ScaleFreeBA

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

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.

build_mat(isOptimized=True)

Build a binary matrix connection data.

If users want to customize their connections, please provide one of the following functions:

• build_mat(): build a matrix binary connection matrix.

• build_csr(): build a csr sparse connection data.

• build_coo(): build a coo sparse connection data.

• build_conn(): deprecated.

Returns:

conn – A binary matrix with the shape (num_pre, num_post).

Return type:

Array