Loop columns of matrix with nested apply - r

Question

I am trying to loop over the columns of a matrix and change certain predefined sequences within the colomns, which are available in form of vectors.
Let's say I have the following matrix:
m2 <- matrix(sample(1:36),9,4)
[,1] [,2] [,3] [,4]
[1,] 11 6 1 14
[2,] 22 16 27 3
[3,] 34 10 23 32
[4,] 21 19 31 35
[5,] 17 9 2 4
[6,] 28 18 29 5
[7,] 20 30 13 36
[8,] 26 33 24 15
[9,] 8 12 25 7
As an example my vector of sequence starts is a and my vector of sequence ends is b. Thus the first sequence to delete in all columns is a[1] to b[1], the 2nd a[2] to b[2] and so on.
My testing code is as follows:
testing <- function(x){
apply(x,2, function(y){
a <- c(1,5)
b <- c(2,8)
mapply(function(y){
y[a:b] <- NA; y
},a,b)
})
}
Expected outcome:
[,1] [,2] [,3] [,4]
[1,] NA NA NA NA
[2,] NA NA NA NA
[3,] 34 10 23 32
[4,] 21 19 31 35
[5,] NA NA NA NA
[6,] NA NA NA NA
[7,] NA NA NA NA
[8,] NA NA NA NA
[9,] 8 12 25 7
Actual result:
Error in (function (y) : unused argument (dots[[2]][[1]])
What is wrong in the above code? I know I could just set the rows to NA, but I am trying to get the above output by using nested apply functions to learn more about them.

Answer 1

We get the sequence of corresponding elements of 'a', 'b' using Map, unlist to create a vector and assign the rows of 'm2' to NA based on that.
m2[unlist(Map(":", a, b)),] <- NA
m2
# [,1] [,2] [,3] [,4]
# [1,] NA NA NA NA
# [2,] NA NA NA NA
# [3,] 34 10 23 32
# [4,] 21 19 31 35
# [5,] NA NA NA NA
# [6,] NA NA NA NA
# [7,] NA NA NA NA
# [8,] NA NA NA NA
# [9,] 8 12 25 7