/// <summary>
/// Performs the selection of chromosomes from the generation specified.
/// </summary>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
/// <returns>
/// The selected chromosomes.
/// </returns>
protected override IList<IChromosome> PerformSelectChromosomes(int number, Generation generation)
{
var chromosomes = generation.Chromosomes;
var selected = new List<IChromosome>();
var sumFitness = chromosomes.Sum(c => c.Fitness.Value);
var rouleteWheel = new List<double>();
var accumulativePercent = 0.0;
double stepSize = 1.0 / number;
foreach (var c in chromosomes)
{
accumulativePercent += c.Fitness.Value / sumFitness;
rouleteWheel.Add(accumulativePercent);
}
var pointer = RandomizationProvider.Current.GetDouble();
for (int i = 0; i < number; i++)
{
if (pointer > 1.0)
{
pointer -= 1.0;
}
var chromosomeIndex = rouleteWheel.Select((value, index) => new { Value = value, Index = index }).FirstOrDefault(r => r.Value >= pointer).Index;
selected.Add(chromosomes[chromosomeIndex]);
pointer += stepSize;
}
return selected;
}
/// <summary>
/// Performs the selection of chromosomes from the generation specified.
/// </summary>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
/// <returns>
/// The selected chromosomes.
/// </returns>
protected override IList<IChromosome> PerformSelectChromosomes(int number, Generation generation)
{
var chromosomes = generation.Chromosomes;
var rouleteWheel = new List<double>();
double stepSize = 1.0 / number;
CalculateCumulativePercentFitness(chromosomes, rouleteWheel);
var pointer = RandomizationProvider.Current.GetDouble();
return SelectFromWheel(
number,
chromosomes,
rouleteWheel,
() =>
{
if (pointer > 1.0)
{
pointer -= 1.0;
}
var currentPointer = pointer;
pointer += stepSize;
return currentPointer;
});
}
public void SelectChromosomes_Generation_ChromosomesSelected()
{
var target = new EliteSelection();
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
});
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual (0.7, actual [0].Fitness);
Assert.AreEqual (0.5, actual [1].Fitness);
actual = target.SelectChromosomes(3, generation);
Assert.AreEqual(3, actual.Count);
Assert.AreEqual (0.7, actual [0].Fitness);
Assert.AreEqual (0.5, actual [1].Fitness);
Assert.AreEqual (0.1, actual [2].Fitness);
}
/// <summary>
/// Performs the selection of chromosomes from the generation specified.
/// </summary>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
/// <returns>
/// The selected chromosomes.
/// </returns>
protected override IList<IChromosome> PerformSelectChromosomes(int number, Generation generation)
{
if (Size > generation.Chromosomes.Count)
{
throw new SelectionException(
this,
"The tournament size is greater than available chromosomes. Tournament size is {0} and generation {1} available chromosomes are {2}.".With(Size, generation.Number, generation.Chromosomes.Count));
}
var candidates = generation.Chromosomes.ToList();
var selected = new List<IChromosome>();
while (selected.Count < number)
{
var randomIndexes = RandomizationProvider.Current.GetUniqueInts(Size, 0, candidates.Count);
var tournamentWinner = candidates.Where((c, i) => randomIndexes.Contains(i)).OrderByDescending(c => c.Fitness).First();
selected.Add(tournamentWinner);
if (!AllowWinnerCompeteNextTournament)
{
candidates.Remove(tournamentWinner);
}
}
return selected;
}
public void SelectChromosomes_Generation_ChromosomesSelected()
{
var target = new StochasticUniversalSamplingSelection();
var c1 = new ChromosomeStub();
c1.Fitness = 0.1;
var c2 = new ChromosomeStub();
c2.Fitness = 0.5;
var c3 = new ChromosomeStub();
c3.Fitness = 0;
var c4 = new ChromosomeStub();
