graph-theory

Discussed in networkx/networkx#4918

There are Four Centrality Measures not found in NetworkX, Leverage Centrality, Bridging Centrality, Laplace Centrality, and Communicability. It would be useful if there are guides on including these into NetworkX.

def Leverage_Centrality(g):
    DegreeI = g.degree(nbunch = i)
    NeighboorsI = [n for n in g.neighbors(i

Basically we're in the DAG, so make sure we've let all the other resources (like files) get built (that might be used for the file server) before the server sends anything out. We could either block or just not return anything yet.

As an aside, does the rf.ReadFrom bit not get cancelled properly on close??

I have a gh graph on 37700 vertices and 289003 edges.

Calculation of its diameter like this:

maximum(maximum(gdistances(gh, i)) for i in vertices(gh))

takes around 250 seconds (probably this is not an optimal algorithm for the task but at least it works).

However, when I run diameter(gh) the process takes so long that I did not wait till it finished.

Hi,

It would be nice to have the capability to expand/collapse nodes similar to https://github.com/iVis-at-Bilkent/cytoscape.js-expand-collapse.

Thanks.

Following up with #603 (the improved Quickstart tutorial) as an example all tutorials could use a bit more "story" in the future.

@bburns632 @jayqi it's been a bit over a year since we did a release to CRAN. Want to do one?

I found myself using {pkgnet} this week to prep for a talk, and I really wanted the features from uptake/pkgnet#243, which I realize now never made it to CRAN.

If you're open to spending a little time on {pkgnet}, I'd also be happy to submit PRs for the warnings on https