public SOMColors()
{
InitializeComponent();
network = CreateNetwork();
gaussian = new NeighborhoodRBF(RBFEnum.Gaussian, WIDTH, HEIGHT);
train = new BasicTrainSOM(network, 0.01, null, gaussian);
train.ForceWinner = false;
samples = AIFH.Alloc2D<double>(15, 3);
for (int i = 0; i < 15; i++)
{
samples[i][0] = rnd.NextDouble(-1, 1);
samples[i][1] = rnd.NextDouble(-1, 1);
samples[i][2] = rnd.NextDouble(-1, 1);
}
train.SetAutoDecay(100, 0.8, 0.003, 30, 5);
}
/// <summary>
/// Construct a BestMatchingUnit class. The training class must be provided.
/// </summary>
/// <param name="som">The SOM to evaluate.</param>
public BestMatchingUnit(SelfOrganizingMap som)
{
_som = som;
}
/// <summary>
/// Construct a BestMatchingUnit class. The training class must be provided.
/// </summary>
/// <param name="som">The SOM to evaluate.</param>
public BestMatchingUnit(SelfOrganizingMap som)
{
_som = som;
}
private SelfOrganizingMap CreateNetwork()
{
var result = new SelfOrganizingMap(3, WIDTH*HEIGHT);
result.Reset();
return result;
}