exit(1);
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}
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if (statusParam.value() != "") {
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ofstream os(statusParam.value().c_str());
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os << parser;// and you can use that file as parameter file
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}
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/* =========================================================
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*
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* Random seed
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*
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* ========================================================= */
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// reproducible random seed: if you don't change SEED above,
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// you'll aways get the same result, NOT a random run
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// more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
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rng.reseed(seed);
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/* =========================================================
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*
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* Initialization of the solution
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*
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* ========================================================= */
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// a Indi random initializer: each bit is random
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// more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
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eoUniformGenerator<bool> uGen;
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eoInitFixedLength<Indi> random(vecSize, uGen);
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/* =========================================================
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*
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* Eval fitness function (full evaluation)
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*
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* ========================================================= */
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// the fitness function is just the number of 1 in the bit string
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oneMaxEval<Indi> fullEval;
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/* =========================================================
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*
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* evaluation of a neighbor solution
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*
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* ========================================================= */
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// Use it if there is no incremental evaluation: a neighbor is evaluated by the full evaluation of a solution
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// moFullEvalByModif<Neighbor> neighborEval(fullEval);
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// Incremental evaluation of the neighbor: fitness is modified by +/- 1
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moOneMaxIncrEval<Neighbor> neighborEval;
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/* =========================================================
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*
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* the neighborhood of a solution
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*
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* ========================================================= */
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// Exploration of the neighborhood in random order
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// at each step one bit is randomly generated
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moRndWithReplNeighborhood<Neighbor> neighborhood(vecSize);
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/* =========================================================
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*
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* The sampling of the search space
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*
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* ========================================================= */
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// sampling object :
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// - random initialization
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// - neighborhood to compute the next step
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// - fitness function
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// - neighbor evaluation
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// - number of steps of the walk
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moAutocorrelationSampling<Neighbor> sampling(random, neighborhood, fullEval, neighborEval, nbStep);
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/* =========================================================
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*
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* execute the sampling
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*
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* ========================================================= */
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sampling();
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/* =========================================================
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*
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* export the sampling
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*
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* ========================================================= */
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// to export the statistics into file
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sampling.fileExport(str_out);
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// to get the values of statistics
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// so, you can compute some statistics in c++ from the data
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const std::vector<double> & fitnessValues = sampling.getValues(0);
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std::cout << "First values:" << std::endl;
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std::cout << "Fitness " << fitnessValues[0] << std::endl;
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std::cout << "Last values:" << std::endl;
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std::cout << "Fitness " << fitnessValues[fitnessValues.size() - 1] << std::endl;
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// more basic statistics on the distribution:
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moStatistics statistics;
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vector<double> rho, phi;
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statistics.autocorrelation(fitnessValues, 10, rho, phi);
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for (unsigned s = 0; s < rho.size(); s++)
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std::cout << s << " " << "rho=" << rho[s] << ", phi=" << phi[s] << std::endl;
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}
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// A main that catches the exceptions
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int main(int argc, char **argv)
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{
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try {
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main_function(argc, argv);
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}
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catch (exception& e) {
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cout << "Exception: " << e.what() << '\n';
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}
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return 1;
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}
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