public override void Execute(ref IOrganism organism)
{
var chromosome = (IGEPChromosome)organism[0];
var main = chromosome.Main;
var activeAlleleDNA = main.GetActiveAllele().DNA;
activeAlleleDNA.DecrementNucleotide(activeAlleleDNA.RandomIndex());
}
public Tuple<IOrganism, IOrganism> CrossLink(IOrganism parent1, IOrganism parent2)
{
if (parent1.Chromosomes.Count != parent2.Chromosomes.Count) {
throw new InvalidOperationException("Parents must have the same number of chromosomes");
}
IOrganism child1 = parent1.Clone();
IOrganism child2 = parent2.Clone();
for (int chromosomeIndex = 0; chromosomeIndex <= parent1.Chromosomes.Count - 1; chromosomeIndex++) {
if (rand.NextDouble() > this.CrossLinkProbability) {
continue;
}
var child1Genes = child1.Chromosomes[chromosomeIndex].GetGenes();
var child2Genes = child2.Chromosomes[chromosomeIndex].GetGenes();
int matchIndex = rand.Next(Math.Min(child1Genes.Count(), child2Genes.Count()));
Chromosome match1 = child1Genes.ElementAt(matchIndex);
Chromosome match2 = child2Genes.ElementAt(matchIndex);
this.SwapGenes(child1.Chromosomes[chromosomeIndex], match1, match2);
this.SwapGenes(child2.Chromosomes[chromosomeIndex], match1, match2);
}
return new Tuple<IOrganism, IOrganism>(child1, child2);
}
public void Start()
{
int iteration = 0;
while (iteration < Iterations)
{
Console.WriteLine($"Generation {iteration}");
iteration++;
var scoredOrganisms = Population.Organisms.Select(o => new
{
Score = o.Score(),
Organism = o
})
.ToArray();
//Sort the organisms by score
var sortedOrganisms = scoredOrganisms
.OrderBy(o => o.Score)
.Select(o => o.Organism)
.ToArray();
//Keep track of the absolute best organism.
var currentBestOrganism = sortedOrganisms.First();
if (AbsoluteBestOrganism == null || currentBestOrganism.Score() < AbsoluteBestOrganism.Score())
{
AbsoluteBestOrganism = currentBestOrganism;
}
//Keep the best organisms
var matePopulation = new HashSet <IOrganism>(sortedOrganisms[0..MatePopulationCutoff]);
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes) {
int index = rand.Next(chromosome.Length);
chromosome[index] = !chromosome[index];
}
}
public Tuple <IOrganism, IOrganism> CrossLink(IOrganism parent1, IOrganism parent2)
{
if (parent1.Chromosomes.Count != parent2.Chromosomes.Count)
{
throw new InvalidOperationException("Parents must have the same number of chromosomes");
}
IOrganism child1 = parent1.Clone();
IOrganism child2 = parent2.Clone();
for (int i = 0; i <= parent1.Chromosomes.Count - 1; i++)
{
if (rand.NextDouble() > this.CrossLinkProbability)
{
continue;
}
int crossLinkIndex1 = rand.Next(Math.Min(parent1.Chromosomes[i].Length, parent2.Chromosomes[i].Length) - 1);
int crossLinkIndex2 = rand.Next(crossLinkIndex1 + 1, Math.Min(parent1.Chromosomes[i].Length, parent2.Chromosomes[i].Length));
child1.Chromosomes[i].OverWrite(crossLinkIndex1, parent2.Chromosomes[i].Bits.Skip(crossLinkIndex1).Take(crossLinkIndex2 - crossLinkIndex1).ToArray());
child2.Chromosomes[i].OverWrite(crossLinkIndex1, parent1.Chromosomes[i].Bits.Take(crossLinkIndex2 - crossLinkIndex1).ToArray());
}
return(new Tuple <IOrganism, IOrganism>(child1, child2));
}
public void Eat(IOrganism organism, List <IOrganism> toDelete)
{
