public void Evolve_ManyGenerations_Fast()
{
var selection = new EliteSelection();
var crossover = new ThreeParentCrossover();
var mutation = new UniformMutation(true);
var fitness = new FunctionBuilderFitness(
new FunctionBuilderInput(
new double[] { 1, 2, 3 },
6)
,
new FunctionBuilderInput(
new double[] { 2, 3, 4 },
24)
);
var chromosome = new FunctionBuilderChromosome(fitness.AvailableOperations, 5);
var population = new Population(100, 200, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new FitnessThresholdTermination(0);
ga.Start();
var bestChromosome = ga.BestChromosome as FunctionBuilderChromosome;
Assert.AreEqual(0.0, bestChromosome.Fitness.Value);
var actual = fitness.GetFunctionResult(
bestChromosome.BuildFunction(),
new FunctionBuilderInput(new double[] { 3, 4, 5 }, 60)
);
Assert.AreEqual(60.0, actual);
}
/// <summary>
/// Initializes a new instance of the <see cref="GeneticSharp.Extensions.Mathematic.FunctionBuilderFitness"/> class.
/// </summary>
/// <param name="inputs">The arguments values and expected results of the function.</param>
public FunctionBuilderFitness(params FunctionBuilderInput[] inputs)
{
m_inputs = inputs;
var parametersCount = m_inputs[0].Arguments.Count;
AvailableOperations = FunctionBuilderChromosome.BuildAvailableOperations(parametersCount);
m_parameterNames = FunctionBuilderChromosome.GetParameterNames(parametersCount);
}
public void Evaluate_AllResultsEquals_MaxFitness()
{
var target = new FunctionBuilderFitness(
new FunctionBuilderInput(new double[] { 1 }, 1),
new FunctionBuilderInput(new double[] { 2 }, 2));
var c = new FunctionBuilderChromosome(target.AvailableOperations, 2);
c.ReplaceGene(0, new Gene("A"));
c.ReplaceGene(1, new Gene(""));
var actual = target.Evaluate(c);
Assert.AreEqual(0, actual);
}
public void Evaluate_InvalidFunction_WorstFitness()
{
var target = new FunctionBuilderFitness(
new FunctionBuilderInput(new double[] { 1 }, 2),
new FunctionBuilderInput(new double[] { 1 }, 3));
var c = new FunctionBuilderChromosome(target.AvailableOperations, 2);
c.ReplaceGene(0, new Gene("-"));
c.ReplaceGene(1, new Gene(""));
var actual = target.Evaluate(c);
Assert.AreEqual(double.MinValue, actual);
}
