- class brainpy.connect.ScaleFreeBADual(m1, m2, p, directed=False, seed=None, **kwargs)#
Build a random graph according to the dual Barabási–Albert preferential attachment model.
A graph of :math::num_node 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.
m1 (int) – Number of edges to attach from a new node to existing nodes with probability \(p\)
m2 (int) – Number of edges to attach from a new node to existing nodes with probability \(1-p\)
p (float) – The probability of attaching \(m\_1\) edges (as opposed to \(m\_2\) edges)
seed (integer, random_state, or None (default)) – Indicator of random number generation state.
ConnectorError – If m1 and m2 do not satisfy
1 <= m1,m2 < nor p does not satisfy
0 <= p <= 1.
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.
conn – A binary matrix with the shape
- Return type: