### Navigation

- index
- modules |
- modules |
- next |
- previous |
- FNSS 0.6.0 documentation »
- API Reference »
- Functions »

# fnss.topologies.randmodels.extended_barabasi_albert_topology

`extended_barabasi_albert_topology`(n, m, m0, p, q, seed=None)

  Return a random topology using the extended Barabasi-Albert preferential attachment model.

  Differently from the original Barabasi-Albert model, this model takes into account the presence of local events, such as the addition of new links or the rewiring of existing links.

  More precisely, the Barabasi-Albert topology is built as follows. First, a topology with m0 isolated nodes is created. Then, at each step: with probability p add m new links between existing nodes, selected with probability:

  with probability q rewire m links. Each link to be rewired is selected as follows: a node i is randomly selected and a link is randomly removed from it. The node i is then connected to a new node randomly selected with probability , with probability add a new node and attach it to m nodes of the existing topology selected with probability

  Repeat the previous step until the topology comprises n nodes in total.

  Parameters: | n : int Number of nodes m : int Number of edges to attach from a new node to existing nodes m0 : int Number of edges initially attached to the network p : float The probability that new links are added q : float The probability that existing links are rewired seed : int, optional Seed for random number generator (default=None).
  Returns: | G : Topology

  References

  [R21] | A. L. Barabasi and R. Albert “Topology of evolving networks: local events and universality”, Physical Review Letters 85(24), 2000.

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- FNSS 0.6.0 documentation »
- API Reference »
- Functions »