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Re: [igraph] ID's for nodes/vertices

From: Tamas Nepusz
Subject: Re: [igraph] ID's for nodes/vertices
Date: Mon, 11 Jul 2011 16:32:02 +0200
User-agent: Mozilla/5.0 (X11; U; Linux x86_64; en-US; rv: Gecko/20110516 Lightning/1.0b2 Thunderbird/3.1.10

> Also with the correct code for "similarity inverse log weighted"
> a = i.similarity_inverse_log_weighted(vertices=33,23)
This is definitely not correct Python syntax; you have a positional argument
(23) after a keyword argument (vertices=...) - although this has nothing to
do with the MemoryError of course.

I have just generated a random graph with 20000 vertices and it seems to
work with similarity_inverse_log_weighted, so I don't know what's going on here:

>>> g = Graph.GRG(20000, 0.01)
>>> print g.vcount()
>>> print g.ecount()
>>> a = g.similarity_inverse_log_weighted(vertices=33)
>>> len(a)
>>> len(a[0])

So it seems to work. If you still have problems, please send me your graph
so I can take a look at it.

> Does this function also convert the graph into a matrix like object?
No, it does not. The result will be a list of lists, however, that's why you
shouldn't simply pass all the vertices to the function (because the
resulting matrix would be too large to keep it in memory for a graph with
20K vertices), but it should work if you pass vertices in small batches.


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