Package edu.uci.ics.jung.algorithms.generators.random
Methods for generating random graphs with various properties. These include:
BarabasiAlbertGenerator
: scale-free graphs using the preferential attachment heuristic.EppsteinPowerLawGenerator
: graphs whose degree distribution approximates a power lawErdosRenyiGenerator
: graphs for which edges are created with a specified probabilityMixedRandomGraphGenerator
: takes the output ofBarabasiAlbertGenerator
and perturbs it to generate a mixed-mode analog with both directed and undirected edges.
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Class Summary Class Description BarabasiAlbertGenerator<V,E> Simple evolving scale-free random graph generator.EppsteinPowerLawGenerator<V,E> Graph generator that generates undirected graphs with power-law degree distributions.ErdosRenyiGenerator<V,E> Generates a random graph using the Erdos-Renyi binomial model (each pair of vertices is connected with probability p).KleinbergSmallWorldGenerator<V,E> Graph generator that produces a random graph with small world properties.MixedRandomGraphGenerator Generates a mixed-mode random graph (with random edge weights) based on the output ofBarabasiAlbertGenerator
.