public SmallGenetics(Main form1, Func <string, int, string, bool> populateM, SmallEquation ptarget)
{
pop = populateM;
form = form1;
target = ptarget;
var population = new Population(populationSize, 320, false, false);
//create the genetic operators
var elite = new Elite(elitismPercentage);
var crossover = new Crossover(crossoverProbability, true)
{
CrossoverType = CrossoverType.SinglePoint
};
var mutation = new BinaryMutate(mutationProbability, true);
//create the GA itself
ga = new GeneticAlgorithm(population, EvaluateFitness);
ga.OnGenerationComplete += ga_OnGenerationComplete;
ga.Operators.Add(elite);
ga.Operators.Add(crossover);
ga.Operators.Add(mutation);
}
public bool populateMethod(SmallEquation equation, int size, string graphseries)
{
chart1.Series.FindByName(graphseries).Points.Clear();
for (int i = -size; i <= size; i++)
{
chart1.Series.FindByName(graphseries).Points.AddXY(i, Utils.calculateY(equation, i));
}
Thread.Sleep(10);
return(true);
}
public static Dictionary <int, double> convertToDictionary(SmallEquation equation, int size)
{
Dictionary <int, double> output = new Dictionary <int, double>();
for (int i = -size; i <= size; i++)
{
output.Add(i, calculateY(equation, i));
}
return(output);
}
private void ga_OnGenerationComplete(object sender, GaEventArgs e)
{
Console.WriteLine("---Generation Complete---");
Console.WriteLine("Gen: " + e.Generation);
Console.WriteLine("Fit: " + e.Population.MaximumFitness + " " + (e.Population.MaximumFitness - lastGenFitness));
lastGenFitness = e.Population.MaximumFitness;
//get the best solution
var chromosome = e.Population.GetTop(1)[0];
int numOfBytes = chromosome.ToBinaryString().Length / 8;
byte[] bytes = new byte[numOfBytes];
for (int i = 0; i < numOfBytes; i++)
{
bytes[i] = Convert.ToByte(chromosome.ToBinaryString().Substring(8 * i, 8), 2);
}
SmallEquation eq = Decoder.decodeToSmallEquation(bytes);
eq.fitness = e.Population.MaximumFitness;
Console.WriteLine("Eq : " + eq.ToString());
form.backgroundWorker1.ReportProgress(Convert.ToInt32(e.Population.MaximumFitness * 100), JsonConvert.SerializeObject(eq));
}
public static double calculateY(SmallEquation eq, double x)
{
return(eq.d0 * Math.Pow((x), 4) + eq.d1 * Math.Pow((x), 3) + eq.d2 * Math.Pow((x), 2) + eq.d3 * Math.Pow((x), 1) + eq.d4);
}