c4.Fitness = 0.7;
var generation = new Generation(1, new List<IChromosome>() {
c1, c2, c3, c4
});
// Fitness sum: 0.1 + 0.5 + 0 + 0.7 = 1.3
// c1: 8% = 0.08
// c2: 38% = 0.46
// c3: 0% = 0.46
// c4: 54% = 1.00
var rnd = MockRepository.GenerateMock<IRandomization>();
rnd.Expect(r => r.GetDouble()).Return(0.3);
RandomizationProvider.Current = rnd;
// Step size 1/2 = 0.5
var actual = target.SelectChromosomes(2, generation);
Assert.AreEqual(2, actual.Count);
Assert.AreEqual(c2.Fitness, actual[0].Fitness); // 0.3
Assert.AreEqual(c4.Fitness, actual[1].Fitness); // 0.8
// Step size 1/3 = 0.33
actual = target.SelectChromosomes(3, generation);
Assert.AreEqual(3, actual.Count);
Assert.AreEqual(c2.Fitness, actual[0].Fitness); // 0.3
Assert.AreEqual(c4.Fitness, actual[1].Fitness); // 0.63
Assert.AreEqual(c4.Fitness, actual[2].Fitness); // 0.96
// Step size 1/4 = 0.25
actual = target.SelectChromosomes(4, generation);
Assert.AreEqual(4, actual.Count);
Assert.AreEqual(c2.Fitness, actual[0].Fitness); // 0.3
Assert.AreEqual(c4.Fitness, actual[1].Fitness); // 0.55
Assert.AreEqual(c4.Fitness, actual[2].Fitness); // 0.80
Assert.AreEqual(c1.Fitness, actual[3].Fitness); // 0.05
// Step size 1/5 = 0.20
actual = target.SelectChromosomes(5, generation);
Assert.AreEqual(5, actual.Count);
Assert.AreEqual(c2.Fitness, actual[0].Fitness); // 0.3
Assert.AreEqual(c4.Fitness, actual[1].Fitness); // 0.5
Assert.AreEqual(c4.Fitness, actual[2].Fitness); // 0.7
Assert.AreEqual(c4.Fitness, actual[3].Fitness); // 0.9
Assert.AreEqual(c2.Fitness, actual[4].Fitness); // 0.1
}
public void Constructor_OkArguments_Instanced()
{
var target = new Generation(1, new List<IChromosome>() {
MockRepository.GenerateMock<IChromosome>(),
MockRepository.GenerateMock<IChromosome>()
});
Assert.AreEqual(1, target.Number);
Assert.AreEqual(2, target.Chromosomes.Count);
}
/// <summary>
/// Selects the number of chromosomes from the generation specified.
/// </summary>
/// <returns>The selected chromosomes.</returns>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
public IList<IChromosome> SelectChromosomes(int number, Generation generation)
{
if (number < m_minNumberChromosomes)
{
throw new ArgumentOutOfRangeException("number", "The number of selected chromosomes should be at least {0}.".With(m_minNumberChromosomes));
}
ExceptionHelper.ThrowIfNull("generation", generation);
return PerformSelectChromosomes(number, generation);
}
public void End_AnyChromosomeWithoutFitness_Exception()
{
var target = new Generation(1, new List<IChromosome>() {
new ChromosomeStub() { Fitness = 0.2 },
new ChromosomeStub() { Fitness = null},
new ChromosomeStub() { Fitness = 0.1 }
});
ExceptionAssert.IsThrowing(new InvalidOperationException("There is unknown problem in current generation, because a chromosome has no fitness value."), () =>
{
target.End(2);
});
}
public void End_ChromosomeNumberGreaterThan_Take()
{
var target = new Generation(1, new List<IChromosome>() {
new ChromosomeStub() { Fitness = 0.2 },
new ChromosomeStub() { Fitness = 0.3 },
new ChromosomeStub() { Fitness = 0.1 }
});
target.End(2);
Assert.AreEqual(2, target.Chromosomes.Count);
Assert.AreEqual(0.3, target.Chromosomes[0].Fitness);
Assert.AreEqual(0.2, target.Chromosomes[1].Fitness);
}
public void SelectChromosomes_TournamentSize3AllowWinnerCompeteNextTournamentFalse_ChromosomesSelected()
{
var target = new TournamentSelection(3, false);
var c0 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c0.Fitness = 0.1;
var c1 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c1.Fitness = 0.5;
var c2 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c2.Fitness = 0;
