concepts.benchmark.algorithm_env.graph.random_generate_graph_dnc#

random_generate_graph_dnc(n, p=None, directed=False, np_random=None)[source]#

Random graph generation method as in DNC, the Differentiable Neural Computer paper. Sample $n$ nodes in a unit square. sample out-degree ($m$) of each nodes, connect to $m$ nearest neighbors (Euclidean distance) in the unit square.

Parameters:

• n (int) – the number of nodes in the graph.

• p (float | None) –

  control the range of the sample of out-degree. Default: $[1,n//3]$

  • (float): $[1,int(n\ast p)]$

  • (int): $[1,p]$

  • (tuple): $[p[0],p[1]]$

• directed (bool) – directed or Undirected graph. Default: False (undirected)

• np_random (RandomState | None) – the random state.

Returns:

A randomly generated graph.

Return type:

graph