Dear Gabor, Can you please send me the binary for igraph 0.6 windows? the previous link provided is returning a code 404 error Regards, Partha Sarathi Das
RA, Bioinformatics Infrastructure Facility, Vidyasagar University, Midnapore, India Mobile : +91 98 31 32 32 32 On Thu, Mar 8, 2012 at 4:02 PM, Wet Bell Diver <[email protected]>wrote: > > Thanks Gabor, that works well. > --Peter > > Op 7-3-2012 19:00, Gábor Csárdi schreef: > > Peter, >> >> you can download a 0.6 windows binary R package here: >> http://win-builder.r-project.**org/Zh7vo2amfgck/<http://win-builder.r-project.org/Zh7vo2amfgck/> >> >> Best, >> Gabor >> >> On Wed, Mar 7, 2012 at 7:36 AM, Wet Bell Diver<[email protected]> >> wrote: >> >>> Dear Tamás and Jeremy, >>> >>> Thanks for your help, both solutions (=the code) work wonderfully. >>> >>> For the solution using igraph directly, I am having trouble installing it >>> into my windows (win7, x64) setup, as the both the command line (R >>> INSTALL >>> etc...) and install.packages("igraph_**nightly_0.6-2646-20120229.tar.**gz", >>> type >>> = "source") give me the error: "ERROR: configuration failed for package >>> 'igraph'" >>> That is a pity, perhaps you have a solution? >>> >>> Apart from that, the code you provide does the trick as well, and I am >>> grateful for that. >>> >>> best, >>> Peter >>> >>> >>> Op 6-3-2012 10:36, Tamás Nepusz schreef: >>> >>> Hello Peter, >>>> >>>> It happens frequently that the same companies engage in multiple deals >>>>> together, but each deal is represented by a line in my data. As a >>>>> result, you see that 'COMP 1' -- 'COMP 2' occurs twice. >>>>> I would like to be able to collapse this to a weighted edge list where >>>>> 'COMP 1' -- 'COMP 2' occurs only once but with value 2, 'COMP 1' -- >>>>> 'COMP 3' occurs only once having value 3, et cetera. >>>>> There must be a very simple way of doing this, but how? >>>>> >>>> I assume that you are using igraph from R. The "simplify" function in >>>> igraph 0.6 will sum up numeric edge attributes when it eliminates >>>> multiple >>>> edges, so I guess the easiest for you is to upgrade to the development >>>> version of igraph (that is, 0.6). Since it has not been released >>>> officially >>>> yet, you can download it from the page of our nightly builds: >>>> >>>> http://code.google.com/p/**igraph/downloads/list<http://code.google.com/p/igraph/downloads/list> >>>> >>>> Download the latest "GNU R source package", and install it in R. If you >>>> happen to use Windows and need a pre-compiled package, let us know - >>>> Gabor >>>> can probably prepare one for you. >>>> >>>> Unfortunately if you cannot upgrade to igraph 0.6 for any reason, then >>>> the >>>> only option is to use count.multiple to find the "multiplicity" of each >>>> edge, and then construct a new graph manually; e.g., like this (not >>>> sure if >>>> there is a simpler solution): >>>> >>>> mul<- count.multiple(g) >>>> df<- as.data.frame(get.edgelist(g)) >>>> df$weight<- cm >>>> g<- graph.data.frame(unique(df)) >>>> >>>> Second, each company has several attributes, including industry. One of >>>>> the things I would like to do is to collapse the entire >>>>> company*company network into a weigted industry*industry network. This >>>>> would reduce the network from approx. 2000*2000 to 40*40. >>>>> How can I construct such a weighted network in igraph? >>>>> >>>> igraph 0.6 will also have a function called contract.vertices which lets >>>> you contract many vertices into a single one, so you could proceed by >>>> first >>>> contracting the vertices by industry using contract.vertices, followed >>>> by >>>> simplify. >>>> >>>> -- >>>> T. >>>> >>> >>> ______________________________**_________________ >>> igraph-help mailing list >>> [email protected] >>> https://lists.nongnu.org/**mailman/listinfo/igraph-help<https://lists.nongnu.org/mailman/listinfo/igraph-help> >>> >> >> >> > ______________________________**_________________ > igraph-help mailing list > [email protected] > https://lists.nongnu.org/**mailman/listinfo/igraph-help<https://lists.nongnu.org/mailman/listinfo/igraph-help> >
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