public AxonGuidanceForcesSumEventArgs(Neuron neuron, int refY, int refX, double[,] score)
{
Neuron = neuron;
RefY = refY;
RefX = refX;
Score = score;
}
public double[,] GetScore(int refY, int refX, Neuron neuron)
{
var result = GetInitializationResult();
int minX = Math.Max(refX - GuidanceForceRange, 0);
int maxX = Math.Min(refX + GuidanceForceRange, Network.Width - 1);
int minY = Math.Max(refY - GuidanceForceRange, 0);
int maxY = Math.Min(refY + GuidanceForceRange, Network.Height - 1);
for (int y = minY; y < maxY; y++)
{
for (int x = minX; x < maxX; x++)
{
// only check in the desired radius
if ((x == refX && y == refY)
/* this ensures that we only check within the range */
|| (Extensions.GetDistance(refX, refY, x, y)) > GuidanceForceRange)
{
continue;
}
if (PreCheckLocation(x, y, neuron) == false)
{
continue;
}
result[y - minY, x - minX] = ComputeScoreAtLocation(x, y, neuron);
}
}
InvokeScoreAvailableEvent(refY, refX, neuron, result);
return result;
}
protected override bool PreCheckLocation(int x, int y, Neuron neuron)
{
return base.PreCheckLocation(x, y, neuron)
&& (x != neuron.PosX || y != neuron.PosY)
&& Extensions.GetNeuronAt(y, x, Network) == null
&& neuron.MovedDistance + Extensions.GetDistance(neuron.PosX, neuron.PosY, x, y) < Network.MaxNeuronMoveDistance
&& Extensions.GetDistanceToNearestNeuron(y, x, neuron, Network) > Network.MinDistanceBetweenNeurons;
}
public GuidanceForceScoreEventArgs(GuidanceForceBase guidanceForce, int refY, int refX, Neuron neuron, double[,] score)
{
GuidanceForce = guidanceForce;
RefY = refY;
RefX = refX;
Neuron = neuron;
Score = score;
}
public IEnumerable<Neuron> GetActiveNeurons()
{
var resultCount = (int)(_availableNeurons.Count * _percentActiveNeurons);
var result = new Neuron[resultCount];
for (int i = 0; i < resultCount; i++)
{
result[i] = _availableNeurons[_random.Next(_availableNeurons.Count)];
}
return result;
}
public void Update(int x, int y, Neuron neuron)
{
}
protected override bool PreCheckLocation(int x, int y, Neuron neuron)
{
return base.PreCheckLocation(x, y, neuron)
&& GetDistanceFromOtherWayPoints(x, y) > Network.AxonMinDistanceToOtherWayPoints;
}
public override double ComputeScoreAtLocation(int x, int y, Neuron neuron)
{
return 0;
}
public void GenerateNetwork()
{
NeuronDesirabilityMap = new double[Height, Width];
NeuronUndesirabilityMap = new double[Height, Width];
NeuronPositionMap = new Neuron[Height, Width];
NeuronAxonWayPoints = new NeuronAxonWaypoint[Height, Width];
AxonGuidanceForces = GetAxonGuidanceForces();
SomaGuidanceForces = GetSomaGuidanceForces();
#region Generate Random Neurons
var neurons = new List<Neuron>();
#region generate input neurons
int generatedNeuronId = 0;
for (int index = 0; index < InputNeuronCount; index++)
{
var neuron = new Neuron(generatedNeuronId++, this, AxonGuidanceForces, SomaGuidanceForces, NeuronType.Input);
int baseIndex = NeuronInputMarginBetween * (index + 1) + 60;
int y = (baseIndex + NeuronGenerationMargin) % Height;
int x = baseIndex / Height + NeuronGenerationMargin;
neuron.MoveTo(y, x);
neuron.ResetMovedDistance();
neurons.Add(neuron);
NeuronPositionMap[neuron.PosY, neuron.PosX] = neuron;
}
#endregion
#region generate output neurons
for (int index = 0; index < OutputNeuronCount; index++)
{
var neuron = new Neuron(generatedNeuronId++, this, AxonGuidanceForces, SomaGuidanceForces, NeuronType.Output);
int baseIndex = NeuronInputMarginBetween * (index + 1) + 60;
int y = (baseIndex + NeuronGenerationMargin) % Height;
int x = Width - (baseIndex / Height + NeuronGenerationMargin);
neuron.MoveTo(y, x);
neuron.ResetMovedDistance();
neurons.Add(neuron);
NeuronPositionMap[neuron.PosY, neuron.PosX] = neuron;
}
#endregion
#region generate other neurons
for (int index = 0; index < NeuronCount; index++)
{
var neuron = new Neuron(generatedNeuronId++, this, AxonGuidanceForces, SomaGuidanceForces, NeuronType.Process);
do
{
neuron.MoveTo(_random.Next(Height - 2 * NeuronGenerationMargin) + NeuronGenerationMargin,
_random.Next(Width - 2 * (NeuronGenerationMargin + NeuronProcessMarginFromInputAndOutputNeurons)) + NeuronGenerationMargin + NeuronProcessMarginFromInputAndOutputNeurons);
}
while (neurons.Any(n => n.PosX == neuron.PosX && n.PosY == neuron.PosY)
