Hi, > print list(graph.vs.select(top_indices)) # Why does this not work and return > []?
It looks like the select() method does not play nicely with NumPy data types, and top_indices is a NumPy array at this point. You can work around the issue by converting it back to a list: >>> top_indices = top_indices.tolist() FWIW, if you are using NumPy only to find the top elements in pr_scores, there’s no need to do that, this would suffice: from heapq import nlargest from operator import itemgetter [...] top_indices, _ = zip(*nlargest(10, enumerate(pr_scores), key=itemgetter(1))) If your graph is (relatively) small, you can also rely on sorted(); the above solution is better in the sense that it does not do a full sort (it builds a heap only and extracts the top 10 elements from the heap). The solution with sorted() would be: top_indices = sorted(range(len(pr_scores)), key=pr_scores.__getitem__, reverse=True)[:10] > for i in top_indices: > print i, focal_subgraph_directed.vs.select(i) # Why does this throw: > invalid vertex filter among positional arguments The elements of a NumPy array are not ordinary Python integers but NumPy datatypes (they are numpy.int64 in your case), and they also do not play nicely with igraph yet :( You can cast them to an integer explicitly. I will try to fix these issues in the next release. All the best, Tamas _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
