/// <summary>
/// build the input connectivity matrix.
/// </summary>
public void setInputConnectivity()
{
System.Random rand = new System.Random();
inputConnections.Clear();
foreach (NeuronIzhikevich n in neurons)
{
n.inputsConnections.Clear();
}
foreach (string key in modalities.Keys)
{
inputConnections[key] = new List <NeuronIzhikevich.Connection> [modalities[key].Size];
for (int m = 0; m < modalities[key].Size; m++)
{
inputConnections[key][m] = new List <NeuronIzhikevich.Connection>();
//Create the connection with a random weight
//inputConnections[key][m].Add(new NeuronIzhikevich.Connection(ref neurons[x, y], 1.0, rand.NextDouble()));
for (int x = 0; x < width; x++)
{
for (int y = 0; y < height; y++)
{
NeuronIzhikevich.Connection c = new NeuronIzhikevich.Connection(neurons[x, y], 1.0, 0.5 /*rand.NextDouble()*/);
inputConnections[key][m].Add(c);
neurons[x, y].inputsConnections.Add(c);
}
}
}
}
}
/// <summary>
/// Reset the local connectivity of the map
/// </summary>
/// <param name="neighboorRadius"></param>
protected void setLateralConnectivity(double neighboorRadius, double lateralW = 0.4)
{
//Reset the lateral connextivity the neurons
lateralConnections.Clear();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
neurons[x, y].lateralProjections.Clear();
}
}
//Build the connections
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
//Go through all the connected neurons
for (int y2 = y - (int)neighboorRadius; y2 <= y + (int)neighboorRadius; y2++)
{
for (int x2 = x - (int)neighboorRadius; x2 <= x + (int)neighboorRadius; x2++)
{
//Calculate the right index for this connection (here we can go circular)
//For now we just check if the index is inbounds
if (y2 >= 0 && y2 < height &&
x2 >= 0 && x2 < width &&
(x != x2 || y != y2))
{
//if (x != x2 || y != y2)
{
double distance = MathFunctions.EuclideanDistance(new float[] { x, y }, new float[] { x2, y2 });
//Console.WriteLine("Distance = " + distance + " Neighbor = " + neighboorRadius);
//If the neuron is in the neihboor range
if (distance < neighboorRadius)
{
//We add a connection with strenght shaped by a mexican hat
//We calculate sigma to so that the inhibition takes place on the border of the neighborhood
float sigma = (float)neighboorRadius / 4.0f;
float strenght = (float)MathFunctions.MexicanHat((float)distance, sigma);
//Console.Write(strenght);
//float strenght = (float)lateralW;
NeuronIzhikevich.Connection cnt = new NeuronIzhikevich.Connection(neurons[x2, y2], distance, strenght);
lateralConnections.Add(cnt);
neurons[x, y].lateralProjections.Add(cnt);
}
}
}
}
//Console.WriteLine();
}
}
}
}