public void SelectChromosomes_NullGeneration_Exception()
{
var target = new RouletteWheelSelection();
ExceptionAssert.IsThrowing(new ArgumentNullException("generation"), () =>
{
target.SelectChromosomes(2, null);
});
}
public void SelectChromosomes_InvalidNumber_Exception()
{
var target = new RouletteWheelSelection();
ExceptionAssert.IsThrowing(new ArgumentOutOfRangeException("number", "The number of selected chromosomes should be at least 2."), () =>
{
target.SelectChromosomes(-1, null);
});
ExceptionAssert.IsThrowing(new ArgumentOutOfRangeException("number", "The number of selected chromosomes should be at least 2."), () =>
{
target.SelectChromosomes(0, null);
});
ExceptionAssert.IsThrowing(new ArgumentOutOfRangeException("number", "The number of selected chromosomes should be at least 2."), () =>
{
target.SelectChromosomes(1, null);
});
}
public void SelectChromosomes_Generation_ChromosomesSelected()
{
var target = new RouletteWheelSelection();
var c1 = MockRepository.GeneratePartialMock<ChromosomeBase> (2);
c1.Fitness = 0.1;
var c2 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c2.Fitness = 0.5;
var c3 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c3.Fitness = 0;
var c4 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c4.Fitness = 0.7;
var generation = new Generation (1, new List<IChromosome> () {
c1, c2, c3, c4
});
// Just one selected chromosome is c1.
FlowAssert.IsAtLeastOneAttemptOk (100, () => {
var actual = target.SelectChromosomes (2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(1, actual.Count(c => c.Fitness == 0.1));
});
// All selected chromosome is c1.
FlowAssert.IsAtLeastOneAttemptOk (1000, () => {
var actual = target.SelectChromosomes (2, generation);
Assert.AreEqual(2, actual.Count);
Assert.IsTrue(actual.All(c => c.Fitness == 0.1));
});
// Just one selected chromosome is c2.
FlowAssert.IsAtLeastOneAttemptOk(100, () =>
{
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(1, actual.Count(c => c.Fitness == 0.5));
});
// All selected chromosome is c2.
FlowAssert.IsAtLeastOneAttemptOk(1000, () =>
{
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.IsTrue(actual.All(c => c.Fitness == 0.5));
});
// None selected chromosome is c3.
FlowAssert.IsAtLeastOneAttemptOk(100, () =>
{
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(0, actual.Count(c => c.Fitness == 0.0));
});
// Just one selected chromosome is c4.
FlowAssert.IsAtLeastOneAttemptOk(100, () =>
{
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(1, actual.Count(c => c.Fitness == 0.7));
});
// All selected chromosome is c4.
FlowAssert.IsAtLeastOneAttemptOk(1000, () =>
{
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.IsTrue(actual.All(c => c.Fitness == 0.7));
});
}
public void Start_ParallelManySlowFitness_Timeout()
{
var taskExecutor = new SmartThreadPoolTaskExecutor();
taskExecutor.MinThreads = 100;
taskExecutor.MaxThreads = 100;
taskExecutor.Timeout = TimeSpan.FromMilliseconds(1000);
var selection = new RouletteWheelSelection();
var crossover = new OnePointCrossover(1);
var mutation = new UniformMutation();
var chromosome = new ChromosomeStub();
var target = new GeneticAlgorithm(new Population(100, 150, chromosome),
new FitnessStub() { SupportsParallel = true, ParallelSleep = 1500 }, selection, crossover, mutation);
target.TaskExecutor = taskExecutor;
ExceptionAssert.IsThrowing(new TimeoutException("The fitness evaluation rech the 00:00:01 timeout."), () =>
{
target.Start();
});
Assert.IsFalse(target.IsRunning);
Assert.AreEqual(GeneticAlgorithmState.Stopped, target.State);
}
public void Start_InvalidFitnessEvaluateResult_Exception()
{
var selection = new RouletteWheelSelection();
var crossover = new OnePointCrossover(1);
var mutation = new UniformMutation();
var chromosome = new ChromosomeStub();
var fitness = MockRepository.GenerateMock<IFitness>();
fitness.Expect(f => f.Evaluate(null)).IgnoreArguments().Return(1.1);
var target = new GeneticAlgorithm(
new Population(20, 20, chromosome),
fitness, selection, crossover, mutation);
ExceptionAssert.IsThrowing(new FitnessException(fitness, "The {0}.Evaluate returns a fitness with value 1.1. The fitness value should be between 0.0 and 1.0.".With(fitness.GetType())), () =>
{
target.Start();
});
fitness = MockRepository.GenerateMock<IFitness>();
fitness.Expect(f => f.Evaluate(null)).IgnoreArguments().Return(-0.1);
target = new GeneticAlgorithm(
new Population(20, 20, chromosome),
fitness, selection, crossover, mutation);
ExceptionAssert.IsThrowing(new FitnessException(fitness, "The {0}.Evaluate returns a fitness with value -0.1. The fitness value should be between 0.0 and 1.0.".With(fitness.GetType())), () =>
{
target.Start();
});
}