AudioController.PlayEat();
AddHealth(organism.Health);
toDelete.Add(organism);
Move(2);
}
public Tuple <IOrganism, IOrganism> CrossLink(IOrganism parent1, IOrganism parent2)
{
if (parent1.Chromosomes.Count != parent2.Chromosomes.Count)
{
throw new InvalidOperationException("Parents must have the same number of chromosomes");
}
IOrganism child1 = parent1.Clone();
IOrganism child2 = parent2.Clone();
for (int chromosomeIndex = 0; chromosomeIndex <= parent1.Chromosomes.Count - 1; chromosomeIndex++)
{
if (rand.NextDouble() > this.CrossLinkProbability)
{
continue;
}
var child1Genes = child1.Chromosomes[chromosomeIndex].GetGenes();
var child2Genes = child2.Chromosomes[chromosomeIndex].GetGenes();
int matchIndex = rand.Next(Math.Min(child1Genes.Count(), child2Genes.Count()));
Chromosome match1 = child1Genes.ElementAt(matchIndex);
Chromosome match2 = child2Genes.ElementAt(matchIndex);
this.SwapGenes(child1.Chromosomes[chromosomeIndex], match1, match2);
this.SwapGenes(child2.Chromosomes[chromosomeIndex], match1, match2);
}
return(new Tuple <IOrganism, IOrganism>(child1, child2));
}
private double CalculateFitness(IOrganism o)
{
List <City> cities = this.cityInfo.Select(c => c.Name).ToList();
var numbers = o.Chromosomes[0].GetGenes().Select((g, i) => Convert.ToInt32(g.ToString(), 2)).ToList();
double totalDistance = 0;
City lastCity = City.Unknown;
numbers.ForEach(i =>
{
City currentCity = cities[i];
cities.RemoveAt(i);
if (lastCity == City.Unknown)
{
lastCity = currentCity;
}
else
{
totalDistance += this.GetDistance(lastCity, currentCity);
lastCity = currentCity;
}
});
return(1 / totalDistance);
}
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes)
{
if (chromosome.Length % this.geneLength != 0)
{
//Throw New InvalidOperationException("The element must be a multiple of gene length")
}
int gene1Index = rand.Next(Convert.ToInt32(Math.Floor((double)chromosome.Length / this.geneLength)) - 1);
int gene2Index = gene1Index + 1;
bool[] temp = new bool[this.geneLength + 1];
for (int i = 0; i <= this.geneLength - 1; i++)
{
temp[i] = chromosome[gene1Index * this.geneLength + i];
}
for (int i = 0; i <= this.geneLength - 1; i++)
{
chromosome[gene1Index * this.geneLength + i] = chromosome[gene2Index * this.geneLength + i];
chromosome[gene2Index * this.geneLength + i] = temp[i];
}
}
}
public void Move(IOrganism obj, Point oldPoint, Point newPoint)
{
var o = Matrix[oldPoint.X, oldPoint.Y];
Matrix[oldPoint.X, oldPoint.Y] = null;
Matrix[newPoint.X, newPoint.Y] = o;
}
private static void GetPopulationUsingVar(IOrganism organism)
{
double population = 0;
// Switch on passed organism using var pattern matching.
switch (organism)
{
// Assign organism to new bee variable, if population is roughly equal to 30 trillion.
case var bee when Math.Abs(bee.Population - 30e12) <= 1:
population = bee.Population;
break;
// Assign organism to new human variable, if object type Name is "Human."
case var human when human.GetType().Name == "Human":
population = human.Population;
break;
default:
// Output alert if organism type is unknown.
Logging.Log($"Unknown organism type ({organism.GetType().Name}), or population exceeds all known estimates.");
return;
}
// Output retrieved population estimate.
