Package edu.uci.ics.jung.algorithms.util

Provides general algorithmic utilities.

See: Description

Interface Summary

Interface	Description
IterativeContext	An interface for algorithms that proceed iteratively.
SettableTransformer<I,O>	An interface for classes that can set the value to be returned (from transform()) when invoked on a given input.

Class Summary

Class	Description
BasicMapEntry<K,V>	An simple minimal implementation of Map.Entry.
DiscreteDistribution	A utility class for calculating properties of discrete distributions.
Indexer	A class providing static methods useful for improving the performance of graph algorithms.
IterativeProcess	Provides basic infrastructure for iterative algorithms.
KMeansClusterer<T>	Groups items into a specified number of clusters, based on their proximity in d-dimensional space, using the k-means algorithm.
MapBinaryHeap<T>	An array-based binary heap implementation of a priority queue, which also provides efficient update() and contains operations.
MapSettableTransformer<I,O>	A SettableTransformer that operates on an underlying Map instance.
NotRandom	A decidedly non-random extension of Random that may be useful for testing random algorithms that accept an instance of Random as a parameter.
SelfLoopEdgePredicate<V,E>	A Predicate that returns true if the input edge's endpoints in the input graph are identical.
TestWeightedChoice
WeightedChoice<T>	Selects items according to their probability in an arbitrary probability distribution.

Exception Summary

Exception	Description
KMeansClusterer.NotEnoughClustersException	An exception that indicates that the specified data points cannot be clustered into the number of clusters requested by the user.

Package edu.uci.ics.jung.algorithms.util Description

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