private void CalculateClusterCenters()
{
for (int j = 0; j < this.Clusters.Count; j++)
{
ClusterCentroid c = this.Clusters[j];
double uX = 0.0;
double uY = 0.0;
double l = 0.0;
for (int i = 0; i < this.Points.Count; i++)
{
ClusterPoint p = this.Points[i];
double uu = Math.Pow(U[i, j], this.Fuzzyness);
uX += uu * c.X;
uY += uu * c.Y;
l += uu;
}
c.X = ((int)(uX / l));
c.Y = ((int)(uY / l));
this.Log += string.Format("Cluster Centroid: ({0}; {1})" + System.Environment.NewLine, c.X, c.Y);
}
}
public CMeansAlgorithm(List <ClusterPoint> points, List <ClusterCentroid> clusters, float fuzzy)
{
if (points == null)
{
throw new ArgumentNullException("points");
}
if (clusters == null)
{
throw new ArgumentNullException("clusters");
}
this.Points = points;
this.Clusters = clusters;
U = new double[this.Points.Count, this.Clusters.Count];
//Uk = new double[this.Points.Count, this.Clusters.Count];
this.Fuzzyness = fuzzy;
double diff;
// Iterate through all points to create initial U matrix
for (int i = 0; i < this.Points.Count; i++)
{
ClusterPoint p = this.Points[i];
double sum = 0.0;
for (int j = 0; j < this.Clusters.Count; j++)
{
ClusterCentroid c = this.Clusters[j];
diff = Math.Sqrt(Math.Pow(p.X - c.X, 2.0) + Math.Pow(p.Y - c.Y, 2.0));
U[i, j] = (diff == 0) ? Eps : diff;
sum += U[i, j];
}
double sum2 = 0.0;
for (int j = 0; j < this.Clusters.Count; j++)
{
U[i, j] = 1.0 / Math.Pow(U[i, j] / sum, 2.0 / (Fuzzyness - 1.0));
sum2 += U[i, j];
}
for (int j = 0; j < this.Clusters.Count; j++)
{
U[i, j] = U[i, j] / sum2;
}
}
this.RecalculateClusterIndexes();
}
private double CalculateEulerDistance(ClusterPoint p, ClusterCentroid c)
{
return(Math.Sqrt(Math.Pow(p.X - c.X, 2) + Math.Pow(p.Y - c.Y, 2)));
}
