gt.minimize_blockmodel_dl for directed networks
Hello dear members of the mailing list, I am not sure I am doing the gt.minimize_blockmodel_dl properly, over directed networks. In the plot <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027258/dib_particion_ttt_14.jpg> you can see the yellow nodes 27 and 147 are in the center of the star-like structures. However, with opposite arrows sense. I would expect the same kind of connectivity, then characterized by similar incomming and outcomming connectivity. My instruction is: State = gt.minimize_blockmodel_dl (g2, deg_corr = False, overlap = False) Where the directionality has been already established in the graphml input file. Shall I change any option in the gt.minimize_blockmodel_dl instruction? Thank you very much in advance, Yérali. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.
On 15.06.2017 18:34, yerali wrote:
I am not sure I am doing the gt.minimize_blockmodel_dl properly, over directed networks. In the plot <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027258/dib_particion_ttt_14.jpg> you can see the yellow nodes 27 and 147 are in the center of the star-like structures. However, with opposite arrows sense. I would expect the same kind of connectivity, then characterized by similar incomming and outcomming connectivity.
That is not how the degree-corrected SBM works. It incorporates the (in,out)-degrees as parameters that are independent of the group memberships. See this paper for a discussion of this model and some alternative variations: https://arxiv.org/abs/1205.7009 For this particular network, you might want to consider using the non-degree-corrected model. Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>
Dear Tiago, Thanks for your very fast reply. I am confused about the following. I understand that if I set: deg_corr = False, as I did in the last example, then I am using the non-degree-corrected model, as you suggested. Am I wrong? Thanks again. Best, Yérali. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.
On 15.06.2017 18:59, yerali wrote:
I am confused about the following. I understand that if I set: deg_corr = False, as I did in the last example, then I am using the non-degree-corrected model, as you suggested. Am I wrong?
I'm sorry, I overlooked that. Indeed in this case it might be the result of a bad fit. You should call the function multiple times and use the result with the smallest description length (obtained via state.entropy()). Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>
Thank you very much!!!! All the Best, Yérali. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.
participants (2)
-
Tiago de Paula Peixoto -
yerali