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Algorithms for the JUNG project

There is a newer version: 2.1.1








Provides general algorithmic utilities.  These include:

DiscreteDistribution: calculates statistical measures on 
discrete probability distributions represented as double arrays
KMeansClusterer: uses the k-means algorithm to cluster 
points in d-dimensional space into k clusters 
MapBinaryHeap: a binary heap implementation that permits
efficient element access and update operations
RandomLocationTransformer: a class that randomly assigns
2D coordinates to items (default initializer for iterative Layouts)
SettableTransformer: an extension of Transformer
that allows mutation of the transformation