/// <summary> /// /// </summary> protected override IEnumerable <Cluster> Cluster(IntensityMatrix vmatrix, DistanceMatrix UNUSED, ArgsClusterer args, ConfigurationClusterer tag, ProgressReporter prog) { // GET OPTIONS int k = (int)args.Parameters[0]; // CREATE RANDOM CENTRES Random rnd = new Random(); var potentialCentres = new List <Vector>(vmatrix.Vectors); List <Cluster> clusters = new List <Cluster>(); for (int n = 0; n < k; n++) { int random = rnd.Next(potentialCentres.Count); Cluster p = new Cluster((clusters.Count + 1).ToString(), tag); Vector vec = potentialCentres[random]; p.Exemplars.Add(vec.Values); potentialCentres.RemoveAt(random); clusters.Add(p); } // Assign to exemplars prog.Enter("Initialising assignments"); LegacyClustererHelper.Assign(vmatrix, clusters, ECandidateMode.Exemplars, args.Distance, prog); prog.Leave(); // Centre LegacyClustererHelper.PerformKMeansCentering(vmatrix, clusters, args.Distance, prog); return(clusters); }
/// <summary> /// /// </summary> protected override IEnumerable <Cluster> Cluster(IntensityMatrix vmatrix, DistanceMatrix UNUSED, ArgsClusterer args, ConfigurationClusterer tag, ProgressReporter prog) { // Get parameters // COUNT LIMIT int countLimit = (int)tag.UntypedArgs.Parameters[0]; // DISTANCE LIMIT double distanceLimit = (double)tag.UntypedArgs.Parameters[1]; // SEED PEAK WeakReference <Peak> seedPeakRef = (WeakReference <Peak>)tag.UntypedArgs.Parameters[2]; Peak seedPeak = seedPeakRef.GetTargetOrThrow(); // SEED GROUP GroupInfo groupInfo = (GroupInfo)tag.UntypedArgs.Parameters[3]; // DO-K-MEANS? bool doKMeans = (bool)tag.UntypedArgs.Parameters[4]; // Create the seed cluster Cluster seedCluster = new Cluster("1", tag); List <Cluster> seedList = new List <Cluster> { seedCluster }; int seedIndex = vmatrix.FindIndex(new IntensityMatrix.RowHeader(seedPeak, args.SplitGroups ? groupInfo : null)); if (seedIndex == -1) { throw new InvalidOperationException($"The chosen peak {{{seedPeak}}} cannot be used a seed because it is not present in the value matrix. Please check that this peak has not been excluded by the filter condition {{{args.PeakFilter}}}."); } seedCluster.Exemplars.Add(vmatrix.Vectors[seedIndex]); // Autogenerate the clusters int? nCountLimit = (countLimit != Int32.MinValue) ? countLimit : (int?)null; double?nDistanceLimit = (distanceLimit != Double.MinValue) ? countLimit : (double?)null; List <Cluster> autoGenClusters = AutogenerateClusters(vmatrix, seedList, nDistanceLimit, nCountLimit, args.Distance, tag, prog); // Do k-means (if requested) if (doKMeans) { prog.Enter("k-means"); LegacyClustererHelper.PerformKMeansCentering(vmatrix, autoGenClusters, args.Distance, prog); prog.Leave(); } // Return full list return(autoGenClusters); }