Delete edge attributes

[GDG]

Hi, with networkx is it possible to delete attributes of edges? Something like

del G.edge[v1][v2][a]

where a is the attribute to be deleted?

Thanks,

G.

[Dan Schult]

Yes, that should work. Also
del G[v1][v2][a]

Be careful with multigraphs though. You need the key of the edge you want to change the attributes for:
del MG[v1][v2][key][a]

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[GDG]

I am getting this error:

Traceback (most recent call last):

  File "../scripts/yed2graphml.py", line 27, in <module>

    del G.edge['n0']['n1']['iteration']

KeyError: 'iteration'

The nodes are 'n0' and 'n1' ; the attributes is 'iteration'.

I am reading the graph from a graphml file (I assume it a multigraph).

G = nx.read_graphml(sys.argv[1])

If I do:

del G.edge['n0']['n1'][0]['iteration']

I get a similar error

Traceback (most recent call last):

  File "../scripts/yed2graphml.py", line 27, in <module>

    del G.edge['n0']['n1'][0]['iteration']

KeyError: 0

Do you have any suggestion?

[Dan Schult]

You should print the attributes to see what they really are (as opposed to what you think they are):
print G.edge['n0']['n1']

[GDG]

Yes. Fixed.

Is there a way to automatically check if an attributes exist for an edge and only in that case proceed with the attribute removal?

[Dan Schult]

attr=G['n0']['n1']
if a in attr:
del attr[a]

[GDG]

Thanks!

[GDG]

I hope that the following will be the last question :P

I am reading my graph from GraphML, the resulting graph can either be or not be a multigraph. In the first case,  I have to use the keys for deleting attributes etc.

G = nx.read_graphml(sys.argv[1])

edge_attributes = ['id', 'iteration']

for ae in edge_attributes:

  for (u, v, k) in G.edges(keys=True):

    ae_list = G.edge[u][v][k]

    if ae in ae_list:

      del G[u][v][k][ae]

If the graph is not a multigraph, the previous code gives an error:

   for (u, v, k) in G.edges(keys=True):

TypeError: edges() got an unexpected keyword argument 'keys'

How can I check if the current graph is or is not a multigraph?

[Aric Hagberg]

You can use G.is_multigraph().
Aric