Class BarabasiAlbertGenerator<V,E>
- java.lang.Object
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- edu.uci.ics.jung.algorithms.generators.random.BarabasiAlbertGenerator<V,E>
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- All Implemented Interfaces:
com.google.common.base.Supplier<Graph<V,E>>
,EvolvingGraphGenerator<V,E>
,GraphGenerator<V,E>
,java.util.function.Supplier<Graph<V,E>>
public class BarabasiAlbertGenerator<V,E> extends java.lang.Object implements EvolvingGraphGenerator<V,E>
Simple evolving scale-free random graph generator. At each time step, a new vertex is created and is connected to existing vertices according to the principle of "preferential attachment", whereby vertices with higher degree have a higher probability of being selected for attachment.
At a given timestep, the probability
p
of creating an edge between an existing vertexv
and the newly added vertex isp = (degree(v) + 1) / (|E| + |V|);
where
|E|
and|V|
are, respectively, the number of edges and vertices currently in the network (counting neither the new vertex nor the other edges that are being attached to it).Note that the formula specified in the original paper (cited below) was
p = degree(v) / |E|
However, this would have meant that the probability of attachment for any existing isolated vertex would be 0. This version uses Lagrangian smoothing to give each existing vertex a positive attachment probability.
The graph created may be either directed or undirected (controlled by a constructor parameter); the default is undirected. If the graph is specified to be directed, then the edges added will be directed from the newly added vertex u to the existing vertex v, with probability proportional to the indegree of v (number of edges directed towards v). If the graph is specified to be undirected, then the (undirected) edges added will connect u to v, with probability proportional to the degree of v.
The
parallel
constructor parameter specifies whether parallel edges may be created.- Author:
- Scott White, Joshua O'Madadhain, Tom Nelson - adapted to jung2, James Marchant
- See Also:
- "A.-L. Barabasi and R. Albert, Emergence of scaling in random networks, Science 286, 1999."
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Field Summary
Fields Modifier and Type Field Description protected com.google.common.base.Supplier<E>
edgeFactory
protected com.google.common.base.Supplier<Graph<V,E>>
graphFactory
protected java.util.Map<V,java.lang.Integer>
index_vertex
protected int
init_vertices
protected java.util.List<V>
vertex_index
protected com.google.common.base.Supplier<V>
vertexFactory
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Constructor Summary
Constructors Constructor Description BarabasiAlbertGenerator(com.google.common.base.Supplier<Graph<V,E>> graphFactory, com.google.common.base.Supplier<V> vertexFactory, com.google.common.base.Supplier<E> edgeFactory, int init_vertices, int numEdgesToAttach, int seed, java.util.Set<V> seedVertices)
Constructs a new instance of the generator.BarabasiAlbertGenerator(com.google.common.base.Supplier<Graph<V,E>> graphFactory, com.google.common.base.Supplier<V> vertexFactory, com.google.common.base.Supplier<E> edgeFactory, int init_vertices, int numEdgesToAttach, java.util.Set<V> seedVertices)
Constructs a new instance of the generator, whose output will be an undirected graph, and which will use the current time as a seed for the random number generation.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
evolveGraph(int numTimeSteps)
Instructs the algorithm to evolve the graph N steps.Graph<V,E>
get()
int
numIterations()
Retrieves the total number of steps elapsed.
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Field Detail
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vertex_index
protected java.util.List<V> vertex_index
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init_vertices
protected int init_vertices
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index_vertex
protected java.util.Map<V,java.lang.Integer> index_vertex
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vertexFactory
protected com.google.common.base.Supplier<V> vertexFactory
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edgeFactory
protected com.google.common.base.Supplier<E> edgeFactory
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Constructor Detail
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BarabasiAlbertGenerator
public BarabasiAlbertGenerator(com.google.common.base.Supplier<Graph<V,E>> graphFactory, com.google.common.base.Supplier<V> vertexFactory, com.google.common.base.Supplier<E> edgeFactory, int init_vertices, int numEdgesToAttach, int seed, java.util.Set<V> seedVertices)
Constructs a new instance of the generator.- Parameters:
graphFactory
- factory for graphs of the appropriate typevertexFactory
- factory for vertices of the appropriate typeedgeFactory
- factory for edges of the appropriate typeinit_vertices
- number of unconnected 'seed' vertices that the graph should start withnumEdgesToAttach
- the number of edges that should be attached from the new vertex to pre-existing vertices at each time stepseed
- random number seedseedVertices
- storage for the seed vertices that this graph creates
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BarabasiAlbertGenerator
public BarabasiAlbertGenerator(com.google.common.base.Supplier<Graph<V,E>> graphFactory, com.google.common.base.Supplier<V> vertexFactory, com.google.common.base.Supplier<E> edgeFactory, int init_vertices, int numEdgesToAttach, java.util.Set<V> seedVertices)
Constructs a new instance of the generator, whose output will be an undirected graph, and which will use the current time as a seed for the random number generation.- Parameters:
graphFactory
- factory for graphs of the appropriate typevertexFactory
- factory for vertices of the appropriate typeedgeFactory
- factory for edges of the appropriate typeinit_vertices
- number of vertices that the graph should start withnumEdgesToAttach
- the number of edges that should be attached from the new vertex to pre-existing vertices at each time stepseedVertices
- storage for the seed vertices that this graph creates
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Method Detail
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evolveGraph
public void evolveGraph(int numTimeSteps)
Description copied from interface:EvolvingGraphGenerator
Instructs the algorithm to evolve the graph N steps.- Specified by:
evolveGraph
in interfaceEvolvingGraphGenerator<V,E>
- Parameters:
numTimeSteps
- number of steps to iterate from the current state
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numIterations
public int numIterations()
Description copied from interface:EvolvingGraphGenerator
Retrieves the total number of steps elapsed.- Specified by:
numIterations
in interfaceEvolvingGraphGenerator<V,E>
- Returns:
- number of elapsed steps
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