Uses of Interface
ffx.numerics.clustering.LinkageStrategy

Packages that use LinkageStrategy

Package	Description
ffx.numerics.clustering	The clustering package provides hierarchical agglomerative clustering utilities, including linkage strategies (single, complete, average, weighted), distance map management, and supporting data structures and algorithms.

Uses of LinkageStrategy in ffx.numerics.clustering

Classes in ffx.numerics.clustering that implement LinkageStrategy

Modifier and Type	Class	Description
class	AverageLinkageStrategy	Linkage strategy that uses the arithmetic mean of pairwise distances between cluster members (UPGMA/average linkage).
class	CompleteLinkageStrategy	Linkage strategy that uses the maximum of pairwise distances between cluster members (complete-linkage / farthest-neighbor).
class	SingleLinkageStrategy	Linkage strategy that uses the minimum of pairwise distances between cluster members (single-linkage / nearest-neighbor).
class	WeightedLinkageStrategy	Linkage strategy that computes a weighted average of pairwise distances using the associated weights of cluster members.

Methods in ffx.numerics.clustering with parameters of type LinkageStrategy

Modifier and Type	Method	Description
void	HierarchyBuilder.agglomerate(LinkageStrategy linkageStrategy)	Performs one agglomerative step by merging the two closest clusters and updating linkages.
List<Cluster>	HierarchyBuilder.flatAgg(LinkageStrategy linkageStrategy, Double threshold)	Performs agglomeration until the minimal inter-cluster distance exceeds the threshold, and returns the remaining clusters (flat clustering at that cut).
Cluster	ClusteringAlgorithm.performClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy)	Performs hierarchical agglomerative clustering on a square distance matrix.
Cluster	DefaultClusteringAlgorithm.performClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy)	Performs hierarchical agglomerative clustering using a full N x N distance matrix.
Cluster	PDistClusteringAlgorithm.performClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy)	Performs hierarchical agglomerative clustering using a condensed pdist-like matrix.
List<Cluster>	ClusteringAlgorithm.performFlatClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy, Double threshold)	Performs a flat clustering by agglomerating until the next linkage distance would exceed the provided threshold, and returns the list of clusters at that cut.
List<Cluster>	DefaultClusteringAlgorithm.performFlatClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy, Double threshold)	Produces a flat clustering by agglomerating until the next merge would exceed the threshold.
List<Cluster>	PDistClusteringAlgorithm.performFlatClustering(double[][] distances, String[] clusterNames, LinkageStrategy linkageStrategy, Double threshold)	Produces a flat clustering from a condensed distance matrix by agglomerating until the threshold is exceeded.
Cluster	ClusteringAlgorithm.performWeightedClustering(double[][] distances, String[] clusterNames, double[] weights, LinkageStrategy linkageStrategy)	Performs hierarchical clustering when each initial element has an associated weight.
Cluster	DefaultClusteringAlgorithm.performWeightedClustering(double[][] distances, String[] clusterNames, double[] weights, LinkageStrategy linkageStrategy)	Performs hierarchical clustering when each element has an associated weight.
Cluster	PDistClusteringAlgorithm.performWeightedClustering(double[][] distances, String[] clusterNames, double[] weights, LinkageStrategy linkageStrategy)	Weighted variant for condensed inputs; currently delegates to unweighted clustering as weights are not applied with condensed input in this implementation.