public IGenome Copy()
{
Dictionary <Guid, INode> nodeReplacements = new Dictionary <Guid, INode>();
List <IGene> genes = Genes.Select(g => g.Copy()).ToList();
genes.ToList().ForEach(g =>
{
if (!nodeReplacements.Any(nr => nr.Key == g.NodeIn.Id))
{
nodeReplacements.Add(g.NodeIn.Id, g.NodeIn.Copy());
}
if (!nodeReplacements.Any(nr => nr.Key == g.NodeOut.Id))
{
nodeReplacements.Add(g.NodeOut.Id, g.NodeOut.Copy());
}
g.NodeIn = nodeReplacements[g.NodeIn.Id];
g.NodeOut = nodeReplacements[g.NodeOut.Id];
});
return(new Genome()
{
Id = Id,
Genes = genes,
Nodes = nodeReplacements.Select(nr => nr.Value).ToList()
});
}
public DNA <T> Crossover(DNA <T> otherParent)
{
DNA <T> child = new DNA <T>(Genes.Length, random, getRandomGene, determineFitness, InitializeGenes: false);
child.Genes = Genes.Select((g, i) => random.NextDouble() < 0.5 ? g : otherParent.Genes[i]).ToArray();
return(child);
}
public Generation(DirectoryInfo d)
{
RootPath = d.FullName;
Name = d.Name;
Genes = d.GetDirectories().Select(x => new Gene(x)).OrderByDescending(x => x.Score).ToList();
AverageScore = Genes.Select(x => x.Score).Where(x => x != double.MinValue).DefaultIfEmpty().Average();
MaxScore = Genes.Select(x => x.Score).Where(x => x != double.MinValue).DefaultIfEmpty().Max();
}
public ChromosomeType Clone()
{
var result = new ChromosomeType(Size);
result.Genes = Genes
.Select(x => x)
.ToArray();
return(result);
}
public override void Evaluar()
{
int valor = 0;
var genes = Genes.Select(gen => new
{
Horario = gen.Horario,
Asignatura = gen.Asignatura.Nombre,
Aula = gen.Aula.Nombre,
Profesor = gen.Asignatura.NombreProfesor
});
valor += 10 * genes
.GroupBy(gen => new
{
CodigoProf = gen.Profesor,
Horario = gen.Horario
})
.Where(gen => gen.Count() > 1)
.Count();
valor += 10 * genes
.GroupBy(gen => new
{
Horario = gen.Horario,
Aula = gen.Aula
})
.Where(res => res.Count() > 1)
.Count();
valor += 5 * genes.
GroupBy(gen => new
{
Asignatura = gen.Asignatura,
Aula = gen.Aula
})
.Where(res => res.Count() != 4)
.Count();
valor += 3 * genes
.GroupBy(gen => new
{
Asignatura = gen.Asignatura,
Aula = gen.Aula,
Dia = HorarioHelper.Dia(gen.Horario)
})
.Where(res => res.Count() > 1)
.Count();
this.Fitness = valor;
}
public virtual IGenome <T> CreateNew(bool copyGenes = true)
{
IList <Gene <T> > genes;
if (copyGenes)
{
genes = Genes.Select(x => new Gene <T>(x)).ToArray();
}
else
{
genes = Genes;
}
return(new GenomeBase <T>(genes));
}
public override IGenome <Synapse> CreateNew(bool copyGenes = true)
{
IList <Gene <Synapse> > genes;
IList <Neuron> neurons;
if (copyGenes)
{
genes = Genes.Select(x => new Gene <Synapse>(x)).ToArray();
}
else
{
genes = Genes;
}
neurons = NeuronLst.Select(x => new Neuron(x)).ToArray();
return(new NeuralGenomeBase(neurons, genes, ActivationF));
}
public override void Evaluar()
{
return;
int valor = 0;
//se sumará el coste de los horarios asignados
//valor += Genes
// .Select(gen => gen.Coste)
// .Sum();
var genes = Genes.Select(gen => new
{
Profesor = gen.Asignatura.NombreProfesor,
Horario = gen.Horario,
Asignatura = gen.Asignatura.Nombre,
Aula = gen.Aula.Nombre
});
//se calcula el número de apariciones del profesor
//en el mismo horario
valor += 5 * genes
.GroupBy(gen => new
{
CodigoProf = gen.Profesor,
Horario = gen.Horario
})
.Where(gen => gen.Count() > 1)
.Count();
//se calcula el número de apariciones del profesor
//en el mismo horario
valor += 5 * Genes
.GroupBy(gen => new
{
Horario = gen.Horario,
Aula = gen.Aula.Nombre
})
.Where(res => res.Count() > 1)
.Count();
this.Fitness = valor;
}
public override List <Individual> getNeighbourhood()
{
var individuos = new List <Individual>();
for (int i = 0; i < 10; i++)
{
var genes = Genes
.Select(gen => {
return(new Gen()
{
Asignatura = gen.Asignatura,
Coste = 0,
Horario = gen.Horario,
Aula = AulaHelper.Aleatorea(gen.Asignatura.TipoAula,
gen.Horario)
});
}).ToList();
individuos.Add(new IndividuoUniversidad(genes));
}
return(individuos);
}
public override List <Individual> getNeighbourhood()
{
individuos.Clear();
int horarios = HorarioHelper.NumHorarios();
for (int i = 0; i < 5; i++)
{
var genes = Genes
.Select(gen =>
{
return(new Gen()
{
Asignatura = AsignaturaHelper.Aleatorea(),
Coste = 0,
Horario = gen.Horario,
Aula = gen.Aula
});
});
individuos.Add(new IndividuoPrescolar(genes));
}
return(individuos);
}
public void Mutate(double MutationRate)
{
Genes = Genes.Select(g => random.NextDouble() < MutationRate ? getRandomGene(random) : g).ToArray();
}
public override string ToString()
{
return(string.Join(" ", Genes.Select(g => g.Allele)));
}
public string GetPath()
{
return(string.Join("\n\t", Genes.Select(c => c.Name)));
}
// Set weights to genes
public double[] getWeights()
{
// Set each weight in the neural net to its gene representation
return(Genes.Select(gene => gene.Allele).ToArray());
}