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Graph measures

Using SparklingGraph you can utilize multiple well-known measures for graphs.

Graph measures API

Graph measures

Each graph mesure extends GraphMeasure trait, defining what kind of value will be returned for whole graph.

Vertex measures

Each vertex mesure extends VertexMeasure trait, defining what kind of value will be returned for each vertex. For main part of measures that will be a single number (like Double) but for some of them a tupple (or other data type) can be returned (like (Double,Double)). Each measure defines also implicit methods for graph, thanks to what your code will be more readable, and you will develop your experiments faster.

Measures accepts VertexMeasureConfiguration in order to configure computation process. You can set following parameters:

  • BucketSizeProvider - used in more complex computations in order to divide data into buckets
  • treatAsUndirected:Boolean - graph will be treated as undirected during computations

Edges measures

Each edge mesure extends EdgeMeasure trait, defining what kind of value will be returned for each edge, and what kind of data is expected for each vertex. Each measure defines also implicit methods for graph, thanks to what your code will be more readable, and you will develop your experiments faster.

Measures accepts parameters:

  • treatAsUndirected:Boolean - graph will be treated as undirected during computations

Beside defining methods for computing measure for whole graph, method (computeValues) for single edge is also present.

Measures

Curretnly you can use following measures:

  • Vertex measures:

    .. toctree::
       :maxdepth: 2
    
       closeness
       eigenvector
       hits
       degree
       neighborhoodConnectivity
       vertexEmbeddedness
       localClustering
    
    
    
  • Graph measures:

    .. toctree::
       :maxdepth: 2
    
       freeman
       modularity
    
    
  • Edges measures:

    .. toctree::
       :maxdepth: 2
    
       adamic
       commonneighbours
    
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