public IEnumerator LTW255ToZero()
{
var LTWGainRate = 16;
var Start = 255;
var End = 3;
var DynamicsGene = new DendriteDynamicsGene(LTWGainRate, 0, 0, null, 0, null, 0, null, null, 0);
DendriteGene DendriteGene = new DendriteGene(0, 0, DendriteGene.SpreadType.Flat, 0, new Vector2Int(0, 0), new Vector2Int(Start, Start), new Vector2Int(1, 1), DynamicsGene);
TestDendrite Dendrite = new TestDendrite(0, 0, DendriteGene);
Dendrite.MockSTW(1);
// Process assumes it is being called in FixedUpdate
// i.e. 10 times a second
foreach (var i in Enumerable.Range(0, 10))
{
Dendrite.Process(null, false, false);
}
Assert.AreEqual(End, Mathf.RoundToInt(Dendrite.LTW));
yield return(null);
}
public LobeGene(
BrainLobeID lobeID,
Vector2Int location,
Vector2Int dimension,
DendriteGene dendrite0,
DendriteGene dendrite1,
NeuronGene neuronGene,
int copyToPerceptionLobe,
int winnerTakesAll
)
{
LobeID = lobeID;
Location = location;
Dimension = dimension;
Dendrite0 = dendrite0;
Dendrite1 = dendrite1;
NeuronGene = neuronGene;
CopyToPerceptionLobe = copyToPerceptionLobe > 0 ? true : false;
WinnerTakesAll = winnerTakesAll == 1 ? true : false;
}
public IEnumerator GetValue()
{
var DynamicsGene = new DendriteDynamicsGene(1, 0, 0, null, 0, null, 0, null, null, 0);
DendriteGene DendriteGene = new DendriteGene(0, 0, DendriteGene.SpreadType.Flat, 0, new Vector2Int(0, 0), new Vector2Int(5, 5), new Vector2Int(1, 1), DynamicsGene);
TestDendrite Dendrite = new TestDendrite(0, 0, DendriteGene);
NeuronGene NeuronGene = new NeuronGene(0, 0, 0, null);
Lobe lobe = new Lobe(0, null, new Vector2Int(0, 0), new Vector2Int(5, 5), Enumerable.Range(0, 25).Select(n => new Neuron(n, NeuronGene)).ToList(), false, false);
lobe.FireNeuron(0);
Dendrite.SetSourceLobe(lobe);
Dendrite.MockSTW(1);
var DendriteValue = Dendrite.GetValue();
Assert.AreEqual(1, DendriteValue);
Dendrite.MockSTW(255);
DendriteValue = Dendrite.GetValue();
Assert.AreEqual(255, DendriteValue);
yield return(null);
}
public static List <Dendrite> BuildFromGene(DendriteGene gene, int sourceLobeSize, int destinationCellIndex)
{
List <Dendrite> Dendrites = new List <Dendrite>();
// In C2, it appears that the spread doesn't really make any difference
// and it's the fanout that actually alters the distribution
// also, fanout may wrap round (e.g. in a 5-cell lobe, a fanout 1 dendrite may go to cell 4 and cell 0)
//hard coding for perception lobe
bool Drive = false;
bool Verb = false;
foreach (var r in Enumerable.Range(0, gene.NumDendrites))
{
int SourceNeuronIndex = Random.Range(destinationCellIndex - gene.Fanout, destinationCellIndex + gene.Fanout) % sourceLobeSize;
SourceNeuronIndex = (int)Mathf.Repeat(SourceNeuronIndex, sourceLobeSize);
// Hard code perception lobe for now
if (gene.SourceLobeIndex == BrainLobeType.Perception)
{
if (SourceNeuronIndex >= 0 && SourceNeuronIndex <= 15)
{
Dendrites.Add(new Dendrite(gene.SourceLobeIndex, SourceNeuronIndex, gene, !Drive));
Drive = true;
}
else if (SourceNeuronIndex >= 16 && SourceNeuronIndex <= 31)
{
Dendrites.Add(new Dendrite(gene.SourceLobeIndex, SourceNeuronIndex, gene, !Verb));
Verb = true;
}
else
{
Dendrites.Add(new Dendrite(gene.SourceLobeIndex, SourceNeuronIndex, gene));
}
}
else
{
Dendrites.Add(new Dendrite(gene.SourceLobeIndex, SourceNeuronIndex, gene));
}
}
return(Dendrites);
}
public static Chromosome CreateCrossover(Chromosome ch1, Chromosome ch2)
{
Gene[] genes = CrossoverManager.Crossover(ch1.Genes, ch2.Genes);
var neuralComparableGenes = CrossoverManager.Crossover(ch1.neuralChromosome.GetComparableGenes(), ch2.neuralChromosome.GetComparableGenes());
DendriteGene[] dendriteGenes = new DendriteGene[neuralComparableGenes.Length];
for (int i = 0; i < dendriteGenes.Length; i++)
{
dendriteGenes[i] = neuralComparableGenes[i].GetGene();
}
NeuralChromosome neuralChromosome = new NeuralChromosome(dendriteGenes);
ChromosomeParameters parameters = CrossoverManager.CrossParameters(ch1.Parameters, ch2.Parameters);
Chromosome chromosome = new Chromosome(genes, neuralChromosome, ch1.MutationTracker + "CR", parameters);
return(chromosome);
}
public static List <Neuron> SetUpDendrites(List <Neuron> neurons, DendriteGene d0, DendriteGene d1, int numSourceNeurons0, int numSourceNeurons1)
{
foreach (var Neuron in neurons)
{
if (d0 == null || d1 == null)
{
return(neurons);
}
if (d0.NumDendrites > 0)
{
Neuron.Dendrites0 = DendriteBuilder.BuildFromGene(d0, numSourceNeurons0, Neuron.Index);
}
else
{
Neuron.Dendrites0 = new List <Dendrite>(0);
}
if (d1.NumDendrites > 0)
{
Neuron.Dendrites1 = DendriteBuilder.BuildFromGene(d1, numSourceNeurons1, Neuron.Index);
}
else
{
Neuron.Dendrites1 = new List <Dendrite>(0);
}
}
return(neurons);
}
public ComparableGene(DendriteGene dendrite)
{
this.startNeuron = dendrite.startNeuron;
this.endNeuron = dendrite.endNeuron;
this.dendrite = dendrite;
}
public TestDendrite(BrainLobeType sourceLobeIndex, int sourceNeuronIndex, DendriteGene gene) : base(sourceLobeIndex, sourceNeuronIndex, gene)
{
}