/// <summary>
/// Helper function for ModelDeviation. Outputs
/// estimates of average cluster deviation.
/// </summary>
protected double ClusterDeviation(List<SegmentInfo> segments, int numClusters, double tempDeviation, out int heterogeneousClusters, out double heterogeneityIndex, bool bestModel, string debugPathClusterInfo = null)
{
// compute average deviation for each cluster (clusterDeviation)
List<ClusterModel> clusterDeviations = new List<ClusterModel>();
for (int clusterID = 0; clusterID < numClusters; clusterID++)
{
ClusterModel clusterInfo = new ClusterModel();
clusterInfo.ClusterID = clusterID + 1;
clusterDeviations.Add(clusterInfo);
}
// populate clusters
foreach (SegmentInfo info in segments)
{
if (info.Cluster.Value != -1 && info.MAF != -1)
clusterDeviations[info.Cluster.Value - 1].ClusterDistances.Add(Tuple.Create(Convert.ToSingle(info.Distance), Convert.ToSingle(info.Weight)));
}
// compute cluster mean and standard deviation
for (int clusterID = 0; clusterID < numClusters; clusterID++)
{
clusterDeviations[clusterID].ClusterMedianDistance = Convert.ToDouble(CanvasCommon.Utilities.WeightedMedian(clusterDeviations[clusterID].ClusterDistances));
clusterDeviations[clusterID].ClusterDistanceIQR = Convert.ToDouble(CanvasCommon.Utilities.WeightedIQR(clusterDeviations[clusterID].ClusterDistances));
}
// exlcude clusters with deviation larger than 1.5 of average deviation
// these clusters locate far from expected model centroids and most likely represent segments coming from heterogeneous variants
double clusterDeviation = 0;
List<double> heterogeneousClusterID = new List<double>();
for (int i = 0; i < numClusters; i++)
{
foreach (ClusterModel clusterInfo in clusterDeviations)
if (clusterInfo.ClusterMedianDistance < tempDeviation * 1.5f)
clusterDeviation += clusterInfo.ClusterMedianDistance;
else if (bestModel)
heterogeneousClusterID.Add(i + 1);
}
// store signatures of potential heterogeneous variants
if (heterogeneousClusterID.Count > 0 && bestModel)
{
foreach (SegmentInfo info in segments)
if (heterogeneousClusterID.Contains(info.Cluster.Value))
this.HeterogeneousSegmentsSignature.Add(info.Segment.Begin + info.Segment.End + info.Segment.Counts.Count);
}
heterogeneousClusters = heterogeneousClusterID.Count;
// derive heterogeneity index
if (bestModel)
{
heterogeneityIndex = ComputeHeterogeneityIndex(clusterDeviations, tempDeviation);
}
else
heterogeneityIndex = 0;
// write cluster deviations
if (debugPathClusterInfo != null)
{
using (StreamWriter debugWriter = new StreamWriter(debugPathClusterInfo))
{
foreach (ClusterModel clusterInfo in clusterDeviations)
debugWriter.WriteLine("{0:F3}\t{1:F3}", clusterInfo.ClusterMedianDistance, clusterInfo.ClusterDistanceIQR);
}
}
return clusterDeviation;
}
