private static Tuple <SamplePoint[], Neuron_SensorPosition[][]> CreateNeurons(ShipPartDNA dna, ItemOptions itemOptions)
{
#region count
// Figure out how many sample points to create
//NOTE: radius assumes a sphere, but this camera is a cone. Not perfect, but good enough
double radius = (dna.Scale.X + dna.Scale.Y + dna.Scale.Z) / (3d * 2d); // xyz should all be the same anyway
double volume = Math.Pow(radius, itemOptions.Sensor_NeuronGrowthExponent);
int numSamples = Convert.ToInt32(Math.Ceiling(itemOptions.CameraHardCoded_NeuronDensity * volume));
if (numSamples == 0)
{
numSamples = 1;
}
#endregion
//TODO: Calculate this based on the densitiy of sets inside the cone portion of the unit sphere
double setSize = .1;
#region positions
// Get points in a cone
//NOTE: Going with a narrower angle, because the neurons will go to the edges, but the neurons will be the center of a vision sphere -- so the actual vision will be larger than this cone
Vector3D[] pointsModel = Math3D.GetRandomVectors_Cone_EvenDist(numSamples, CameraColorRGBDesign.CameraDirection, 60, .2, 1);
// Turn into sensor neurons
Neuron_SensorPosition[][] neurons = pointsModel.
Select(o => GetNeuronSet(o.ToPoint(), setSize)).
ToArray();
double worldMax = itemOptions.CameraHardCoded_WorldMax;
//NOTE: The term world is a bit misleading. It's world distances, but still technically model coords. It's just not neural's unit circle coords
Point3D[] pointsWorld = pointsModel.
Select(o =>
{
double distanceFromOrigin = o.Length;
return(o.ToUnit() * (worldMax * Math.Pow(distanceFromOrigin, 3)));
}).
Select(o => o.ToPoint()).
ToArray();
#endregion
#region vision radius
// Delaunay
//TODO: Throw out thin triangles
Tetrahedron[] tetras = Math3D.GetDelaunay(pointsWorld, 10);
double approximateRadius = worldMax * .667;
double[] cellRadii = null;
if (tetras == null)
{
cellRadii = Enumerable.Range(0, pointsWorld.Length).
Select(o => approximateRadius).
ToArray();
}
else
{
Tuple <int, int>[] uniqueLines = Tetrahedron.GetUniqueLines(tetras);
cellRadii = Enumerable.Range(0, pointsWorld.Length).
Select(o => GetCellRadius(o, pointsWorld, uniqueLines, approximateRadius)).
ToArray();
}
#endregion
// Turn into sample points
SamplePoint[] samplePoints = Enumerable.Range(0, numSamples).
Select(o => new SamplePoint(pointsModel[o].ToPoint(), pointsWorld[o].ToVector(), cellRadii[o], neurons[o])).
ToArray();
return(Tuple.Create(samplePoints, neurons));
}
