Re: [graph-tool] Use of edge's weights in model inference

On 15.11.2016 19:24, Andrea Briega wrote:

The edge's weights are integers

In this case, you should just pass the property map with the weights as the "eweight" parameter, e.g.

state = minimize_nested_blockmodel_dl(g,state_args=dict(eweight=weights))

Best, Tiago

2016-11-15 18:17 GMT+01:00 Andrea Briega <annbrial@gmail.com mailto:annbrial@gmail.com>:

Dear Dr. Tiago Peixoto, 

I have a question regarding weighted graphs. I would like to classify a
network with weighted edges into groups taking into account these
weights. I have used minimize_blockmodel_dl and
minimize_nested_blockmodel_dl before but I don't know exactly how to
implement these functions in a weighted network. I'm not sure if I have
to use the layered version, but in this case I don't know how to get
these layers from my network.

Thank you very much and sorry for the basic question,

Andrea

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