Applying a matrix to a function [duplicate]

Question

Trying to apply a matrix to a function, using mapply without success

I'm trying to solve a set of equations for different parameters. In a more simplistic form of the set of functions, I'm trying to pass a function to a matrix - constants -

     a b c
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9

and trying to solve the the equation 3*a + 2*b + 3*c and return the answer for each row in the matrix. I have changed the original function to a linear and more simple one - that is why I prefer using #mapply and that former explanations have not assisted me.

building the matrix

my_vector <- 1:9
constants <- matrix(my_vector, 3, 3)
colnames(constants) <- c("a", "b", "c")
constants

the target function

fun_abc <- function(a, b, c){
  return(3 * a + 2 * b + 3 * c)
}

applying constants to the function

mapply(fun_abc, 2, constants)

I keep getting Error in (function (a, b, c) : argument "c" is missing, with no default Can anyone spot the problems?

Answer 1

You can directly multiply values and take rowSums to get row-wise sum

vals <- c(3, 2, 3)
rowSums(t(t(constants) * vals))
#[1] 32 40 48

We use transpose since constants * vals would multiply vals in each column, so the first transpose is to multiply vals row-wise and the second transpose is to get matrix in original format again. If we would always have a square matrix (nrow == ncol), we can reduce one transpose and use colSums instead to get the same value.

colSums(t(constants) * vals)
#[1] 32 40 48

---

If we want to avoid transposing we can also use sweep

rowSums(sweep(constants, 2, vals, `*`))

Answer 2

One simple way to do this using matrix multiplication, and then changing it to vector if you want so:

my_vector <- 1:9
constants <- matrix(my_vector, 3, 3)
colnames(constants) <- c("a", "b", "c")
vals <- c(3, 2, 3)

c(constants %*% vals)
#> [1] 32 40 48

---

Or, redefine your function and use apply:

fun_x <- function(x){
  sum(x * vals) # same as 3 * x[1] + 2 * x[2] + 3 * x[3]
}

apply(constants, 1, fun_x)