public void RequestBadNumberOfChildren_ThrowsException(int childrenCount)
{
var childrenGenerator = new ChildrenGenerator(A.Fake <ICrossoverManager>(), new BasicMutationProbabilityManager(0),
new RouletteWheelSelection());
childrenGenerator.GenerateChildren(GetPopulation(1), childrenCount, 0, null);
}
public void SelectionStrategyReturnsNull_ThrowsException()
{
Assertions.AssertThrowAggretateExceptionOfType(() =>
{
var selectionStrategy = A.Fake <ISelectionStrategy>();
A.CallTo(() => selectionStrategy.SelectChromosome()).Returns(null);
var childrenGenerator = new ChildrenGenerator(A.Fake <ICrossoverManager>(), new BasicMutationProbabilityManager(0),
selectionStrategy);
childrenGenerator.GenerateChildren(GetPopulation(1), 1, 0, null);
}, typeof(GeneticAlgorithmException));
}
public void BadMutationProbability_ThrowException(double probability)
{
var mutationManager = A.Fake <IMutationProbabilityManager>();
A.CallTo(() => mutationManager.MutationProbability(A <Population> ._, A <IEnvironment> ._, A <int> ._))
.Returns(probability);
var childrenGenerator = new ChildrenGenerator(A.Fake <ICrossoverManager>(), mutationManager, new RouletteWheelSelection());
childrenGenerator.GenerateChildren(GetPopulation(1), 1, 1, null);
}
public void RetusnRightNumberOfChromosomes(int childrenCount)
{
const int count = 1500;
var crossoverManager = A.Fake <ICrossoverManager>();
var childrenGenerator = new ChildrenGenerator(crossoverManager, new BasicMutationProbabilityManager(0), new RouletteWheelSelection());
var children = childrenGenerator.GenerateChildren(GetPopulation(count), childrenCount, 0, null);
Assert.AreEqual(childrenCount, children.Length, "Didn't get enough children");
foreach (var chromosome in children)
{
Assert.IsNotNull(chromosome, "No children should be null");
}
}
public void TestMutationsHappen(double mutationProbability)
{
const int populationSize = 1500;
int mutationCounter = 0;
var population = GetPopulation(populationSize, () => Interlocked.Increment(ref mutationCounter));
var crossoverManager = A.Fake <ICrossoverManager>();
A.CallTo(() => crossoverManager.Crossover(A <IChromosome> ._, A <IChromosome> ._))
.ReturnsLazily((IChromosome c1, IChromosome c2) => c1);
var childrenGenerator = new ChildrenGenerator(crossoverManager, new BasicMutationProbabilityManager(mutationProbability), new RouletteWheelSelection());
childrenGenerator.GenerateChildren(population, populationSize, 0, null);
const double errorMargin = 0.05;
Assert.IsTrue(mutationCounter < populationSize * mutationProbability + errorMargin * populationSize, $"Too few mutations ({mutationCounter})");
Assert.IsTrue(mutationCounter > populationSize * mutationProbability - errorMargin * populationSize, $"Too many mutations ({mutationCounter})");
}