brainpy.connect.ScaleFreeBA

class brainpy.connect.ScaleFreeBA(m, directed=False, seed=None)

Build a random graph according to the Barabási–Albert preferential attachment model.

A graph of \(num\_node\) nodes is grown by attaching new nodes each with \(m\) edges that are preferentially attached to existing nodes with high degree.

Parameters

• m (int) – Number of edges to attach from a new node to existing nodes

• seed (integer, random_state, or None (default)) – Indicator of random number generation state.

Raises

ConnectorError – If m does not satisfy 1 <= m < n.

References

1

A. L. Barabási and R. Albert “Emergence of scaling in random networks”, Science 286, pp 509-512, 1999.

__init__(m, directed=False, seed=None)

Methods

__init__(m[, directed, seed])
build_conn()	build connections with certain data type.
check(structures)
make_returns(structures, conn_data[, csr, ...])	Make the desired synaptic structures and return them.
require(*structures)
requires(*structures)