Re: [graph-tool] Model Selection across Distributions

Am 30.11.20 um 22:39 schrieb Enrique Castaneda: In case I want to simply compare two models with unscaled discrete covariates: one using a geometric distribution and one using a binomial distribution. Can I perform model selection by simply comparing their state.entropy() values? Yes, in the c

Re: [graph-tool] Model Selection across Distributions

Hi Tiago, yes, I mean edge-covariates. In the example you referenced you compare state.entropy() for two distributions, i.e. exponential and log-normal, where for the log-normal model the covariates were scaled, which is handled by subtracting log(g.ep.weight.a).sum(). In case I want to simply co

Re: [graph-tool] get_hierarchy_control_points return values

Ok, but then I should be able to find the edge's target position in the points generated by the the function get_hierarchy_control_points right? If it is not the last two components of the vector (boundary condition?) it should at the position [-4:-3]? If I understand correctly what you said, from

Re: [graph-tool] get_hierarchy_control_points return values

Am 30.11.20 um 19:08 schrieb AntoineR: Ok, that seems right, but still, there is something that I do not understand. I followed the piece of code of the documentation of graph_tool.draw.get_hierarchy_control_points

Re: [graph-tool] get_hierarchy_control_points return values

Ok, that seems right, but still, there is something that I do not understand. I followed the piece of code of the documentation of graph_tool.draw.get_hierarchy_control_points

Re: [graph-tool] get_hierarchy_control_points return values

Am 30.11.20 um 18:38 schrieb AntoineR: Hi Tiago, Sure the documentation states that there should be 6 points, but in my case the length of the map is variable, so I think that either the documentation is outdated, or the format of the map is not correct. Sometimes I have a length of 40 for the ve

Re: [graph-tool] get_hierarchy_control_points return values

Hi Tiago, Sure the documentation states that there should be 6 points, but in my case the length of the map is variable, so I think that either the documentation is outdated, or the format of the map is not correct. Sometimes I have a length of 40 for the vector, sometimes 50 or so. Thanks, A. -

Re: [graph-tool] Model Selection across Distributions

Am 30.11.20 um 10:29 schrieb kicasta: Hi all, I´d have a question regarding model selection with different distributions. When we want to decide the partition that best describes the data for a given distribution we go with that that gives the smallest entropy. However say we want to compare 2 d

Re: [graph-tool] get_hierarchy_control_points return values

Am 25.11.20 um 18:38 schrieb AntoineR: Hi, I would like to know also how the info are formatted... In my case the length of the property is not the same across the edges... The documentation of graph_draw() for "edge_control_points" says: Control points of a Bézier spline used to draw the edge

Re: [graph-tool] mixed-membership SBM in graph-tool?

Am 24.11.20 um 05:34 schrieb sam: hi, i think i understand the difference between the overlapping SBM and mixed-membership SBM (introduced by Airoldi et al, 2009). in MMSBM, a given node can be in multiple blocks, their membership is discrete (0-1) in overlapping SBM, a given node can also be

Re: [graph-tool] How to perform edge contraction?

Am 21.11.20 um 02:25 schrieb jms: Hi, I came across this library looking for an efficiently implemented graph library and it looks awesome. One of the tasks I'd like to perform is efficient edge contraction, where I remove an edge from the graph and merge the two nodes joined by that edge, and th

[graph-tool] Model Selection across Distributions

Hi all, I´d have a question regarding model selection with different distributions. When we want to decide the partition that best describes the data for a given distribution we go with that that gives the smallest entropy. However say we want to compare 2 different distributions d1 and d2 and th