Logging.Log($"Estimated number of {organism.GetType().Name.ToLower()}s on Earth: {population:n0}.");
}
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes)
{
int index = rand.Next(chromosome.Length);
chromosome[index] = !chromosome[index];
}
}
public void Clone(IOrganism parent)
{
var parentCast = (IncrementingBoard)parent;
for (int i = 0; i < GeneInfo.Length; i++)
{
GeneInfo[i] = parentCast.GeneInfo[i];
}
}
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes) {
int index = rand.Next(chromosome.Length - 1);
bool temp = chromosome[index];
chromosome[index] = chromosome[index + 1];
chromosome[index + 1] = temp;
}
}
/// <summary>
/// Removes the current occupant from the <see cref="VehicleSeat"/>.
/// </summary>
public void Clear()
{
if (!IsOccupied)
{
return;
}
Occupant = null;
}
/// <summary>
/// Gets the IMetrics of the IOrganism.
///
/// Calls OnEvaluationStart on start and calls OnEvaluationEnd on end.
/// </summary>
/// <returns></returns>
public override IMetrics GetMetrics(IOrganism organism)
{
this.OnEvaluationStart(new StartMetricsEvaluationEventArgs());
var metrics = this.GetMetricsDelegate(organism: organism);
this.OnEvaluationEnd(new EndMetricsEvaluationEventArgs());
return metrics;
}
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes)
{
int index = rand.Next(chromosome.Length - 1);
bool temp = chromosome[index];
chromosome[index] = chromosome[index + 1];
chromosome[index + 1] = temp;
}
}
public void Mutate(IOrganism organism)
{
for (int i = 0; i <= organism.Chromosomes.Count - 1; i++) {
int index = rand.Next(organism.Chromosomes[i].Length);
Chromosome mutated = new Chromosome(organism.Chromosomes[i].GeneLength, organism.Chromosomes[i].Length - 1);
Array.Copy(organism.Chromosomes[i].Bits, 0, mutated.Bits, 0, index);
Array.Copy(organism.Chromosomes[i].Bits, index + 1, mutated.Bits, index, organism.Chromosomes[i].Length - index - 1);
organism.Chromosomes[i] = mutated;
}
}
public void Clone(IOrganism parent)
{
var p = (Warehouse)parent;
//Copy the shelves
for (int i = 0; i < Shelves.Length; i++)
{
SetShelf(i, p.Shelves[i]);
}
}
public void Mutate(IOrganism organism)
{
for (int i = 0; i <= organism.Chromosomes.Count - 1; i++)
{
int index = rand.Next(organism.Chromosomes[i].Length);
Chromosome mutated = new Chromosome(organism.Chromosomes[i].GeneLength, organism.Chromosomes[i].Length - 1);
Array.Copy(organism.Chromosomes[i].Bits, 0, mutated.Bits, 0, index);
Array.Copy(organism.Chromosomes[i].Bits, index + 1, mutated.Bits, index, organism.Chromosomes[i].Length - index - 1);
organism.Chromosomes[i] = mutated;
}
}
public void Mutate(IOrganism organism)
{
if (this.Mutators.Count == 0) {
throw new ArgumentException("Mutators");
}
if (rand.NextDouble() < this.MutationProbability) {
int index = rand.Next(this.Mutators.Count);
this.Mutators[index].Mutate(organism);
}
}
public override void Execute(ref IOrganism organism)
{
var chromosome = (IGEPChromosome)organism[0];
var main = chromosome.Main;
var dna = main.GetActiveAllele().DNA;
var nucleotidesToMutateCount = Randomizer.Next(this.MinimumNucleotidesToMutate,
this.MaximumNucleotidesToMutate + 1);
for (var i = 0; i < nucleotidesToMutateCount; i++)
dna.RandomlyFlipNucleotide();
}
/// <summary>
/// Kills the <see cref="Organism"/>, specifying the killer.
/// </summary>
/// <param name="killer">The killer.</param>
public void Kill(IOrganism killer)
{
if (IsDead)
{
return;
}
IsAlive = false;
SetHealth(0);
OnKilled();
}
private IOrganism CorrectEncoding(IOrganism o)
{
var genes = o.Chromosomes[0].GetGenes();
var geneCount = genes.Count();
for (int geneId = 0; geneId < geneCount; geneId++)
{
o.Chromosomes[0].Gene(geneId, new Chromosome(geneLength, Convert.ToString(Convert.ToInt32(o.Chromosomes[0].Gene(geneId).ToString(), 2) % (genes.Count() - geneId), 2).PadLeft(geneLength, '0')));
}
return(o);
}
/// <summary>
/// Revives the <see cref="Organism"/>, specifying the reviver.
