// this method compute distance between clusters thas has subclusters (cluster2 represents the new cluster)
public static double ComputeDistance(Cluster cluster1, Cluster cluster2, DissimilarityMatrix dissimilarityMatrix, Strategy strategy)
{
double distance1, distance2, distance = 0;
//get the distance between cluster1 and subcluster0 of the cluster2
distance1 = dissimilarityMatrix.ReturnClusterPairDistance(new ClusterPair(cluster1, cluster2.GetSubCluster(0)));
//get the distance between cluster1 and subcluster1 of the cluster cluster2
distance2 = dissimilarityMatrix.ReturnClusterPairDistance(new ClusterPair(cluster1, cluster2.GetSubCluster(1)));
switch (strategy)
{
case Strategy.SingleLinkage: distance = _MinValue(distance1, distance2); break;
case Strategy.CompleteLinkage: distance = _MaxValue(distance1, distance2); break;
case Strategy.AverageLinkageWPGMA: distance = (distance1 + distance2) / 2; break;
case Strategy.AverageLinkageUPGMA:
distance = ((cluster2.GetSubCluster(0).TotalQuantityOfPatterns *distance1) / cluster2.TotalQuantityOfPatterns) + ((cluster2.GetSubCluster(1).TotalQuantityOfPatterns *distance2) / cluster2.TotalQuantityOfPatterns);
break;
default: break;
}
return(distance);
}
// compute the distance between all pair of clusters and store it on the dissimilarity matrix. this algorithm step is done using parallelization to improve performance.
private void _BuildDissimilarityMatrixParallel()
{
double distanceBetweenTwoClusters;
_dissimilarityMatrix = new DissimilarityMatrix();
Parallel.ForEach(_ClusterPairCollection(), clusterPair =>
{
distanceBetweenTwoClusters = ClusterDistance.ComputeDistance(clusterPair.Cluster1, clusterPair.Cluster2);
_dissimilarityMatrix.AddClusterPairAndDistance(clusterPair, distanceBetweenTwoClusters);
});
}
// calcula a distancia entre todos os clusters e as armazena na matrix de dissimilaridade
private void CreateDissimilarityMatrix()
{
double distanceBetweenTwoClusters;
_dissimilarityMatrix = new DissimilarityMatrix();
ClusterPair clusterPair;
for (int i = 0; i < _clusters.Count(); i++)
{
for (int j = i + 1; j < _clusters.Count(); j++)
{
clusterPair = new ClusterPair();
clusterPair.Cluster1 = _clusters.GetCluster(i);
clusterPair.Cluster2 = _clusters.GetCluster(j);
distanceBetweenTwoClusters = ClusterDistance.ComputeDistance(clusterPair.Cluster1, clusterPair.Cluster2);
_dissimilarityMatrix.AddClusterPairAndDistance(clusterPair, distanceBetweenTwoClusters);
}
}
}
