private static NeuralLink[] BuildExternalLinksExisting_AcrossParts(NeuralLinkExternalDNA dnaLink, HighestPercentResult[] partLinks, ContainerInput[] containers, Dictionary<ContainerInput, ContainerPoints> nearestNeurons, int maxIntermediateLinks, int maxFinalLinks)
{
List<NeuralLink> retVal = new List<NeuralLink>();
foreach (HighestPercentResult partLink in partLinks)
{
#region Get containers
ContainerInput fromContainer = containers[partLink.From.Index];
if (!nearestNeurons.ContainsKey(fromContainer))
{
nearestNeurons.Add(fromContainer, new ContainerPoints(fromContainer, maxIntermediateLinks));
}
ContainerPoints from = nearestNeurons[fromContainer];
ContainerInput toContainer = containers[partLink.To.Index];
if (!nearestNeurons.ContainsKey(toContainer))
{
nearestNeurons.Add(toContainer, new ContainerPoints(toContainer, maxIntermediateLinks));
}
ContainerPoints to = nearestNeurons[toContainer];
#endregion
List<LinkIndexed> links = new List<LinkIndexed>();
// Build links
HighestPercentResult[] bestLinks = GetHighestPercent(from.GetNearestPoints(dnaLink.From), to.GetNearestPoints(dnaLink.To), maxIntermediateLinks, false);
foreach (HighestPercentResult link in bestLinks)
{
double[] brainChemicals = null;
if (dnaLink.BrainChemicalModifiers != null)
{
brainChemicals = dnaLink.BrainChemicalModifiers.
Take(fromContainer.BrainChemicalCount). // if there are more, just drop them
Select(o => o).
//Select(o => o * link.Percent). // I decided not to multiply by percent. The weight is already reduced, no point in double reducing
ToArray();
}
links.Add(new LinkIndexed(link.From.Index, link.To.Index, dnaLink.Weight * link.Percent, brainChemicals));
}
// Convert the indices into return links
retVal.AddRange(links.Select(o => new NeuralLink(fromContainer.Container, toContainer.Container, from.AllNeurons[o.From], to.AllNeurons[o.To], partLink.Percent * o.Weight, o.BrainChemicalModifiers)));
}
if (retVal.Count > maxFinalLinks)
{
// Prune and normalize percents
var pruned = Prune(retVal.Select(o => o.Weight).ToArray(), maxFinalLinks); // choose the top X weights, and tell what the new weight should be
retVal = pruned.Select(o => new NeuralLink(retVal[o.Item1].FromContainer, retVal[o.Item1].ToContainer, retVal[o.Item1].From, retVal[o.Item1].To, o.Item2, retVal[o.Item1].BrainChemicalModifiers)).ToList(); // copy the referenced retVal items, but with the altered weights
}
// Exit Function
return retVal.ToArray();
}
public ContainerInput(long token, INeuronContainer container, NeuronContainerType containerType, Point3D position, Quaternion orientation, double? internalRatio, Tuple<NeuronContainerType, ExternalLinkRatioCalcType, double>[] externalRatios, int brainChemicalCount, NeuralLinkDNA[] internalLinks, NeuralLinkExternalDNA[] externalLinks)
{
this.Token = token;
this.Container = container;
this.ContainerType = containerType;
this.Position = position;
this.Orientation = orientation;
this.InternalRatio = internalRatio;
this.ExternalRatios = externalRatios;
this.BrainChemicalCount = brainChemicalCount;
this.InternalLinks = internalLinks;
this.ExternalLinks = externalLinks;
}
