GraphGenerator

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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6. final def eq(arg0: AnyRef): Boolean

   

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7. def equals(arg0: Any): Boolean

   

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8. def extractSubgraph(size: Int, g: Graph): Graph

   

   Extracts a subgraph of 'size' vertices from graph 'g' by performing a breadth-first search from a random vertex.

   Extracts a subgraph of 'size' vertices from graph 'g' by performing a breadth-first search from a random vertex.

   size

   the number of vertices to extract

   g

   the data graph to extract from

9. def finalize(): Unit

   

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10. def genBFSQuery(size: Int, avDegree: Int, g: Graph): Graph

    

    Given a graph 'g', performs a breadth first search starting at a random vertex until the breadth first tree contains 'size' vertices.

    Given a graph 'g', performs a breadth first search starting at a random vertex until the breadth first tree contains 'size' vertices. At each junction, it chooses a random number of children to traverse, with that random number averaging to 'avDegree'.

    size

    the number of vertices to extract

    avDegree

    the average out degree

    g

    the data graph to extract from

11. def genPowerLawGraph(size: Int, nLabels: Int, maxDegree: Int, distPow: Double): Graph

    

    Generates a graph with power law degree distribution with exponent 'distPow' and uniformly distributed labels.

    Generates a graph with power law degree distribution with exponent 'distPow' and uniformly distributed labels.

    size

    the number of vertices

    nLabels

    the number of labels (distributed uniformly)

    maxDegree

    the maximum allowed degree for any vertex

    distPow

    the power/exponent

12. def genPowerLawGraph_PowLabels(size: Int, nLabels: Int, maxDegree: Int, distPow: Double): Graph

    

    Generates a graph with power law degree distribution with exponent 'distPow' and power law distributed labels.

    Generates a graph with power law degree distribution with exponent 'distPow' and power law distributed labels.

    size

    the number of vertices

    nLabels

    the number of labels (distributed according to power law)

    maxDegree

    the maximum allowed degree for any vertex

    distPow

    the power/exponent

13. def genRandomConnectedGraph(size: Int, nLabels: Int, avDegree: Int): Graph

    

    Generates a random connected graph by using genRandomGraph and checking whether it is connected.

    Generates a random connected graph by using genRandomGraph and checking whether it is connected.

    size

    the number of vertices to generate

    nLabels

    the number of labels (distributed uniformly)

    avDegree

    the average degree

14. def genRandomGraph(size: Int, nLabels: Int, avDegree: Int): Graph

    

    Generates a random graph with the specified size (number of vertices), average degree and labels evenly distributed across vertices from 0 to nLabels - 1.

    Generates a random graph with the specified size (number of vertices), average degree and labels evenly distributed across vertices from 0 to nLabels - 1. Not necessarily a connected graph.

    size

    the number of vertices to generate

    nLabels

    the number of labels (distributed uniformly)

    avDegree

    the average degree

15. def genRandomGraph_PowLabels(size: Int, nLabels: Int, avDegree: Int): Graph

    

    Generates a random graph with labels distributed based on a power law distribution (currently with the magic number 2.1 for the power law exponent).

    Generates a random graph with labels distributed based on a power law distribution (currently with the magic number 2.1 for the power law exponent).

    size

    the number of vertices to generate

    nLabels

    the number of labels (distributed according to power law)

    avDegree

    the average degree

16. final def getClass(): Class[_]

    

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17. def hashCode(): Int

    

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18. final def isInstanceOf[T0]: Boolean

    

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19. final def ne(arg0: AnyRef): Boolean

    

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20. final def notify(): Unit

    

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21. final def notifyAll(): Unit

    

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22. final def synchronized[T0](arg0: ⇒ T0): T0

    

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23. def toString(): String

    

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24. final def wait(): Unit

    

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25. final def wait(arg0: Long, arg1: Int): Unit

    

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26. final def wait(arg0: Long): Unit

    

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