Dear James,
Am 23.11.21 um 16:07 schrieb James Ruffle:
Hi Tiago,
Apologies for not being clearer. Let me try and make my example more
specific:
I have a network defined from brain imaging and am passing an edge
weight of a given clinical variable. In this example the nodes are
voxels of brain tissue, the edges are the presence of the voxels being
structurally connected in imaging space, and the edge weight is the
relationship of this to a clinical variable, a weight which incorporates
ageing. I want to firstly derive the community structure, passing the
edge weight, which ultimately gives me clusters of voxels. But, in
addition I want to derive some formulation of a weight for the community
blocks for their relation to the passed edge weight. For instance, in
this example I would want a block which contains voxels within the
hippocampus to be negatively associated to an age weight given atrophy
associated with age, but a block containing voxels of the ventricular
system to be positively associated as they will enlarge with age.
How would you go about doing this?
The seemingly obvious answer is to look at the distribution of edge
covariates on edges incident on the groups. But it is still not very
clear exactly what you want to find.
In any case, this is a question about a particular research problem, so
I don't believe it is appropriate for this list, which is about using
graph-tool.
Best,
Tiago
--
Tiago de Paula Peixoto <ti...@skewed.de>
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