dual_barabasi_albert_graph#

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

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.

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]

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