I am aware of a post asking for the same topic, but it was dated 2 years
ago, but I wonder if there was any development on this front?
In the function "model.minimize_nested_blockmodel_dl" it is possible to
specify B_min=G and B_max=G in order to get exactly G blocks for the whole
clustering. I wonder if it is possible to specify separately the number of
blocks on each side of the bi-partite network, say G1 for one side of the
network and G2 for the other side? Even maybe by running 2 different
estimations?
I also noticed that Tzu-Chi Yen has an alternative code for this, but I
wonder how comparable it is to graph-tool in terms of efficiency?
I am aware of a post asking for the same topic, but it was dated 2 years
ago, but I wonder if there was any development on this front?
In the function "model.minimize_nested_blockmodel_dl" it is possible to
specify B_min=G and B_max=G in order to get exactly G blocks for the
whole clustering. I wonder if it is possible to specify separately the
number of blocks on each side of the bi-partite network, say G1 for one
side of the network and G2 for the other side? Even maybe by running 2
different estimations?
Unfortunately, this functionality has not been implemented yet.
I also noticed that Tzu-Chi Yen has an alternative code for this, but I
wonder how comparable it is to graph-tool in terms of efficiency?
As you can see for yourself, that implementation is in pure Python,
whereas graph-tool is implemented in C++. Therefore it should be much
slower than graph-tool.