Ni! Hi Haiko, Do you mean the nested description length as in: NestedBlockState(h, c_nested).entropy() ? .~´ On Fri, Apr 9, 2021 at 4:41 PM Lietz, Haiko <Haiko.Lietz@gesis.org> wrote:

Dear Tiago, all,

I’m happy to have discovered the new partition overlap functionality. It works very nicely. But is it possible to obtain the description length of a nested consensus state?

Getting the description length of the consensus state works fine for an unnested model:

from graph_tool.all import *

h = collection.data['polbooks']

num_models = 2

states = [minimize_blockmodel_dl(h) for i in range(num_models)]

bs = [states[i].get_blocks().a for i in range(num_models)]

c, r = partition_overlap_center(bs)

h_blocks = h.new_vp('int')

h_blocks.a = c

BlockState(h, h_blocks).entropy()

For nested partitions, getting the consensus state is a bit more complicated:

states_nested = [minimize_nested_blockmodel_dl(h) for i in range(num_models)]

bs_nested = []

for j in range(num_models):

l = []

for k in range(len(states_nested[j].get_levels())):

l.append(states_nested[j].get_bstack()[k].vp.b.a)

bs_nested.append(l)

c_nested, r_nested = nested_partition_overlap_center(bs_nested)

But how can I get its description length?

Many thanks for your attention

Haiko

GESIS, Cologne

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