/// </summary>
/// <param name="reviver">The reviver.</param>
public void Revive(IOrganism reviver)
{
if (!IsDead)
{
return;
}
IsAlive = true;
SetHealth(Template.MaxHealth);
OnRevived();
}
private void addIOrganism(IOrganism organism)
{
organism.Position = Position.GenerateRandomEmptyPosition(this.Terrarium);
organism.LastPosition = new Position(organism.Position.X, organism.Position.Y);
organism.Terrarium = this.Terrarium;
if (organism is Plant)
{
Plant plant = (Plant)organism;
Terrarium.RenderPlant(plant);
}
this.Terrarium.Organisms.Add(organism);
}
public void Add(IOrganism obj, Point point)
{
var o = Matrix[point.X, point.Y];
if (o == null)
{
Organisms.Add(obj);
LiveOrganisms.Add(obj);
Matrix[point.X, point.Y] = obj;
}
}
protected override void ConstructFromOrganism(IOrganism organism)
{
this.Clear();
var chromosomeIndex = 0;
foreach (IGEPChromosome chromosome in organism)
{
var geneLevel = 0;
this.FillGenomeUnits(currentGene: chromosome.Main, chromosomeIndex: chromosomeIndex, geneLevel: ref geneLevel);
chromosomeIndex++;
}
}
public void Mutate(IOrganism organism)
{
if (this.Mutators.Count == 0)
{
throw new ArgumentException("Mutators");
}
if (rand.NextDouble() < this.MutationProbability)
{
int index = rand.Next(this.Mutators.Count);
this.Mutators[index].Mutate(organism);
}
}
public void Mutate(IOrganism organism)
{
for (int i = 0; i <= organism.Chromosomes.Count - 1; i++) {
int index = rand.Next(organism.Chromosomes[i].Length);
bool newElement = rand.NextDouble() > 0.5;
bool[] mutated = new bool[organism.Chromosomes[i].Length + 1];
Array.Copy(organism.Chromosomes[i].Bits, 0, mutated, 0, index);
mutated[index] = newElement;
Array.Copy(organism.Chromosomes[i].Bits, index, mutated, index + 1, organism.Chromosomes[i].Length - index);
organism.Chromosomes[i] = new Chromosome(organism.Chromosomes[i].GeneLength, mutated);
}
}
/// <summary>
/// Occupies the <see cref="VehicleSeat"/> with the specified creature.
/// </summary>
/// <param name="newOccupant">The creature to occupy the seat with.</param>
/// <param name="force">Whether to boot the current occupant out.</param>
public void Occupy(IOrganism newOccupant, bool force = true)
{
if (IsOccupied)
{
if (force)
{
Occupant = newOccupant;
}
return;
}
Occupant = newOccupant;
}
public void Mutate(IOrganism organism)
{
for (int i = 0; i <= organism.Chromosomes.Count - 1; i++)
{
int index = rand.Next(organism.Chromosomes[i].Length);
bool newElement = rand.NextDouble() > 0.5;
bool[] mutated = new bool[organism.Chromosomes[i].Length + 1];
Array.Copy(organism.Chromosomes[i].Bits, 0, mutated, 0, index);
mutated[index] = newElement;
Array.Copy(organism.Chromosomes[i].Bits, index, mutated, index + 1, organism.Chromosomes[i].Length - index);
organism.Chromosomes[i] = new Chromosome(organism.Chromosomes[i].GeneLength, mutated);
}
}
public override void ConstructFromOrganism(IOrganism organism, ISurroundings surroundings)
{
base.ConstructFromOrganism(organism: organism, surroundings: surroundings);
var o = (IGEPOrganism) organism;
var gepSurroundings = (IGEPSurroundings) surroundings;
foreach(IGEPChromosome chromosome in o.GetChromosomes())
{
var debuggableChromosome =
chromosome.ToDebuggableChromosome(new GEPChromosomeSurroundings(gepSurroundings));
this.Chromosomes.Add(debuggableChromosome);
}
}
/// <summary>
/// Heals the <see cref="Organism"/>, specifying the healer.
