public double Distance(KCluster cluster, quadPanel input)
{
//euclidean distance between centroid weights and input weights
double d = Math.Pow(cluster.weightVector.X - input.weights[0], 2)
+ Math.Pow(cluster.weightVector.Y - input.weights[1], 2)
+ Math.Pow(cluster.weightVector.Z - input.weights[2], 2);
return(Math.Sqrt(d));
}
quadPanel[] inputs; //input panels
public KClusterGroup(int K, quadPanel[] inputs)
{
this.K = K;
Random rnd = new Random();
centroids = new KCluster[K];
for (int i = 0; i < centroids.Length; i++)
{
int randomIndex = rnd.Next(centroids.Length);
centroids[i] = new KCluster(inputs[randomIndex]);
}
this.inputs = inputs;
//assign inputs to clusters for first time
AssignClusters();
}
