[graph-tool] Re: property map values are not loaded for .graphml graph
Am 28.06.21 um 20:48 schrieb bnikp...@gmail.com:
Hi,
I have saved a graph in Networkx with .graphml format. I can successfully load
the graph in graph-tool and I can see the edge property attached to graph.
However, when I try to access the values I get an error that the property does
not exist.
G =
gt.load_graph('gdrive/MyDrive/ColabNotebooks/Thesis/sources/k4p3-2-test.graphml')
G.properties
{('e',
'_graphml_edge_id'): ,
('e',
'etype'): ,
('v',
'_graphml_vertex_id'): }
e = G.edges().next()
etype[e]
NameError: name 'etype' is not defined
You seem unfamiliar with the Python syntax. In Python, objects need to
be declared before they are used.
The correct way to obtain the property map would have been:
etype = G.ep["etype"]
etype[e]
--
Tiago de Paula Peixoto
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[graph-tool] property map values are not loaded for .graphml graph
Hi,
I have saved a graph in Networkx with .graphml format. I can successfully load
the graph in graph-tool and I can see the edge property attached to graph.
However, when I try to access the values I get an error that the property does
not exist.
G =
gt.load_graph('gdrive/MyDrive/ColabNotebooks/Thesis/sources/k4p3-2-test.graphml')
G.properties
{('e',
'_graphml_edge_id'): ,
('e',
'etype'): ,
('v',
'_graphml_vertex_id'): }
e = G.edges().next()
etype[e]
NameError: name 'etype' is not defined
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[graph-tool] Re: Problem on bipartite-networks with label
Dear Filippo,
This has been fixed in the newest release (2.41), thanks for the bug report.
(In the future, it is enough just to open an issue in the website, as
you did. There is no need to post an additional message to the mailing
list.)
Best,
Tiago
Am 27.06.21 um 09:06 schrieb filippo.va...@edu.unito.it:
I am using [SBMtopicmodeling](https://github.com/martingerlach/hSBM_Topicmodel)
to inference partition on bipartite networks
After a recent graph-tool update I noticed there is a problem with
**state_args** in minimize_nested_blockmodel_dl
step to reproduce:
given a trivial bi-partite network, with VertexProperty **kind** that imposes
the bi-partition
clabel = g.vp['kind']
state_args = {}
state = gt.minimize_nested_blockmodel_dl(g, state_args=state_args)
finds partitions
but when I impose bi-partition
clabel = model.g.vp['kind']
state_args = {'clabel': clabel, 'pclabel': clabel}
state = gt.minimize_nested_blockmodel_dl(g, state_args=state_args)
it fails to find any partition.
What could be the problem?
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--
Tiago de Paula Peixoto
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