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# networkx.generators.random_graphs.dual_barabasi_albert_graph¶

dual_barabasi_albert_graph(n, m1, m2, p, seed=None)[source]

Returns a random graph according to the dual Barabási–Albert preferential attachment model.

A graph of $$n$$ nodes is grown by attaching new nodes each with either $$m_1$$ edges (with probability $$p$$) or $$m_2$$ edges (with probability $$1-p$$) that are preferentially attached to existing nodes with high degree.

Parameters: n (int) – Number of nodes m1 (int) – Number of edges to attach from a new node to existing nodes with probability $$p$$ m2 (int) – Number of edges to attach from a new node to existing nodes with probability $$1-p$$ p (float) – The probability of attaching $$m_1$$ edges (as opposed to $$m_2$$ edges) seed (integer, random_state, or None (default)) – Indicator of random number generation state. See Randomness. G Graph NetworkXError – If m1 and m2 do not satisfy 1 <= m1,m2 < n or p does not satisfy 0 <= p <= 1.

References

 [1] Moshiri “The dual-Barabasi-Albert model”, arXiv:1810.10538.