/// </summary>
/// <param name="healer">The healer.</param>
/// <param name="amount">The healing amount (hp).</param>
public void Heal(IOrganism healer, int amount)
{
if (IsDead)
{
return;
}
if (Health + amount > Template.MaxHealth)
{
SetHealth(Template.MaxHealth);
return;
}
SetHealth(Health + amount);
OnHealed();
}
public void Mate(IOrganism parent1, IOrganism parent2)
{
var parent1Cast = (IncrementingBoard)parent1;
var parent2Cast = (IncrementingBoard)parent2;
var cutoff = Rng.Next(1, parent1Cast.GeneInfo.Length - 1);
for (int i = 0; i < cutoff; i++)
{
GeneInfo[i] = parent1Cast.GeneInfo[i];
}
for (int i = cutoff; i < parent2Cast.GeneInfo.Length; i++)
{
GeneInfo[i] = parent2Cast.GeneInfo[i];
}
}
private string WritePath(IOrganism o)
{
List <City> cities = this.cityInfo.Select(c => c.Name).ToList();
var numbers = o.Chromosomes[0].GetGenes().Select((g, i) => Convert.ToInt32(g.ToString(), 2) % (cities.Count - i)).ToList();
City[] output = new City[cities.Count + 1];
int counter = 0;
numbers.ForEach(i =>
{
output[counter] = cities[i];
cities.RemoveAt(i);
counter += 1;
});
return(string.Join(",", output));
}
public void Fight(IOrganism organism, List <IOrganism> toDelete)
{
// Cast to animal to use add health
Animal animal = (Animal)organism;
//Console.WriteLine("Carnivore fought with Carnivore");
if (organism.Health > Health)
{
toDelete.Add(this);
animal.AddHealth(Health);
}
else if (organism.Health <= Health)
{
toDelete.Add(organism);
AddHealth(animal.Health);
Move(2);
}
AudioController.PlayFight();
}
public void TravellingSalesmanTest()
{
int populationSize = 100;
IRandom rand = new Rand();
this.geneLength = 6;
this.cityInfo = this.BuildCityInfo();
Population candidates = RandomPopulationGenerator.GeneratePopulation(rand, populationSize, 1, geneLength, this.cityInfo.Count, this.cityInfo.Count, new List <Chromosome>(), new List <Chromosome>(), CorrectEncoding);
GeneticAlgorithm ga = new GeneticAlgorithm(rand, candidates, CalculateFitness);
ga.encodingCorrector = CorrectEncoding;
IOrganism solution = ga.FindSolution();
string path = WritePath(solution);
double totalDistance = 1 / CalculateFitness(solution);
Assert.IsTrue(totalDistance <= 25000);
}
public Tuple<IOrganism, IOrganism> CrossLink(IOrganism parent1, IOrganism parent2)
{
if (parent1.Chromosomes.Count != parent2.Chromosomes.Count) {
throw new InvalidOperationException("Parents must have the same number of chromosomes");
}
IOrganism child1 = parent1.Clone();
IOrganism child2 = parent2.Clone();
for (int i = 0; i <= parent1.Chromosomes.Count - 1; i++) {
if (rand.NextDouble() > this.CrossLinkProbability) {
continue;
}
int crossLinkIndex = rand.Next(Math.Min(parent1.Chromosomes[i].Length, parent2.Chromosomes[i].Length));
child1.Chromosomes[i].OverWrite(crossLinkIndex, parent2.Chromosomes[i].Bits.Skip(crossLinkIndex).ToArray());
child2.Chromosomes[i].OverWrite(crossLinkIndex, parent1.Chromosomes[i].Bits.Take(child2.Chromosomes[i].Length - crossLinkIndex).ToArray());
}
return new Tuple<IOrganism, IOrganism>(child1, child2);
}
public virtual void PlaceOrganisms(IOrganism organism, int count, int index)
{
do
{
Point p = new Point();
p.X = Rand.Next(0, Size);
p.Y = Rand.Next(0, Size);
if (Matrix[p.X, p.Y] != null)
{
continue;
}
var obj = organism.Create(this, BaseCore, p, index);
Add(obj, p);
count--;
