BollobasRiordan (Graphoscope)

Graphoscope

Documentation for 0.5.1-preview.1

BollobasRiordan Type

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

Constructors

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

Static members

Static member	Description
`BollobasRiordan.initDirected (n, alpha, beta, gamma, delta_in, delta_out, create_using)` Full Usage: `BollobasRiordan.initDirected (n, alpha, beta, gamma, delta_in, delta_out, create_using)` Parameters: n : `int` - Number of nodes in graph, integer. alpha : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` - Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` - Bias for choosing nodes from in-degree distribution, float delta_out : `float` - Bias for choosing nodes from out-degree distribution, float create_using : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` - Basis for the graph generation Returns: `'a` A DiGraph	Returns a randomly generated, directed, scale free DiGraph, based on the given paramters. If the given graph has less than 3 vertices, a hard-coded example is used instead. The sum of alpha, beta, and gamma must be 1. n : `int` Number of nodes in graph, integer. alpha : `float` Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` Bias for choosing nodes from in-degree distribution, float delta_out : `float` Bias for choosing nodes from out-degree distribution, float create_using : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` Basis for the graph generation Returns: `'a` A DiGraph
`BollobasRiordan.initDirected (n, alpha, beta, gamma, delta_in, delta_out, create_using)` Full Usage: `BollobasRiordan.initDirected (n, alpha, beta, gamma, delta_in, delta_out, create_using)` Parameters: n : `int` - Number of nodes in graph, integer. alpha : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` - Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` - Bias for choosing nodes from in-degree distribution, float delta_out : `float` - Bias for choosing nodes from out-degree distribution, float create_using : `FGraph<int, int, float>` - Basis for the graph generation Returns: `FGraph<int, int, float>` An FGraph	Returns a randomly generated, directed, scale free FGraph, based on the given paramters. If the given graph has less than 3 vertices, a hard-coded example is used instead. The sum of alpha, beta, and gamma must be 1. n : `int` Number of nodes in graph, integer. alpha : `float` Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` Bias for choosing nodes from in-degree distribution, float delta_out : `float` Bias for choosing nodes from out-degree distribution, float create_using : `FGraph<int, int, float>` Basis for the graph generation Returns: `FGraph<int, int, float>` An FGraph
`BollobasRiordan.initDirectedDiGraph n alpha beta gamma delta_in delta_out create_using` Full Usage: `BollobasRiordan.initDirectedDiGraph n alpha beta gamma delta_in delta_out create_using` Parameters: n : `int` - Number of nodes in graph, integer. alpha : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` - Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` - Bias for choosing nodes from in-degree distribution, float delta_out : `float` - Bias for choosing nodes from out-degree distribution, float create_using : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` - Basis for the graph generation Returns: `'a` A DiGraph	Returns a randomly generated, directed, scale free DiGraph, based on the given paramters. If the given graph has less than 3 vertices, a hard-coded example is used instead. The sum of alpha, beta, and gamma must be 1. n : `int` Number of nodes in graph, integer. alpha : `float` Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` Bias for choosing nodes from in-degree distribution, float delta_out : `float` Bias for choosing nodes from out-degree distribution, float create_using : `DiGraph<'NodeKey, 'NodeData, 'EdgeData>` Basis for the graph generation Returns: `'a` A DiGraph
`BollobasRiordan.initDirectedFGraph n alpha beta gamma delta_in delta_out create_using` Full Usage: `BollobasRiordan.initDirectedFGraph n alpha beta gamma delta_in delta_out create_using` Parameters: n : `int` - Number of nodes in graph, integer. alpha : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` - Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` - Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` - Bias for choosing nodes from in-degree distribution, float delta_out : `float` - Bias for choosing nodes from out-degree distribution, float create_using : `FGraph<int, int, float>` - Basis for the graph generation Returns: `FGraph<int, int, float>` An FGraph	Returns a randomly generated, directed, scale free FGraph, based on the given paramters. If the given graph has less than 3 vertices, a hard-coded example is used instead. The sum of alpha, beta, and gamma must be 1. n : `int` Number of nodes in graph, integer. alpha : `float` Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution, float beta : `float` Probability for adding an edge between two existing nodes. One existing node is chosen randomly according the in-degree distribution and the other chosen randomly according to the out-degree distribution,float gamma : `float` Probability for adding a new node connected to an existing node chosen randomly according to the out-degree distribution, float delta_in : `float` Bias for choosing nodes from in-degree distribution, float delta_out : `float` Bias for choosing nodes from out-degree distribution, float create_using : `FGraph<int, int, float>` Basis for the graph generation Returns: `FGraph<int, int, float>` An FGraph