protected static IEnumerable <Cluster> CreateClustersFromIntegers(IntensityMatrix vmatrix, IList <int> clusters, ConfigurationClusterer tag)
{
Dictionary <int, Cluster> pats = new Dictionary <int, Cluster>();
List <Cluster> r = new List <Cluster>();
for (int n = 0; n < vmatrix.NumRows; n++)
{
Vector p = vmatrix.Vectors[n];
int c = clusters != null ? clusters[n] : 0;
Cluster pat;
if (!pats.TryGetValue(c, out pat))
{
pat = new Cluster((pats.Count + 1).ToString(), tag);
pats.Add(c, pat);
r.Add(pat);
}
pat.Assignments.Add(new Assignment(p, pat, double.NaN));
}
return(r);
}
public ResultClusterer ExecuteAlgorithm(Core core, int isPreview, bool doNotCluster, ArgsClusterer args, ConfigurationClusterer tag, ProgressReporter prog, out IntensityMatrix vmatrixOut, out DistanceMatrix dmatrixOut)
{
IReadOnlyList <Peak> peaks;
if (isPreview > 0 && isPreview < core.Peaks.Count)
{
List <Peak> p = core.Peaks.ToList();
p.Shuffle();
p = p.GetRange(0, Math.Min(isPreview, p.Count)).ToList();
// Make sure any seed peaks are in the list
foreach (Peak peak in tag.Args.Parameters.OfType <WeakReference <Peak> >().Select(par => (par).GetTargetOrThrow()))
{
p.Insert(0, peak);
p.RemoveAt(p.Count - 1);
}
peaks = p;
}
else
{
peaks = core.Peaks;
}
// FILTER PEAKS
PeakFilter pfilter = args.PeakFilter ?? PeakFilter.Empty;
IntensityMatrix src = args.SourceMatrix;
Filter <Peak> .Results filter = pfilter.Test(peaks);
Cluster insigs;
if (filter.Failed.Count == 0)
{
insigs = null;
}
else
{
insigs = new Cluster("Insig", tag);
insigs.States |= Session.Main.Cluster.EStates.Insignificants;
// We still need the vmatrix for plotting later
IntensityMatrix operational = src.Subset(args.PeakFilter, args.ObsFilter, ESubsetFlags.InvertPeakFilter);
if (args.SplitGroups)
{
operational = operational.SplitGroups();
}
for (int index = 0; index < operational.NumRows; index++)
{
Vector p = new Vector(operational, index);
insigs.Assignments.Add(new Assignment(p, insigs, double.NaN));
}
}
// CREATE VMATRIX AND FILTER OBSERVATIONS
PeakFilter temp = new PeakFilter("filtered in", null, new[] { new PeakFilter.ConditionPeak(Filter.ELogicOperator.And, false, filter.Failed, Filter.EElementOperator.IsNot) });
IntensityMatrix vmatrix = src.Subset(args.PeakFilter, args.ObsFilter, ESubsetFlags.None);
if (args.SplitGroups)
{
vmatrix = vmatrix.SplitGroups();
}
prog.Enter("Creating distance matrix");
DistanceMatrix dmatrix = RequiresDistanceMatrix ? DistanceMatrix.Create(core, vmatrix, args.Distance, prog) : null;
prog.Leave();
IEnumerable <Cluster> clusters;
if (doNotCluster)
{
vmatrixOut = vmatrix;
dmatrixOut = dmatrix;
return(null);
}
// CLUSTER USING VMATRIX OR DMATRIX
prog.Enter("Clustering");
clusters = Cluster(vmatrix, dmatrix, args, tag, prog);
prog.Leave();
vmatrixOut = vmatrix;
dmatrixOut = dmatrix;
List <Cluster> result = new List <Cluster>();
if (insigs != null)
{
result.Add(insigs);
}
result.AddRange(clusters);
return(new ResultClusterer(result));
}
/// <summary> /// Clustering /// /// If the cluster does't make use of the distance matrix OR the distance metric it should flag itself with DoesNotSupportDistanceMetrics. /// </summary> protected abstract IEnumerable <Cluster> Cluster(IntensityMatrix vmatrix, DistanceMatrix dmatrix, ArgsClusterer args, ConfigurationClusterer tag, ProgressReporter prog);
