Re: [igraph] average neighbors' degree on bipartite networks

[Simone Gabbriellini]

Hi Gabor,

thanks for the info, I got the logic... still have a difficult with
basic R commands, I suppose, because I don't know how to filter two
lists of lists, i.e. the result of neighborhood():

nei1<-neighborhood(g, 1, V(g)[which(V(g)$type==FALSE)])
nei2<-neighborhood(g, 2, V(g)[which(V(g)$type==FALSE)])

then I tried:

V(g)[which(V(g)$type==FALSE)]$nei2<-nei2[which(nei2!=nei1)]

or

V(g)[which(V(g)$type==FALSE)]$nei2<-lapply(nei2, setdiff, nei1)

with no success... tried to google it, but no luck either... If you
have suggestions, I'll be happy to hear...

Best,
Simone

2013/1/31 Gábor Csárdi <address@hidden>:
> Hi Simone,
>
> On Thu, Jan 31, 2013 at 11:14 AM, Simone Gabbriellini
> <address@hidden> wrote:
>>
>> Hello List,
>>
>> I have a question regarding graph.knn() if applied on bipartite
>> networks. When I calculate this:
>>
>> graph.knn(g, V(g)[type==FALSE])
>>
>> $knn
>>      u43      u62       u9      u17      u19     u102     u127
>> u142      u64     u137
>> 3.750000 4.250000 4.181818 4.571429 5.600000 5.200000 6.000000
>> 5.333333 5.166667 6.000000
>
> [...]
>
>>
>> what these numbers represents? for each node of set1, I have the
>> average degree of the nodes in set2?
>
>
> The average degree of the neighbors of the node. Since your graph is
> bipartite, yes, all these neighbors are in set 2.
>
>>
>> if yes, is it possible to extend
>> this concept to check for the average degree of dist-2 neighbors -
>> i.e. nodes still belonging to set1?
>
>
> Yes, but this is not in igraph and you need to code it for yourself,
> probably using neighborhood() is easiest. For bipartite graphs it might be
> very easy, actually, because all you need to do for a vertex in set 1 is
> taking an order 2 neighborhood, and then removing all vertices from set 2
> (first neighbors) and the maybe the node itself, and you end up with the
> dist-2 neighbors.
>
> G.
>
>>
>>
>> Many thanks,
>> Simone
>>
>>
>> --
>> Simone Gabbriellini, PhD
>>
>> address@hidden, University of Bologna
>> mobile: +39 340 39 75 626
>> email: address@hidden
>> home: www.digitaldust.it
>>
>> DigitalBrains srl
>> Amministratore
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>>
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>
>
>
>
> --
> Gabor Csardi <address@hidden>     MTA KFKI RMKI
>
> _______________________________________________
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>



-- 
Simone Gabbriellini, PhD

address@hidden, University of Bologna
mobile: +39 340 39 75 626
email: address@hidden
home: www.digitaldust.it

DigitalBrains srl
Amministratore
mobile: +39 340 39 75 626
email: address@hidden
home: www.digitalbrains.it