I am wondering if there is a built-in function in R which applies a function to each element of the matrix (of course, the function should be computed based on matrix indices). The equivalent would be something like this:
matrix_apply <- function(m, f) {
m2 <- m
for (r in seq(nrow(m2)))
for (c in seq(ncol(m2)))
m2[[r, c]] <- f(r, c)
return(m2)
}
If there is no such built-in function, what is the best way to initialize a matrix to contain values obtained by computing an arbitrary function which has matrix indices as parameters?
I suspect you want outer
:
> mat <- matrix(NA, nrow=5, ncol=3)
> outer(1:nrow(mat), 1:ncol(mat) , FUN="*")
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 2 4 6
[3,] 3 6 9
[4,] 4 8 12
[5,] 5 10 15
> outer(1:nrow(mat), 1:ncol(mat) , FUN=function(r,c) log(r+c) )
[,1] [,2] [,3]
[1,] 0.6931472 1.098612 1.386294
[2,] 1.0986123 1.386294 1.609438
[3,] 1.3862944 1.609438 1.791759
[4,] 1.6094379 1.791759 1.945910
[5,] 1.7917595 1.945910 2.079442
That yields a nice compact output. but it's possible that mapply
would be useful in other situations. It is helpful to think of mapply
as just another way to do the same operation that others on this page are using Vectorize
for. mapply
is more general because of the inability Vectorize
to use "primitive" functions.
data.frame(mrow=c(row(mat)), # straightens out the arguments
mcol=c(col(mat)),
m.f.res= mapply(function(r,c) log(r+c), row(mat), col(mat) ) )
# mrow mcol m.f.res
1 1 1 0.6931472
2 2 1 1.0986123
3 3 1 1.3862944
4 4 1 1.6094379
5 5 1 1.7917595
6 1 2 1.0986123
7 2 2 1.3862944
8 3 2 1.6094379
9 4 2 1.7917595
10 5 2 1.9459101
11 1 3 1.3862944
12 2 3 1.6094379
13 3 3 1.7917595
14 4 3 1.9459101
15 5 3 2.0794415
You probably didn't really mean to supply to the function what the row() and col() functions would have returned: This produces an array of 15 (somewhat redundant) 3 x 5 matrices:
> outer(row(mat), col(mat) , FUN=function(r,c) log(r+c) )