networkx.generators.gaussian_random_partition_graph¶

networkx.generators.gaussian_random_partition_graph(n, s, v, p_in, p_out, directed=False, seed=None)[source]¶

Generate a Gaussian random partition graph.

A Gaussian random partition graph is created by creating k partitions each with a size drawn from a normal distribution with mean s and variance s/v. Nodes are connected within clusters with probability p_in and between clusters with probability p_out[1]

Parameters:	n : int Number of nodes in the graph s : float Mean cluster size v : float Shape parameter. The variance of cluster size distribution is s/v. p_in : float Probabilty of intra cluster connection. p_out : float Probability of inter cluster connection. directed : boolean, optional default=False Whether to create a directed graph or not seed : int Seed value for random number generator
Returns:	G : NetworkX Graph or DiGraph gaussian random partition graph
Raises:	NetworkXError If s is > n If p_in or p_out is not in [0,1]

See also

random_partition_graph

Notes

Note the number of partitions is dependent on s,v and n, and that the last partition may be considerably smaller, as it is sized to simply fill out the nodes [1]

References

[R1034]

Ulrik Brandes, Marco Gaertler, Dorothea Wagner, Experiments on Graph Clustering Algorithms, In the proceedings of the 11th Europ. Symp. Algorithms, 2003.

Examples

>>> G = nx.gaussian_random_partition_graph(100,10,10,.25,.1)
>>> len(G)
100