I forgot to mention that 'b' in np.random.randint(0, b, N) is the number of blocks.
Thank you On Wed, Sep 27, 2017 at 8:27 AM, Snehal Shekatkar <[email protected] > wrote: > Hello Tiago, > > I am trying to generate a stochastic block model but with the > degree-sequence preserved. I am fine even if the degree-distribution is > preserved instead of the exact sequence. I tried the following: > > def prob(a, b): > if a == b : > return 0.999 > else: > return 0.001 > > g, bm = gt.random_graph(N, lambda: 1 + np.random.poisson(5), model = > "blockmodel-degree", directed = False, block_membership=np.random.randint(0, > b, N), edge_probs = prob) > > However, this generates an ER graph. What can I do to retain the > block-structure? > > Thank you > -- > Snehal M. Shekatkar > Pune > India > -- Snehal M. Shekatkar Pune India
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