} while (count > 0);
}
public void Mutate(IOrganism organism)
{
foreach (Chromosome chromosome in organism.Chromosomes) {
if (chromosome.Length % this.geneLength != 0) {
//Throw New InvalidOperationException("The element must be a multiple of gene length")
}
int gene1Index = rand.Next(Convert.ToInt32(Math.Floor((double)chromosome.Length / this.geneLength)) - 1);
int gene2Index = gene1Index + 1;
bool[] temp = new bool[this.geneLength + 1];
for (int i = 0; i <= this.geneLength - 1; i++) {
temp[i] = chromosome[gene1Index * this.geneLength + i];
}
for (int i = 0; i <= this.geneLength - 1; i++) {
chromosome[gene1Index * this.geneLength + i] = chromosome[gene2Index * this.geneLength + i];
chromosome[gene2Index * this.geneLength + i] = temp[i];
}
}
}
private static void GetPopulationUsingType(IOrganism organism)
{
double population = 0;
// Switch on passed organism using type pattern matching.
switch (organism)
{
case Bee bee:
population = bee.Population;
break;
case Human human when(human.Population < 1e7):
// If a Human is passed and the population is too low, panic!
Logging.Log($"The human population is too low at {human.Population:n0}! Apocalypse!");
return;
case Human human:
// If the Human population is alright, proceed as normal.
population = human.Population;
break;
case Insect insect:
population = insect.Population;
break;
case Mammal mammal:
population = mammal.Population;
break;
default:
// Output alert if organism type is unknown.
Logging.Log($"Unknown organism type ({organism.GetType().Name}), or population exceeds all known estimates.");
return;
}
// Output retrieved population estimate.
Logging.Log($"Estimated number of {organism.GetType().Name.ToLower()}s on Earth: {population:n0}.");
}
public void Fight(IOrganism organism, List <IOrganism> toDelete)
{
// Cast to animal to use add health
Animal animal = (Animal)organism;
if (organism is Human)
{
if (organism.Health >= Health)
{
toDelete.Add(this);
animal.AddHealth(Health);
}
else if (organism.Health < Health)
{
toDelete.Add(organism);
AddHealth(animal.Health);
Move(2);
}
}
else // If other carnivore
{
if (organism.Health > Health)
{
toDelete.Add(this);
animal.AddHealth(Health);
}
else if (organism.Health < Health)
{
toDelete.Add(organism);
AddHealth(animal.Health);
Move(2);
}
}
AudioController.PlayFight();
}
/// <summary> /// Gets the percentage that IOrganism one and IOrganism two are similar. /// 100% would be identical and 0% would indicate that the IOrganisms share nothing. /// </summary> /// <param name="one">The first IOrganism to compare.</param> /// <param name="two">The second IOrganism to compare.</param> /// <returns>The percentage that IOrganism one and IOrganism two are similar. /// 100% would be identical and 0% would indicate that the IOrganisms share nothing.</returns> public abstract double GetPercentageIOrganismSimilarity(IOrganism one, IOrganism two);
private IOrganism CorrectEncoding(IOrganism o)
{
var genes = o.Chromosomes[0].GetGenes();
var geneCount = genes.Count();
for (int geneId = 0; geneId < geneCount; geneId++) {
o.Chromosomes[0].Gene(geneId, new Chromosome(geneLength, Convert.ToString(Convert.ToInt32(o.Chromosomes[0].Gene(geneId).ToString(), 2) % (genes.Count() - geneId), 2).PadLeft(geneLength, '0')));
}
return o;
}
private string WritePath(IOrganism o)
{
