I was under the impression that passing a list corresponds to getting the probability that *all* the edges are missing. Indeed, when I try it out I get back a scalar not a np array. I want to collect the probability that each individual edge is missing.
Also, with respect to the heuristics I mention, I just saw this paper "Evaluating Overfit and Underfit in Models of Network Community Structure" use "s_ij = θ_i *θ_ j* l_gi,gj" If sampling is not computationally feasible, this is what I had in mind. 1) Is there a way built into graph-tool to compute this similarity function efficiently? (i.e., without Python slowing me down) 2) Is there a hierarchical analog, like just summing this similarity at each level? Thanks as always On Mon, Mar 23, 2020 at 10:13 AM Tiago de Paula Peixoto <[email protected]> wrote: > Am 19.03.20 um 18:33 schrieb Deklan Webster: > > I'm attempting to use get_edges_prob to find the most likely missing > > edges out of every possible non-edge. I know every possible edge is > O(n^2). > > > > Currently I'm sampling the like this: > > > > non_edges_probs = [[] for _ in range(len(non_edges))] > > > > def collect_edge_probs(s): > > s = s.levels[0] > > > > for i, non_edge in enumerate(non_edges): > > p = s.get_edges_prob([non_edge], [], > > entropy_args=dict(partition_dl=False)) > > non_edges_probs[i].append(p) > > > > gt.mcmc_equilibrate(nested_state, > > force_niter=100, > > mcmc_args=dict(niter=10), > > callback=collect_edge_probs, > > verbose=True) > > > > Is there a way to speed this up at all? If not, is there a heuristic I > > can use to reduce the number of possibilities? > > There is no way to avoid looking at all possibilities, but you could > pass the actual list at once, instead of iterating through it and > passing lists of size 1. The reason get_edges_prob() exists and accepts > lists is precisely to speed things up in this case. > > Best, > Tiago > > -- > Tiago de Paula Peixoto <[email protected]> > > _______________________________________________ > graph-tool mailing list > [email protected] > https://lists.skewed.de/mailman/listinfo/graph-tool >
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