[igraph] Calculating measures for a bunch of ego-networks

[Magnus Torfason]

Hi all,

I have a (relatively sparse) network of 100K nodes in igraph. Each node 
has a bunch of attributes, and the edges have some attributes as well.

I've calculated some standard measures on the nodes (degree, constraint, 
etc) and this has been pretty fast.

However, now I need to calculate some non-standard measures for each 
node, that might theoretically depend on the attributes of:
  - The attributes of the focal vertex
  - The attributes of the edges of the focal vertex
  - The attributes of the vertices in the immediate neighborhood
  - The ties between the neighbors

So this can be accomplished by looping through the vertices of the 
graph, extracting the graph.neighborhood(g, 1, i) for each, and 
manipulating it. However, this takes a long time. Are there any better 
ways for doing stuff like this?

I think I'm kind of hoping that there is a way of writing a function 
that takes a vertex ID, and that this can be "applied" to all the 
vertices of the graph, but in an efficient manner that does not require 
generating 100K subgraphs.

I guess an alternative way of phrasing the question would be: If I 
wanted to implement the constraint measure in R code in an efficient 
manner, could I do it?

Thanks for any help and ideas!

Best,
Magnus