/// <summary>
/// c) Update clustering by calculating the distance between the chromosome genes and the mean vectors for each cluster
/// </summary>
/// <param name="numClusters"></param>
/// <param name="clusterMeanVectors"></param>
/// <returns></returns>
public bool updateClustering(int numClusters, double[][] clusterMeanVectors)
{
bool go = true;
bool hasChanged = false;
bool hasZeroMembers = false;
//Run through all the chromosomes and compare its genes to all the mean vectors. Store new temporary clusterIds
int[] tempClusterId = new int[chromosomes.Length];
for (int i = 0; i < chromosomes.Length; i++)
{
double[] distances = new double[numClusters];
//Run through the clusters in order to compare to each mean vector
for (int j = 0; j < numClusters; j++)
{
distances[j] = Friends.calcDistance(chromosomes[i].GetGenes(), clusterMeanVectors[j]);
}
int newClusterId = identifyClusterId(distances);
tempClusterId[i] = newClusterId;
if (chromosomes[i].clusterId != newClusterId)
{
hasChanged = true;
}
}
//Check that each new cluster contains at least one chromosome before changing the clusterId property
int[] tempClusterCounts = new int[numClusters];
for (int i = 0; i < numClusters; i++)
{
tempClusterCounts[i] = 0;
}
for (int i = 0; i < chromosomes.Length; i++)
{
tempClusterCounts[tempClusterId[i]]++;
}
for (int i = 0; i < tempClusterCounts.Length; i++)
{
if (tempClusterCounts[i] == 0)
{
hasZeroMembers = true;
}
}
//If no cluster has zero elements then update the chromosome clusterId property
if (!hasZeroMembers)
{
for (int i = 0; i < chromosomes.Length; i++)
{
chromosomes[i].clusterId = tempClusterId[i];
}
}
//Check whether the cluster loop shall continue or not
if (!hasChanged || hasZeroMembers)
{
go = false;
}
return(go);
}
