private void RebuildDistanceProps()
{
const double B = .75d; // y=mx+b: don't want to use a b of 1, because y gets added to a neuron's current output, so multiple objects close together would quickly saturate a neuron
const double B_at_neighbor = .4d; // at a distance of nearest neighbor, what the output should be (this needs to be relatively high so that there is some overlap. Otherwise there are holes where items won't be seen)
// Rise over run, but negative
double slope = (B_at_neighbor - B) / _neuronDistBetween;
// I want a distance of _neuronDistBetween between the outermost neuron and SearchRadius
double scale = _searchRadius / (_neuronMaxRadius + _neuronDistBetween);
// Take each existing length times scale to see where they should be. Don't need to worry about checking for
// null, there are no neurons at 0,0,0.
Point3D[] worldScalePositions = _neurons.Select(o => (o.PositionUnit.Value * (o.PositionLength * scale)).ToPoint()).ToArray();
// Store a new one
_distProps = new DistanceProps(_searchRadius, _neuronMaxRadius, _neuronDistBetween, slope, B, worldScalePositions);
}
private static void UpdateNeurons(Neuron_SensorPosition[] neurons, Tuple<Point3D, Quaternion> location, IEnumerable<MapObjectInfo> items, DistanceProps distProps, long botToken)
{
//TODO: Rotate into world
// Since neuron.Value is a volatile, build up the final values in a local array
double[] values = new double[neurons.Length];
Vector3D positionVect = location.Item1.ToVector();
foreach (MapObjectInfo item in items)
{
if (item.Token == botToken)
{
continue;
}
for (int cntr = 0; cntr < neurons.Length; cntr++)
{
//TODO: don't just look at item's position. Should also account for its radius
double distance = (distProps.NeuronWorldPositions[cntr] + positionVect - item.Position).Length;
// y=mx+b
double neuronValue = (distProps.Slope * distance) + distProps.B;
if (neuronValue > 0) // if the item is too far from the neuron, the slope will take the value negative, but just ignore those
{
values[cntr] += neuronValue;
}
}
}
// Store the new neuron values
for (int cntr = 0; cntr < neurons.Length; cntr++)
{
if (values[cntr] > 1)
{
neurons[cntr].Value = 1;
}
else
{
neurons[cntr].Value = values[cntr];
}
}
}
