, s, v, p_in, p_out, directed=False, seed=None)[source]#

Generate a Gaussian random partition graph.

A Gaussian random partition graph is created by creating k partitions each with a size drawn from a normal distribution with mean s and variance s/v. Nodes are connected within clusters with probability p_in and between clusters with probability p_out[1]

  • n (int) – Number of nodes in the graph

  • s (float) – Mean cluster size

  • v (float) – Shape parameter. The variance of cluster size distribution is s/v.

  • p_in (float) – Probabilty of intra cluster connection.

  • p_out (float) – Probability of inter cluster connection.

  • directed (boolean, optional default=False) – Whether to create a directed graph or not

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


G – gaussian random partition graph

Return type:

NetworkX Graph or DiGraph


NetworkXError – If s is > n If p_in or p_out is not in [0,1]


Note the number of partitions is dependent on s,v and n, and that the last partition may be considerably smaller, as it is sized to simply fill out the nodes [1]


>>> G = nx.gaussian_random_partition_graph(100, 10, 10, 0.25, 0.1)
>>> len(G)