On Thu, Dec 02, 2010 at 01:13:40PM -0800, Aaron Polhamus wrote:
...
> Many thanks for the tips, those solved my queries. Still interested in how
> to force custom functions to work over rows rather than columns when using
> apply,
In the command
TMAT <- apply(MAT, 1, function(X) X/sum(X))
the custom function is applied over rows of MAT, however, when
collecting the obtained (originally) rows to a matrix, they
become columns, due to the following rule from ?apply
If each call to ‘FUN’ returns a vector of length ‘n’, then ‘apply’
returns an array of dimension ‘c(n, dim(X)[MARGIN])’ if ‘n > 1’.
Here, n is the length of the original rows and dim(X)[MARGIN] is
the number of rows of the input matrix. So, the order of the
dimensions gets reversed in this case.
The following demonstrates that apply(t(MAT), 2, ) and apply(MAT, 1, )
produce the same matrix except of a transposition.
MAT <- rbind(
c(5, 3, 1, 6, 7),
c(9, 7, 3, 10, 11),
c(1, 2, 3, 4, 5),
c(2, 4, 6, 8, 10),
c(9, 5, 2, 1, 1)
)
colnames(MAT) <- c("A", "B", "C", "D", "E")
rownames(MAT) <- c("A", "B", "C", "D", "E")
A <- apply(t(MAT), 2, function(X) X/sum(X))
A <- t(A)
B <- apply(MAT, 1, function(X) X/sum(X))
all(A == t(B)) # [1] TRUE
The "dual" command to M / rowSums(M), which divides each element
of a matrix M by the sum of its column, may be done, for example
M <- matrix(1:12, nrow=3)
M1 <- M / rep(colSums(M), each=dim(M)[1])
[,1] [,2] [,3] [,4]
[1,] 0.1666667 0.2666667 0.2916667 0.3030303
[2,] 0.3333333 0.3333333 0.3333333 0.3333333
[3,] 0.5000000 0.4000000 0.3750000 0.3636364
M/M1
[,1] [,2] [,3] [,4]
[1,] 6 15 24 33
[2,] 6 15 24 33
[3,] 6 15 24 33
Alternatively, it is possible to use
sweep(M, 2, colSums(M), FUN="/")
Petr Savicky.
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