I ran mcmc_equilibrate on a nested block state model in a weighted graph. As
per instructions, I copied the initially computed state in another object
with increased hierarchy depth to 10. However, this fixed the depth to 10.
Everything computed afterwards has depth 10 even if is clear that after 3 or
4 levels the nodes converge to one.
There are many empty branches and when I try to plot it with empty_branches
= False, I get an error stating it is not a tree.
RuntimeError: Invalid hierarchical tree: No path from source to target.
Did anybody perform any similar analyses?
The hierarchy after mcmc_equilibrate:
<NestedBlockState object, with base <BlockState object with 24 blocks (24
nonempty), degree-corrected, with 1 edge covariate, for graph <Graph
object, undirected, with 230 vertices and 11230 edges, edges filtered by
(<PropertyMap object with key type 'Edge' and value type
Graph 0x7fc3a89f1210, at 0x7fc3a64911d0>, False), vertices filtered by
(<PropertyMap object with key type 'Vertex' and value type 'bool',
0x7fc3a89f1210, at 0x7fc3a64912d0>, False) at 0x7fc3a89f1210>, at
0x7fc3a6491950>, and 10 levels of sizes [(230, 24), (24, 5), (5, 1), (1, 1),
(1, 1), (1, 1), (1, 1), (1, 1), (1, 1), (1, 1)] at 0x7fc3a6491590>
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