[graph-tool] strength and clustering coefficient on weighted digraph
Renato Fabbri
renato.fabbri at gmail.com
Tue Mar 5 10:26:42 CET 2013
Dear Alexandre,
This is one of the .GML files: http://ubuntuone.com/58AiS1hjG62bdNF8kocfmo
2013/3/2 Alexandre Hannud Abdo <abdo at member.fsf.org>:
> On 01-03-2013 22:51, Renato Fabbri wrote:
>> I am not being able to find out how to get the degrees calculated with
>> the weights (i.e. strengths)
>> and I need to get clustering coefficients (i.e. transitivity) for the
>> same kind of graphs, that is,
>> weighted digraphs.
>>
>> Is this possible in graph_tool?
>
> Ni!
> Hi Renato,
>
> If you have weights on a graph, you probably have vertex and edge
> properties encoded in your graphml file.
>
> You can find these properties with:
>
> g.list_properties()
>
> and then access, for example an edge property, with
>
> g.edge_properties["the name you found listed"]
>
> Take a look at the section "Internal property maps" in:
>
> http://projects.skewed.de/graph-tool/doc/graph_tool.html
>
> So that's how you access those weights, and from there you can perform
> your degree calculations however you need.
>
> If the degrees won't change during your processing, you might want to
> store them in a property map for efficiency, instead of recalculating
> them whenever you need the value.
>
> You can create a property map as as explained in the section "Creation
> of new property maps" of that same page.
I think I got it (even beforehand). I could not get the strength in a
direct manner as
I get the degree. I fell that is because I am not understanding something.
>
>
> Regarding the clustering coefficient, could you specify what it is that
> you want to calculate?
frac of numb of closed triads.
>
> Graph-tool provides the two standard clustering measures (local and
> global) plus one extended measure that accounts for larger cycles.
> However none of those incorporate weights. See:
>
> http://projects.skewed.de/graph-tool/doc/clustering.html
>
> The reason is that there is no single or standard way to account for
> weights in the calculation of a clustering coefficient, not to mention
> there is no single way to define clustering for a directed graph.
Thanks. This is valuable information which I believed so but I did not find
a direct reference to.
>
> Which also explains why those other libraries don't do it as well.
Ok. Besides that, there is a clustering coeff for digraphs is Gephi
and graph tool
and they differ.
>
> Clustering is a very unspecific measure, so if you have a specific
> application need, you must first understand why you want to calculate
> some kind of clustering, to then define how, and then implement the
> specific solution your problem calls for.
>
> So if you already have a formal description of what you need, for
> example an article with a mathematical/algorithmic description of the
> specific weighted clustering you want to calculate, you can use
> graph-tool to program that calculation in either python or c++ (a choice
> which will depend on your efficiency needs).
>
> However if you don't know exactly what you need, you must first figure
> that out. There is no such thing as a one-size-fits-all formula for
> "weighted clustering".
Thanks!! Again!
>
>
> Maybe Tiago has better pointers, but I think that covers it.
>
> Feel free to expand your question if I did not fully understand it.
>
> Cheers,
>
> ale
> .~´
>
Cheers. Your detailed and helpful response was very appreciated.
There is more info on what we are doing here:
http://www.wiki.nosdigitais.teia.org.br/ARS
and here:
http://labmacambira.sourceforge.net/redes
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labmacambira.sf.net
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