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

package edu.uci.ics.jung.algorithms.util
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
  • 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.
    IterativeContext
    An interface for algorithms that proceed iteratively.
    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.
    KMeansClusterer.NotEnoughClustersException
    An exception that indicates that the specified data points cannot be clustered into the number of clusters requested by the user.
    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.
    SelfLoopEdgePredicate<V,E>
    A Predicate that returns true if the input edge's endpoints in the input graph are identical.
    SettableTransformer<I,O>
    An interface for classes that can set the value to be returned (from transform()) when invoked on a given input.
    WeightedChoice<T>
    Selects items according to their probability in an arbitrary probability distribution.