|| Extensions.GetDistanceToNearestNeuron(neuron.PosY, neuron.PosX, neuron, this) <= MinDistanceBetweenNeurons);
neuron.ResetMovedDistance();
neurons.Add(neuron);
NeuronPositionMap[neuron.PosY, neuron.PosX] = neuron;
}
#endregion
_neurons = neurons.ToArray();
#endregion Generate Random Neurons
_neuronsInput = neurons.Take(InputNeuronCount).ToArray();
_neuronsOutput = neurons.Skip(InputNeuronCount).Take(OutputNeuronCount).ToArray();
//var inputOutputNeuronBindings = new List<Tuple<Neuron, Neuron>>();
//for (int index = 0; index < InputNeuronCount; index++)
//{
// inputOutputNeuronBindings.Add(new Tuple<Neuron,Neuron>(_neuronsInput.ElementAt(index), _neuronsOutput.ElementAt(index)));
//}
BindedActiveNeuronGenerator = new PushPullBoxActivityGenerator(this, _neuronsInput, _neuronsOutput);
NormalActiveNeuronGenerator = new SequentialActiveInputNeuronGenerator(_neuronsInput, Math.Min(_neuronsInput.Length, 3));
ActiveNeuronGenerator = NormalActiveNeuronGenerator;
_iteration = 0;
}
public void RestartNetwork()
{
NeuronDesirabilityMap = new double[Height, Width];
NeuronUndesirabilityMap = new double[Height, Width];
NeuronPositionMap = new Neuron[Height, Width];
NeuronAxonWayPoints = new NeuronAxonWaypoint[Height, Width];
#region Generate Random Neurons
var oldNeurons = _neurons.ToList();
var neurons = new List<Neuron>();
for (int index = 0; index < oldNeurons.Count; index++)
{
var neuron = new Neuron(index, this, AxonGuidanceForces, SomaGuidanceForces,
index >= NeuronCount ? NeuronType.Input : NeuronType.Process);
neuron.MoveTo(oldNeurons[index].PosY, oldNeurons[index].PosX);
neuron.ResetMovedDistance();
neurons.Add(neuron);
NeuronPositionMap[neuron.PosY, neuron.PosX] = neuron;
}
_neurons = neurons.ToArray();
#endregion Generate Random Neurons
_neuronsInput = neurons.GetRange(NeuronCount, InputNeuronCount).ToArray();
ActiveNeuronGenerator = new SequentialActiveInputNeuronGenerator(_neuronsInput, Math.Min(_neuronsInput.Length, 3));
_iteration = 0;
}
/// <summary>
/// Perform VERY FAST checks here
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="neuron">The neuron context to check</param>
/// <returns></returns>
protected virtual bool PreCheckLocation(int x, int y, Neuron neuron)
{
return true;
}
public NeuronChangedEventArgs(Neuron neuron)
{
Contract.Requires<ArgumentNullException>(neuron != null);
Neuron = neuron;
}
public abstract double ComputeScoreAtLocation(int x, int y, Neuron neuron);
private void OnViewerManagerNeuronSelectedChanged(object sender, NeuronChangedEventArgs e)
{
SelectedNeuron = e.Neuron;
_viewerAxonTerminalGuidanceForces.Neuron = e.Neuron;
_viewerSomaDesirabilityMapGuidanceForce.Neuron = e.Neuron;
}
protected override bool PreCheckLocation(int x, int y, Neuron neuron)
{
return base.PreCheckLocation(x, y, neuron)
&& Math.Abs(Network.NeuronUndesirabilityMap[y, x] - 0.0d) < 0.00001 == false;
}
public override double ComputeScoreAtLocation(int x, int y, Neuron neuron)
{
return 3 * Network.NeuronUndesirabilityMap[y, x];
}
public NeuronAxonWaypoint(int id, Neuron neuron, Point waypoint)
{
Id = id;
Neuron = neuron;
Waypoint = waypoint;
}
private void InvokeScoreAvailableEvent(int refY, int refX, Neuron neuron, double[,] score)
{
var handler = ScoreAvailableEvent;
if (handler != null)
{
handler(this, new GuidanceForceScoreEventArgs(this, refY, refX, neuron, score));
}
}
public bool GetWasActive(Neuron exclusiveNeuron)
{
return Network.NeuronActivityHistory.Any(item => item.Contains(this)
&& item.Contains(exclusiveNeuron) == false);
}
private void UpdateHoverAndSelectedNeuron(int mousePosX, int mousePosY, bool leftButtonPressed)
{
NeuronHover = Extensions.GetClosestNeuronsWithinRange(mousePosX, mousePosY, _network, 10);
if (NeuronHover != null)
{
if (leftButtonPressed)
{
NeuronSelected = NeuronHover;
}
}
}
private void OnNeuronHoverChanged(Neuron value)
{
var handler = NeuronHoverChanged;
if (handler != null)
{
handler(this, new NeuronChangedEventArgs(value));
}
}
public bool GetWasActive(Neuron exclusiveNeuron)
{
return(Network.NeuronActivityHistory.Any(item => item.Contains(this) &&
item.Contains(exclusiveNeuron) == false));
}
public NeuronAxonWaypoint(int id, Neuron neuron, Point waypoint)
{
Id = id;
Neuron = neuron;
Waypoint = waypoint;
}