Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

# 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
nint

Number of nodes

m1int

Number of edges to attach from a new node to existing nodes with probability $$p$$

m2int

Number of edges to attach from a new node to existing nodes with probability $$1-p$$

pfloat

The probability of attaching $$m_1$$ edges (as opposed to $$m_2$$ edges)

seedinteger, random_state, or None (default)

Indicator of random number generation state. See Randomness.

Returns
GGraph
Raises
NetworkXError

If m1 and m2 do not satisfy 1 <= m1,m2 < n or p does not satisfy 0 <= p <= 1.

References

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