BarabasiAlbert (Graphoscope)

Graphoscope

Documentation for 0.5.1-preview.1

BarabasiAlbert Type

Namespace: Graphoscope.RandomModels
Assembly: Graphoscope.dll
Base Type: obj

Constructors

Constructor	Description
`BarabasiAlbert()` Full Usage: `BarabasiAlbert()` Returns: `BarabasiAlbert`	Returns: `BarabasiAlbert`

Static members

Static member	Description
`BarabasiAlbert.init (numberOfVertices, numberOfEdgesPerIteration, fVertexKey, fLabel, fWeight, startingGraph)` Full Usage: `BarabasiAlbert.init (numberOfVertices, numberOfEdgesPerIteration, fVertexKey, fLabel, fWeight, startingGraph)` Parameters: numberOfVertices : `int` - specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` - specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` - is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` - is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` - is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` - is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `'a` A DiGraph	Returns a DiGraph that was randomly grown according to the Barabási–Albert model with the given parameters. numberOfVertices : `int` specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `'a` A DiGraph
`BarabasiAlbert.init (numberOfVertices, numberOfEdgesPerIteration, fVertexKey, fLabel, fWeight, startingGraph)` Full Usage: `BarabasiAlbert.init (numberOfVertices, numberOfEdgesPerIteration, fVertexKey, fLabel, fWeight, startingGraph)` Parameters: numberOfVertices : `int` - specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` - specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` - is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` - is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` - is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `FGraph<int, int, float>` - is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `FGraph<int, int, float>` An FGraph	Returns an FGraph that was randomly grown according to the Barabási–Albert model with the given parameters. numberOfVertices : `int` specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `FGraph<int, int, float>` is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `FGraph<int, int, float>` An FGraph
`BarabasiAlbert.initDiGraph numberOfVertices numberOfEdgesPerIteration fVertexKey fLabel fWeight startingGraph` Full Usage: `BarabasiAlbert.initDiGraph numberOfVertices numberOfEdgesPerIteration fVertexKey fLabel fWeight startingGraph` Parameters: numberOfVertices : `int` - specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` - specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` - is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` - is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` - is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` - is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `'a` A DiGraph	Returns a DiGraph that was randomly grown according to the Barabási–Albert model with the given parameters. numberOfVertices : `int` specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `'a` A DiGraph
`BarabasiAlbert.initFGraph numberOfVertices numberOfEdgesPerIteration fVertexKey fLabel fWeight startingGraph` Full Usage: `BarabasiAlbert.initFGraph numberOfVertices numberOfEdgesPerIteration fVertexKey fLabel fWeight startingGraph` Parameters: numberOfVertices : `int` - specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` - specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` - is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` - is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` - is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `FGraph<int, int, float>` - is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `FGraph<int, int, float>` An FGraph	Returns an FGraph that was randomly grown according to the Barabási–Albert model with the given parameters. numberOfVertices : `int` specifies how many additional vertices the final graph will have. numberOfEdgesPerIteration : `int` specifies how many edges should be added to the graph per iteration. fVertexKey : `int -> int` is a function that is used to transform an integer (the index of the vertex) into the 'Vertex type. fLabel : `int -> int` is a function that transforms the 'Vertex type into a label of the 'Label type. fWeight : `int * int -> float` is a funtion that takes two 'Vertices and returns a weight between them in form of an 'Edge type. startingGraph : `FGraph<int, int, float>` is the original graph, that is used as the initial connected network. The rest of the calculations and growth of the network are performed on this graph. Returns: `FGraph<int, int, float>` An FGraph
`BarabasiAlbert.initUndirected nodesToAdd m` Full Usage: `BarabasiAlbert.initUndirected nodesToAdd m` Parameters: nodesToAdd : `int` - specifies how many additional vertices the final graph will have. m : `int` - specifies how many edges should be added to the graph per iteration. Returns: `UndirectedGraph<int, int, float>`	Returns an UndirectedGraph that was randomly grown according to the Barabási–Albert model with the given parameters. nodesToAdd : `int` specifies how many additional vertices the final graph will have. m : `int` specifies how many edges should be added to the graph per iteration. Returns: `UndirectedGraph<int, int, float>`