public void Resume(GAFunction fitnessFunc, OnGeneration onGenerationFunc)
{
FitnessFunction = fitnessFunc;
OnGenerationFunction = onGenerationFunc;
Go(true);
}
public StringFunction(Func <IFitness> getFitnessMethod, GAStatus bestStatus, GAFunction fitnessFunc, OnGeneration generationFunc, double crossoverRate, double mutationRate, int genomeSize, TargetParams targetParams)
{
_getFitnessFunc = getFitnessMethod;
_bestStatus = bestStatus;
_crossoverRate = crossoverRate;
_mutationRate = mutationRate;
_genomeSize = genomeSize;
_fitnessFunc = fitnessFunc;
_generationFunc = generationFunc;
_targetParams = targetParams;
}
public StringFunction(Func<IFitness> getFitnessMethod, GAStatus bestStatus, GAFunction fitnessFunc, OnGeneration generationFunc, double crossoverRate, double mutationRate, int genomeSize, TargetParams targetParams)
{
_getFitnessFunc = getFitnessMethod;
_bestStatus = bestStatus;
_crossoverRate = crossoverRate;
_mutationRate = mutationRate;
_genomeSize = genomeSize;
_fitnessFunc = fitnessFunc;
_generationFunc = generationFunc;
_targetParams = targetParams;
}
public StringFunctionChunk(Func <IFitness> getFitnessMethod, Action <string, object> onStepComplete, GAStatus bestStatus, GAFunction fitnessFunc, OnGeneration generationFunc, double crossoverRate, double mutationRate, int genomeSize, TargetParams targetParams, int chunkSize = 4)
{
_getFitnessFunc = getFitnessMethod;
_onStepComplete = onStepComplete;
_bestStatus = bestStatus;
_crossoverRate = crossoverRate;
_mutationRate = mutationRate;
_genomeSize = genomeSize;
_fitnessFunc = fitnessFunc;
_generationFunc = generationFunc;
_targetParams = targetParams;
_chunkSize = chunkSize;
}
public void InitializeGA(NetworkInitializer initializer, Func <double[], double> fitnessFunction)
{
var input = (GeneticInitializer)initializer;
this.crossover = input.Crossover;
this.iterations = input.Iterations;
this.mutationRate = input.MutationRate;
this.populationSize = input.PopulationSize;
InitializeWeights(initializer);
ga = new GA(crossover, mutationRate, populationSize, iterations, weights);
ga.Elitism = true;
GAFunction func = new GAFunction(fitnessFunction);
ga.FitnessFunction = func;
}
/// <summary>
/// Setup the genetic algorithm and run it.
/// </summary>
/// <returns>Best brain's output source code</returns>
public static string Run(IGeneticAlgorithm iga, GAFunction fitnessFunc, OnGeneration generationFunc, Action setupFunc = null, bool resume = false)
{
GA ga = (GA)iga;
if (!resume)
{
if (setupFunc != null)
{
// Perform any additional setup for this fitness.
setupFunc();
}
try
{
// Delete any existing dat file.
File.Delete(Directory.GetCurrentDirectory() + "\\my-genetic-algorithm.dat");
}
catch (Exception excep)
{
Console.WriteLine("Unable to delete " + Directory.GetCurrentDirectory() + "\\my-genetic-algorithm.dat\n" + excep.Message);
}
// Start a new genetic algorithm.
ga.GAParams.Elitism = true;
ga.GAParams.HistoryPath = Directory.GetCurrentDirectory() + "\\history.txt";
ga.FitnessFunction = new GAFunction(fitnessFunc);
ga.OnGenerationFunction = new OnGeneration(generationFunc);
ga.Go();
}
else
{
// Load a saved genetic algorithm.
ga.Load("my-genetic-algorithm.dat");
ga.Resume(fitnessFunc, generationFunc);
}
// Results.
double[] weights;
double fitness;
ga.GetBest(out weights, out fitness);
Console.WriteLine("***** DONE! *****");
return(CommonManager.ConvertDoubleArrayToBF(weights));
}
/// <summary>
/// Setup the genetic algorithm and run it.
/// </summary>
/// <returns>Best brain's output source code</returns>
public static string Run(IGeneticAlgorithm iga, GAFunction fitnessFunc, OnGeneration generationFunc, Action setupFunc = null, bool resume = false)
{
GA ga = (GA)iga;
if (!resume)
{
if (setupFunc != null)
{
// Perform any additional setup for this fitness.
setupFunc();
}
// Delete any existing dat file.
File.Delete(Directory.GetCurrentDirectory() + "\\my-genetic-algorithm.dat");
// Start a new genetic algorithm.
ga.GAParams.Elitism = true;
ga.GAParams.HistoryPath = Directory.GetCurrentDirectory() + "\\history.txt";
ga.FitnessFunction = new GAFunction(fitnessFunc);
ga.OnGenerationFunction = new OnGeneration(generationFunc);
ga.Go();
}
else
{
// Load a saved genetic algorithm.
ga.Load("my-genetic-algorithm.dat");
ga.Resume(fitnessFunc, generationFunc);
}
// Results.
double[] weights;
double fitness;
ga.GetBest(out weights, out fitness);
Console.WriteLine("***** DONE! *****");
return CommonManager.ConvertDoubleArrayToBF(weights);
}
public void Resume(GAFunction fitnessFunc, OnGeneration onGenerationFunc)
{
FitnessFunction = fitnessFunc;
OnGenerationFunction = onGenerationFunc;
Go(true);
}
