This documents the development version of NetworkX. Documentation for the current release can be found here.
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.
Number of nodes
Number of edges to attach from a new node to existing nodes with probability \(p\)
Number of edges to attach from a new node to existing nodes with probability \(1-p\)
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.
m2do not satisfy
1 <= m1,m2 < nor
pdoes not satisfy
0 <= p <= 1.
Moshiri “The dual-Barabasi-Albert model”, arXiv:1810.10538.