This is my first post =)
To begin with - what an awesome package! The website is great, the docs are
amazing, the code is beautiful, sane autotools usage, very fast, pythonic!
Best software package ever!
I'm a beginner in graph theory. Any suggestions on books/tutorials which
can quickly take me from basics to advanced topics would be appreciated.
Now the question.
I'm doing numerical simulation over a veronoi graph. I'm storing data on
the vertexes and edges. The iterations go as following:
1) Using data on the edges ('incident pulses') I'm calculating the value of
the vertex ('node voltage')
2) Using value of the vertex, I'm calculating new values for the edges
3) During next timestep scattered pulses become incident - repeat
In the future I may need to use symmetric directed graph and do more fun
things with incident and scattered pulses.
Now the slight problem arrises, when my graph + values is bigger than I can
store in RAM.
There is Global Arrays toolkit, which recently got GAiN (Global Arrays in
Numpy) which allow seamlessly use numpy/scipy over shared memory cluster.
But it will give good performance if arrays are exercising data locality
In my case I want property maps of vertixes & edges to be 'near each other'
based on connectivity. Such that my algorithm computes as many
vertexes/edges locally as possible. E.g. for a 2D latice I'm using
Now I want something similar but for veronoi diagram.
I'm not familiar with graph theory, but I was playing around with
graph-tool and it seems like betweenness and/or communities give me
something what I want. Ideally I want to retrieve indexes which will sort
PropertyMap to exhibit data locality properties (Similar to Z-order curve).
Does graph-tool already does something like this?
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