List<City> cities = this.cityInfo.Select(c => c.Name).ToList();
var numbers = o.Chromosomes[0].GetGenes().Select((g, i) => Convert.ToInt32(g.ToString(), 2) % (cities.Count - i)).ToList();
City[] output = new City[cities.Count + 1];
int counter = 0;
numbers.ForEach(i =>
{
output[counter] = cities[i];
cities.RemoveAt(i);
counter += 1;
});
return string.Join(",", output);
}
/// <summary> /// Executes the Mutation on the given IOrganism. /// </summary> /// <param name="organism">The IOrganism to mutate.</param> public abstract void Execute(ref IOrganism organism);
private IMetrics MetricsFunction(IOrganism organism)
{
var o = (IGEPOrganism) organism;
var value = this.GetValue(o,
this.GetInputRegistry(o, 1),
this.GetInputRegistry(o, 2),
this.GetInputRegistry(o, 3),
this.GetInputRegistry(o, 4),
this.GetInputRegistry(o, 5),
this.GetInputRegistry(o, 6),
this.GetInputRegistry(o, 8),
this.GetInputRegistry(o, 9)
);
const double worstFitness = 15000;
if (double.IsNaN(value) || double.IsInfinity(value))
value = worstFitness;
return new Metrics() {Value = new MetricsValue() {Value = value}};
}
public void Add(IOrganism member)
{
this.Members.Add(member);
}
public void Remove(IOrganism member)
{
this.Members.Remove(member);
}
public override void ConstructFromOrganism(IOrganism organism, GeneticFaraday.Contracts.Organisms.OrganismBehavior.Surroundings.ISurroundings surroundings)
{
this.Chromosomes = new List<IDebuggableChromosome>();
}
public override void Execute(ref IOrganism organism)
{
var chromosome = (IGEPChromosome) organism[0];
var main = chromosome.Main;
main.GetActiveAllele().DNA.RandomlyFlipNucleotide();
}
/// <summary> /// Gets the IMetrics of the IOrganism. /// /// Calls EvaluationStart at its beginning and EvaluationEnd at its end. /// </summary> /// <returns></returns> public abstract IMetrics GetMetrics(IOrganism organism);
private double CalculateFitness(IOrganism o)
{
List<City> cities = this.cityInfo.Select(c => c.Name).ToList();
var numbers = o.Chromosomes[0].GetGenes().Select((g, i) => Convert.ToInt32(g.ToString(), 2)).ToList();
double totalDistance = 0;
City lastCity = City.Unknown;
numbers.ForEach(i =>
{
City currentCity = cities[i];
cities.RemoveAt(i);
if (lastCity == City.Unknown) {
lastCity = currentCity;
} else {
totalDistance += this.GetDistance(lastCity, currentCity);
lastCity = currentCity;
}
});
return 1 / totalDistance;
}
public virtual void RespondTo(IOrganism organism)
{
}
/// <summary>
/// The provided IOrganism must be an IGEPOrganism.
/// </summary>
/// <param name="item"></param>
new public void Add(IOrganism item)
{
this.Add((IGEPOrganism) item);
}
/// <summary>
/// Gets the percentage that IOrganism one and IOrganism two are similar.
/// 100% would be identical and 0% would indicate that the IOrganisms share nothing.
/// </summary>
/// <param name="one">The first IOrganism to compare.</param>
/// <param name="two">The second IOrganism to compare.</param>
/// <returns>The percentage that IOrganism one and IOrgnaism two are similar.
/// 100% would be identical and 0% would indicate that the IOrganisms share nothing.</returns>
public override double GetPercentageIOrganismSimilarity(IOrganism one, IOrganism two)
{
return this.GetPercentageIOrganismSimilarityDelegate(one: one, two: two);
}
public void Mutate(IOrganism organism)
{
this.MutationCount += 1;
}