dual_barabasi_albert_graph

dual_barabasi_albert_graph(n, m1, m2, p, seed=None, initial_graph=None, *, create_using=None)

Returns a random graph using dual Barabási–Albert preferential attachment

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 link each new node to existing nodes with probability \(p\)

m2int

Number of edges to link each 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.

initial_graphGraph or None (default)

Initial network for Barabási–Albert algorithm. A copy of initial_graph is used. It should be connected for most use cases. If None, starts from an star graph on max(m1, m2) + 1 nodes.

create_usingGraph constructor, optional (default=nx.Graph)

Graph type to create. If graph instance, then cleared before populated. Multigraph and directed types are not supported and raise a NetworkXError.

Returns:

GGraph

Raises:

NetworkXError

If m1 and m2 do not satisfy 1 <= m1,m2 < n, or p does not satisfy 0 <= p <= 1, or the initial graph number of nodes m0 does not satisfy m1, m2 <= m0 <= n.

References

[1]

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