brainpy.connect.ScaleFreeBA
brainpy.connect.ScaleFreeBA#
- class brainpy.connect.ScaleFreeBA(m, directed=False, seed=None, **kwargs)[source]#
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.
Methods
__init__
(m[, directed, seed])build_conn
()build connections with certain data type.
build_coo
()Build a coo sparse connection data.
build_csr
()Build a csr sparse connection data.
build_mat
()Build a binary matrix connection data.
require
(*structures)Require all the connection data needed.
requires
(*structures)Require all the connection data needed.
Attributes
is_version2_style