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# scale_free_graph¶

scale_free_graph(n, alpha=0.41, beta=0.54, gamma=0.05, delta_in=0.2, delta_out=0, create_using=None, seed=None)[source]

Return a scale free directed graph.

Parameters : n : integer Number of nodes in graph alpha : float Probability for adding a new node connected to an existing node chosen randomly according to the in-degree distribution. 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. gamma : float Probability for adding a new node conecgted to an existing node chosen randomly according to the out-degree distribution. delta_in : float Bias for choosing ndoes from in-degree distribution. delta_out : float Bias for choosing ndoes from out-degree distribution. create_using : graph, optional (default MultiDiGraph) Use this graph instance to start the process (default=3-cycle). seed : integer, optional Seed for random number generator

Notes

The sum of alpha, beta, and gamma must be 1.

References

 [R288] B. Bollob{‘a}s, C. Borgs, J. Chayes, and O. Riordan, Directed scale-free graphs, Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms, 132–139, 2003.

Examples

>>> G=nx.scale_free_graph(100)