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object RandomGraph

Provides convenience metrics and methods for the generation of random graphs.

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Type Members

  1. trait IntFactory extends Metrics[Int]
  2. trait Metrics[N] extends MetricsBase[N]
  3. trait MetricsBase[N] extends AnyRef

    Template for Metrics with connected set to true and some lazy values useful for checking the metrics of generated graphs.

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
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  2. final def ##(): Int
    Definition Classes
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  3. final def ==(arg0: Any): Boolean
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  4. def apply[N, E[X] <: EdgeLikeIn[X], G[X, Y[Z] <: EdgeLikeIn[Z]] <: Graph[X, Y[Z]] with GraphLike[X, Y[Z], G]](graphCompanion: GraphCompanion[G], metrics: Metrics[N], edgeCompanions: Set[EdgeCompanionBase[E]])(implicit edgeTag: ClassTag[E[N]], nodeTag: ClassTag[N]): RandomGraph[N, E, G]
  5. def apply[N, E[X] <: EdgeLikeIn[X], G[X, Y[Z] <: EdgeLikeIn[Z]] <: Graph[X, Y[Z]] with GraphLike[X, Y[Z], G]](graphCompanion: GraphCompanion[G], order: Int, nodeFactory: ⇒ N, nodeDegree: NodeDegreeRange, edgeCompanions: Set[EdgeCompanionBase[E]], connected: Boolean, weightFactory: Option[() ⇒ Long], labelFactory: Option[() ⇒ Any])(implicit edgeTag: ClassTag[E[N]], nodeTag: ClassTag[N]): RandomGraph[N, E, G]
  6. final def asInstanceOf[T0]: T0
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  7. def clone(): AnyRef
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    protected[java.lang]
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    @native() @throws( ... )
  8. def diGraph[N, G[N, E[X] <: EdgeLikeIn[X]] <: Graph[N, E[X]] with GraphLike[N, E[X], G]](graphCompanion: GraphCompanion[G], metrics: Metrics[N])(implicit edgeTag: ClassTag[DiEdge[N]], nodeTag: ClassTag[N]): RandomGraph[N, DiEdge, G]

    Returns a generator for non-labeled directed graphs of any metrics and any type.

    Returns a generator for non-labeled directed graphs of any metrics and any type.

    metrics

    The Metrics to be applied to the generated graph.

  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
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  10. def equals(arg0: Any): Boolean
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  11. def finalize(): Unit
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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]
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    @native()
  13. def hashCode(): Int
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    @native()
  14. final def isInstanceOf[T0]: Boolean
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  15. final def ne(arg0: AnyRef): Boolean
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  16. final def notify(): Unit
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    @native()
  17. final def notifyAll(): Unit
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    @native()
  18. def smallConnectedIntDi[G[N, E[X] <: EdgeLikeIn[X]] <: Graph[N, E[X]] with GraphLike[N, E[X], G]](graphCompanion: GraphCompanion[G]): RandomGraph[Int, DiEdge, G]

    Returns a generator for small, connected, non-labeled directed graphs with the metrics defined by SmallInt.

  19. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  20. def tinyConnectedIntDi[G[N, E[X] <: EdgeLikeIn[X]] <: Graph[N, E[X]] with GraphLike[N, E[X], G]](graphCompanion: GraphCompanion[G]): RandomGraph[Int, DiEdge, G]

    Returns a generator for tiny, connected, non-labeled directed graphs with the metrics defined by TinyInt.

  21. def toString(): String
    Definition Classes
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  22. def unDiGraph[N, G[N, E[X] <: EdgeLikeIn[X]] <: Graph[N, E[X]] with GraphLike[N, E[X], G]](graphCompanion: GraphCompanion[G], metrics: Metrics[N])(implicit edgeTag: ClassTag[UnDiEdge[N]], nodeTag: ClassTag[N]): RandomGraph[N, UnDiEdge, G]

    Returns a generator for non-labeled undirected graphs of any metrics and any type.

    Returns a generator for non-labeled undirected graphs of any metrics and any type.

    metrics

    The Metrics to be applied to the generated graph.

  23. final def wait(): Unit
    Definition Classes
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    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit
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    @throws( ... )
  25. final def wait(arg0: Long): Unit
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    @native() @throws( ... )
  26. object SmallInt extends IntFactory

    Predefined metrics of a 'small' graph with the node type of Int, an order of 20 and a node degree range of 2 to 5.

  27. object TinyInt extends IntFactory

    Predefined metrics of a 'tiny' graph with the node type of Int, an order of 5 and a node degree range of 2 to 4.

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