private void ClearData()
{
topColours = null;
previousCluster = null;
currentCluster = null;
Histogram = null;
Thresholds.Clear();
clusterArr.Clear();
converged = false;
}
private void Iterate()
{
float d, curD;
KeyValuePair <int, Cluster> closestCl = new KeyValuePair <int, Cluster>();
//find closest cluster for each histogram unit and apply info
foreach (KeyValuePair <ushort, HistogramUnit> node in Histogram)
{
d = float.MaxValue;
foreach (KeyValuePair <int, Cluster> c in currentCluster)
{
curD = Math.Abs(c.Value.Centroid - (float)node.Key);
if (curD < d)
{
d = curD;
closestCl = c;
}
}
closestCl.Value.Counter += node.Value.Counter;
closestCl.Value.Sum += node.Value.Sum;
if (closestCl.Value.Min > node.Key)
{
closestCl.Value.Min = node.Key;
}
if (closestCl.Value.Max < node.Key)
{
closestCl.Value.Max = node.Key;
}
}
//calculate the new centroids
foreach (KeyValuePair <int, Cluster> c in currentCluster)
{
c.Value.Centroid = c.Value.Sum / c.Value.Counter;
}
//Calculate new thresholds
clusterArr.Clear();
for (int i = 0; i < currentCluster.Count; i++)
{
Cluster tempClust = null;
foreach (KeyValuePair <int, Cluster> cluster in currentCluster)
{
if (clusterArr.IndexOf(cluster.Value) == -1)
{
if (tempClust == null)
{
tempClust = cluster.Value;
}
else if (tempClust.Min > cluster.Value.Min)
{
tempClust = cluster.Value;
}
}
}
if (tempClust != null)
{
clusterArr.Add(tempClust);
}
}
Thresholds.Clear();
for (int i = 0, j = 1; j < clusterArr.Count; i++, j++)
{
Thresholds.Add((int)(clusterArr[i].Max + ((clusterArr[j].Min - clusterArr[i].Max) / 2)));
}
Thresholds.Add(int.MaxValue);
clusterArr.Clear();
//Clear;
foreach (KeyValuePair <int, Cluster> c in currentCluster)
{
c.Value.Min = float.MaxValue;
c.Value.Max = float.MinValue;
c.Value.Counter = 1;
c.Value.Sum = (long)c.Value.Centroid;
}
CheckConvergence();
}
