Consider the following two mode-data:
edgelist:
actor event
1 Sam a
2 Sam b
3 Sam c
4 Greg a
5 Tom b
6 Tom c
7 Tom d
8 Mary b
9 Mary d
Two-Mode Adjacency Matrix:
a b c d
Sam 1 1 1 0
Greg 1 0 0 0
Tom 0 1 1 1
Mary 0 1 0 1
To transform two mode to one mode data, we need a function that transforms the
data like so:
Sam is connected to Greg (via event a)
Sam is connected to Tom (via event b and c)
Sam is connected to Mary (via event b)
Tom is connected to Mary (via event b and d)
OK, now I load my data by executing the following:
###################################################################################
require(igraph)
df <- data.frame(actor =
c('Sam','Sam','Sam','Greg','Tom','Tom','Tom','Mary','Mary'),
event =c('a','b','c','a','b','c','d','b','d') )
g = graph.data.frame(df, directed=F) #Coerce data to igraph object 'g'
#Loading Function two.to.one:
##two.to.one() transforms 2-mode data to 1-mode
two.to.one <- function(g, keep) {
neis <- neighborhood(g, order=2)
neis <- lapply(seq(neis), function(x) neis[[x]][ neis[[x]] != x-1]) ## drop
self-loops
neis <- lapply(neis, function(x) x[ x %in% keep ]) ## keep
only these
neis <- lapply(seq(neis), function(x) t(cbind(x-1, neis[[x]]))) ## create
edge lists
neis[-keep-1] <- NULL ## these
are not needed
neis <- matrix(unlist(neis), byrow=TRUE, nc=2) ## a
single edge list
neis <- neis[ neis[,1] > neis[,2], ] ## count
an edge once only
mode(neis) <- "character"
g2 <- graph.edgelist(neis, dir=FALSE)
V(g2)$id <- V(g2)$name ## 'id' is used in Pajek
g2
}
#Actors are the first 4 verticies, set them to be kept:
keep = V(g)[1:4]
#Convert matrix with two.to.one:
g2 = two.to.one(g, keep)
g2
###################################################################################
This yields the following output:
> g2
Vertices: 4
Edges: 2
Directed: FALSE
Edges:
[0] 3 -- 2
[1] 4 -- 1
But, this can't be right. Here there are only two edges where there should be
four, and if I am inturpreting correctly, the output it is reporting that Tom
is connected to Greg (he is not) and Sam is connected to Mary (which is true).
When I load my function, which is designed to transform a two mode edgelist
(e.g. two columns of data) into a one-mode adjacency matrix it seems to work:
###################################################################################
#load my function
df.to.nxn <- function( x, y ){
# x values will be the N x N values
M <- matrix( nrow = length( unique( x ) ), ncol = length( unique( x ) ),
dimnames = list( unique( x ), unique( x ) ) )
M[ 1:length( unique( x ) ), 1:length( unique( x ) ) ] <- 0
#initialize the values to 0 - this possibly could be removed for illustrative
purposes
for( i in 1:length( x ) ) {
# iterate through rows of data
index = which( y == y[i] )
M[ as.character( x[ index ] ), as.character( x[ index ] ) ] = 1
}
M
# return M, an N x N matrix
}
#Convert matrix
g3 = df.to.nxn(df$actor, df$event)
g4 = graph.adjacency(g3, mode = "undirected", diag = F)
V(g4)$name = row.names(g3)
g4
###################################################################################
This yields:
> g4
Vertices: 4
Edges: 4
Directed: FALSE
Edges:
[0] Sam -- Greg
[1] Sam -- Tom
[2] Sam -- Mary
[3] Tom -- Mary
Which is what we wanted. I have not figured out how to weight edges yet (the
Sam and Tom edge and the Tom and Mary edge should perhaps be weighted at 2
because 'connected twice' -- connected by two events).
-Solomon
________________________________
From: Gabor Csardi [mailto:[EMAIL PROTECTED]
Sent: Wed 5/14/2008 4:01 AM
To: Messing, Solomon O.
Cc: R Help list
Subject: Re: [R] For Social Network Analysis-Graph Analysis - How to convert 2
mode data to 1 mode data?
Please stay on the list.
On Tue, May 13, 2008 at 06:05:15PM -0400, Messing, Solomon O. wrote:
> Gabor,
>
> By the way, this seems to work:
I'm a bit lost. So now you're converting your data frame
to a matrix? Why? Or you're doing the two-mode to one-mode
conversion here? It does not seem so to me.
Btw. there is a get.adjacency function in igraph to convert
a graph to an adjacency matrix.
G.
>
> df.to.nxn <- function( x, y ){
> # x values will be the N x N values
> M <- matrix( nrow = length( unique( x ) ), ncol = length( unique( x
> ) ),
> dimnames = list( unique( x ), unique( x ) ) )
> M[ 1:length( unique( x ) ), 1:length( unique( x ) ) ] <- 0
> # initialize the values to 0
> for( i in 1:length( x ) ) {
> # iterate through rows of data
> index = which( y == y[i] )
> M[ as.character( x[ index ] ), as.character( x[ index ]
> ) ] = 1
> }
> M
> # return M, an N x N matrix
> }
--
Csardi Gabor <[EMAIL PROTECTED]> UNIL DGM
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