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networkx.generators.random_graphs.dual_barabasi_albert_graph

dual_barabasi_albert_graph(n, m1, m2, p, seed=None)

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.

Returns:

G

Return type:

Graph

Raises:

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.