[graph-tool] Questions about inference algorithms

Tiago de Paula Peixoto tiago at skewed.de
Thu May 19 10:07:51 CEST 2016


On 19.05.2016 09:55, Andrea Briega wrote:
> I have just run a few analysis of the new version of your package and
> my results totally change between v2.13 and v2.16.
>
> Nested_minimize_blockmodel is the one that make most relevant changes
> and it is very difficult to get a biological explanation of the new
> results, mainly at the superior hierarchical levels.

There is nothing fundamental that changed between versions, only a
re-organization of the code.

> I would like to know the particular changes in these two analysis to better understanding of my results. Is it possible to change any parameter to run this function in a similar way to the v2.13? I used to run this function on this way:
>
> state = minimize_nested_blockmodel_dl(g, pclabel=vprop_double, overlap=False, nonoverlap_init=False, deg_corr=True, layers=False)

In that version, the pclabel option did not exist. Note also that
passing all the other options are redundant, since you are using the
default values for them.

> And I have run the new version of the function on this way:
>
> state = minimize_nested_blockmodel_dl(g, state_args=dict(pclabel=vprop_double), overlap=False, nonoverlap_init=False,  deg_corr=True,  layers=False)

The difference here is that pclabel is being used. In the previous
version it was being ignored.

Maybe you should try without the pclabel option, to see if you get
similar results to the ones you got previously. This may help you
understand the difference.

Best,
Tiago

-- 
Tiago de Paula Peixoto <tiago at skewed.de>

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