Dear all, I am wondering how exactly the k-core decomposition for directed network is defined in graph-tool. With the following network: Gt = gt.Graph(directed=True) Gt.add_edge_list([(1, 0),(2, 0),(2, 1),(3, 1),(3, 0),(4, 0),(4, 1),(5, 1), (5, 0),(6, 0),(6, 1),(7, 4),(7, 0),(8, 3),(8, 0),(9, 0), (9, 2),(10, 2),(10, 3),(11, 2),(11, 3),(12, 5),(12, 3), (13, 2),(13, 12),(14, 11),(14, 0)]) The k-core decomposition is: print(gt.kcore_decomposition(Gt, 'in').a)

...

...

[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]

print(gt.kcore_decomposition(Gt, 'out').a)

...

...

[10 5 4 4 1 1 0 0 0 0 0 1 1 0 0]

print(gt.kcore_decomposition(Gt, 'total').a)

...

...

[2 2 2 2 2 2 2 2 2 2 2 2 2 2 2]

I don't understand the results for the out-k-core. The same analysis in igraph (using shell_index()) gives: in-core : [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] out-core : [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] total : [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2] Looking at the source code of kcore_decomposition, it looks like when deg=='out', the decomposition is done on the reversed network, but still using the out-degree. Is it normal? I am a bit confused. Thanks, Alex