private void Initiation()
{
Console.WriteLine("\n=== Starting Initiation ===");
Console.WriteLine("Population Size: {0};\nGenome Size: {1};\nGene Value Range: [{2}; {3}]\n\n",
this.PopulationSize, this.GenomeSize, Specimen.MinGeneValue, Specimen.MaxGeneValue);
_currGeneration = new List <Specimen>();
var newSpecies = Enumerable.Range(0, PopulationSize).AsParallel().Select(i =>
{
var newSpec = new Specimen
{
Length = this.GenomeSize
};
SpecimenHelper.GenerateGenes(ref newSpec);
var fitness = FitnessFunction(newSpec);
// FIXME: Replace '1e5' magic number with well described constant
newSpec.Fitness = double.IsNaN(fitness) ? 0 : (double.IsInfinity(fitness) ? 1e5 : fitness);
Console.WriteLine("Specimen {1} has Fitness: {0}", newSpec.Fitness, i);
return(newSpec);
}).OrderBy(s => s.Fitness).Take(this.PopulationSize);
_currGeneration = newSpecies.ToList(); // Huge load starts here :)
_fitnessTable = new List <double>();
foreach (var spec in _currGeneration)
{
if (!_fitnessTable.Any())
{
_fitnessTable.Add(spec.Fitness);
}
else
{
_fitnessTable.Add(_fitnessTable.Last() + spec.Fitness);
}
}
TotalFitness = _currGeneration.Sum(spec => spec.Fitness);
var best = _currGeneration.Last();
Console.WriteLine("=== Initiation Result ===\n");
Console.WriteLine("Best Specimen:\n{0}", best.Print());
}
static void Main(string[] args)
{
if (args.Length > 0)
{
var cmd = args[0].ToLower(CultureInfo.InvariantCulture);
switch (cmd)
{
case "simulate":
case "simulation":
InitializeSimulator();
FedKfSim.PrintSimResults = true;
var spec = new Specimen();
SpecimenHelper.SetGenes(ref spec, ReadSimulationGenes());
FedKfSim.Simulate(spec);
break;
case "set":
var settingName = args[1];
var settingValue = args[2];
var config = ConfigurationManager.OpenExeConfiguration(ConfigurationUserLevel.None);
config.AppSettings.Settings[settingName].Value = settingValue;
config.Save(ConfigurationSaveMode.Modified);
ConfigurationManager.RefreshSection("appSettings");
Console.WriteLine("'{0}' set to {1}", settingName, settingValue);
break;
case "print":
Console.WriteLine("Current settings:");
foreach (var name in ConfigurationManager.AppSettings.AllKeys.AsParallel())
{
var value = ConfigurationManager.AppSettings[name];
Console.WriteLine("'{0}' => {1}", name, value);
}
break;
case "help":
case "?":
case "-h":
PrintHelp();
break;
default:
Console.Error.WriteLine(string.Format("\nARGUMENT ERROR\n'{0}' is unknown command!\n", cmd));
PrintHelp();
break;
}
}
else
{
InitializeSimulator();
var genCount = int.Parse(ConfigurationManager.AppSettings["GenerationsCount"]);
var popSize = int.Parse(ConfigurationManager.AppSettings["PopulationSize"]);
var crossOver = double.Parse(ConfigurationManager.AppSettings["CrossoverRate"], FileParser.NumberFormat);
var mutRate = double.Parse(ConfigurationManager.AppSettings["MutationRate"], FileParser.NumberFormat);
var maxGeneVal = double.Parse(ConfigurationManager.AppSettings["MaxGeneValue"], FileParser.NumberFormat);
var minGeneVal = double.Parse(ConfigurationManager.AppSettings["MinGeneValue"], FileParser.NumberFormat);
var genomeLength = int.Parse(ConfigurationManager.AppSettings["GenomeLength"]);
SpecimenHelper.SimilarityThreshold = double.Parse(
ConfigurationManager.AppSettings["SimilarityThreshold"], FileParser.NumberFormat);
var ga = new Ga(genomeLength)
{
FitnessFunction = FedKfSim.Simulate,
Elitism = true,
GenerationsCount = genCount,
PopulationSize = popSize,
CrossoverRate = crossOver,
MutationRate = mutRate
};
FedKfSim.PrintSimResults = false;
ga.Go(maxGeneVal, minGeneVal);
}
Console.ReadLine();
}
