//public Type FilterType { get; set; }
#endregion
#region Public Methods
public override ShipPartDNA GetDNA()
{
SensorVisionDNA retVal = new SensorVisionDNA();
base.FillDNA(retVal);
retVal.SearchRadius = SearchRadius;
//retVal.FilterType = FilterType;
return(retVal);
}
private static NeuronLayer[] CreateNeurons_Layers(SensorVisionDNA dna, ItemOptionsArco itemOptions)
{
if (dna.Filters == null || dna.Filters.Length == 0)
{
throw new ApplicationException("This method requires filters to be populated");
}
var count = GetNeuronCount(dna.Scale, itemOptions.Sensor_NeuronGrowthExponent, itemOptions.VisionSensor_NeuronDensity);
//TODO: SensorVisionFilterType.Bot will need two layers
var neuronZs = GetNeuron_Zs(dna.Filters.Length, count.radius);
Point3D[] staticPositions = new Point3D[] { new Point3D(0, 0, 0) };
Point3D[] singlePlate = null;
if (dna.Neurons != null && dna.Neurons.Length > 0)
{
var byLayer = NeuralUtility.DivideNeuronLayersIntoSheets(dna.Neurons, neuronZs.z, count.neuronCount);
// Just use one of the layer's positions to re evenly distribute (first layer with the correct number of neurons - or closest number).
// Could try to find the nearest between each layer and use the average of each set, but that's a lot of expense with very little payoff
singlePlate = GetBestNeuronSheet(byLayer, count.neuronCount);
}
// Make sure there is a correct number of neurons and apply an even distribution
singlePlate = NeuralUtility.GetNeuronPositions_Circular_Even(singlePlate, staticPositions, 1d, count.neuronCount, count.radius).
Select(o => o.ToPoint()).
ToArray();
// Use the location of neurons in this single layer for all layers. By making sure that each neuron represents the same point in each
// layer (and the index of that neuron is the same in each layer), position logic in each tick can be optimized
return(Enumerable.Range(0, dna.Filters.Length).
Select(o => new NeuronLayer()
{
FilterType = dna.Filters[o],
Z = neuronZs.z[o],
Neurons = singlePlate.
Select(p => new Neuron_SensorPosition(new Point3D(p.X, p.Y, neuronZs.z[o]), true, true)).
ToArray(),
}).
ToArray());
}
public SensorVision(EditorOptions options, ItemOptionsArco itemOptions, SensorVisionDNA dna, Map map)
: base(options, dna, itemOptions.VisionSensor_Damage.HitpointMin, itemOptions.VisionSensor_Damage.HitpointSlope, itemOptions.VisionSensor_Damage.Damage)
{
_itemOptions = itemOptions;
_map = map;
Design = new SensorVisionDesign(options, true);
Design.SetDNA(dna);
double radius, volume;
SensorGravity.GetMass(out _mass, out volume, out radius, out _scaleActual, dna, itemOptions);
Radius = radius;
if (dna.Filters == null || dna.Filters.Length == 0)
{
_neurons = CreateNeurons(dna, itemOptions, itemOptions.VisionSensor_NeuronDensity, true, true);
_neuronLayers = null;
_allNeurons = _neurons;
var distances = GetNeuronAvgDistance(_neurons.Select(o => o.Position.ToPoint2D()).ToArray());
_neuronDistBetween = distances.distBetween;
_neuronMaxRadius = distances.maxRadius;
}
else
{
_neuronLayers = CreateNeurons_Layers(dna, itemOptions);
_neurons = null;
_allNeurons = _neuronLayers.
SelectMany(o => o.Neurons).
ToArray();
var distances = GetNeuronAvgDistance(_neuronLayers[0].Neurons.Select(o => o.Position.ToPoint2D()).ToArray()); // all the layers have neurons in the same place
_neuronDistBetween = distances.distBetween;
_neuronMaxRadius = distances.maxRadius;
}
SearchRadius = dna.SearchRadius; // need to set this last, because it populates _distProps
}
