public void UpdateClusterMeans()
{
ClusterObject newCentroid = new ClusterObject();
double[] newCoordinates = new double[m_nDimensionCount];
foreach (KeyValuePair<int, ClusterObject> kvp in m_dictObjects)
{
for (int i = 0; i < m_nDimensionCount; i++)
{
newCoordinates[i] += kvp.Value.Coordinates[i];
}
}
for (int i = 0; i < m_nDimensionCount; i++)
{
newCoordinates[i] /= m_dictObjects.Count;
}
newCentroid.Coordinates = new List<double>(newCoordinates);
if (m_OldClusterCentroid == null)
{
m_OldClusterCentroid = newCentroid;
}
else
{
m_OldClusterCentroid = m_ClusterCentroid;
}
m_ClusterCentroid = newCentroid;
EuclidianDistanceStrategy e = new EuclidianDistanceStrategy();
double dDistance = e.CalculateDistance(m_OldClusterCentroid, m_ClusterCentroid);
if (dDistance > 0) //TODO: Set an acceptable margin to determine if the
// center moved or not. To aviod osciallation, small changes
// may be neglected.
{
CenterMoved = true;
}
else
{
CenterMoved = false;
}
}
public static double CalculateDistance(ClusterObject object1, ClusterObject object2)
{
EuclidianDistanceStrategy distance = new EuclidianDistanceStrategy();
return distance.CalculateDistance(object1, object2);
}