var c3 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c3.Fitness = 0.7;
var c4 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c4.Fitness = 0.3;
var c5 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c5.Fitness = 0.2;
var generation = new Generation(1, new List<IChromosome>() {
c0, c1, c2, c3, c4, c5
});
var mock = new MockRepository();
var rnd = mock.StrictMock<IRandomization>();
using (mock.Ordered())
{
rnd.Expect(r => r.GetUniqueInts(3, 0, 6)).Return(new int[] { 0, 1, 2 });
rnd.Expect(r => r.GetUniqueInts(3, 0, 5)).Return(new int[] { 2, 3, 4 });
rnd.Expect(r => r.GetUniqueInts(3, 0, 4)).Return(new int[] { 0, 1, 2 });
rnd.Expect(r => r.GetUniqueInts(3, 0, 3)).Return(new int[] { 0, 1, 2 });
}
RandomizationProvider.Current = rnd;
mock.ReplayAll();
var actual = target.SelectChromosomes(4, generation);
Assert.AreEqual(4, actual.Count);
Assert.AreEqual(c1, actual[0]);
Assert.AreEqual(c3, actual[1]);
Assert.AreEqual(c4, actual[2]);
Assert.AreEqual(c5, actual[3]);
}
public void SelectChromosomes_TournamentSizeGreaterThanAvailableChromosomes_Exception()
{
var target = new TournamentSelection(3, true);
var c0 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c0.Fitness = 0.1;
var c1 = MockRepository.GeneratePartialMock<ChromosomeBase>(2);
c1.Fitness = 0.5;
var generation = new Generation(1, new List<IChromosome>() {
c0, c1
});
ExceptionAssert.IsThrowing(new SelectionException(target,
"The tournament size is greater than available chromosomes. Tournament size is 3 and generation 1 available chromosomes are 2."), () =>
{
target.SelectChromosomes(2, generation);
});
}
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));
});
}
/// <summary>
/// Creates a new generation.
/// </summary>
/// <param name="chromosomes">The chromosomes for new generation.</param>
public void CreateNewGeneration(IList<IChromosome> chromosomes)
{
ExceptionHelper.ThrowIfNull("chromosomes", chromosomes);
chromosomes.ValidateGenes();
CurrentGeneration = new Generation(++GenerationsNumber, chromosomes);
Generations.Add(CurrentGeneration);
GenerationStrategy.RegisterNewGeneration(this);
}
/// <summary>
/// Performs the selection of chromosomes from the generation specified.
/// </summary>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
/// <returns>The select chromosomes.</returns>
protected override IList<IChromosome> PerformSelectChromosomes(int number, Generation generation)
{
var ordered = generation.Chromosomes.OrderByDescending (c => c.Fitness);
return ordered.Take (number).ToList ();
}
/// <summary>
/// Performs the selection of chromosomes from the generation specified.
/// </summary>
/// <param name="number">The number of chromosomes to select.</param>
/// <param name="generation">The generation where the selection will be made.</param>
/// <returns>The select chromosomes.</returns>
protected override IList<IChromosome> PerformSelectChromosomes(int number, Generation generation)
{
var chromosomes = generation.Chromosomes;
var rouletteWheel = new List<double>();
var rnd = RandomizationProvider.Current;
CalculateCumulativePercentFitness(chromosomes, rouletteWheel);
return SelectFromWheel(number, chromosomes, rouletteWheel, () => rnd.GetDouble());
}
/// <summary> /// Performs the selection of chromosomes from the generation specified. /// </summary> /// <returns>The selected chromosomes.</returns> /// <param name="number">The number of chromosomes to select.</param> /// <param name="generation">The generation where the selection will be made.</param> protected abstract IList<IChromosome> PerformSelectChromosomes(int number, Generation generation);
