assign() for only one sheet of an array - avoid manual change - r

Question

I have some arrays that I will need to fill in. The names of the arrays are variable, but the same functions will happen to them throughout. Basically I need a way to replace only one "sheet" of an array with another without manually entering the array name. Example below:
big_array_1 <- array(dim = c(5,5,10))
big_array_1[,,1] <- sample(c(1:10), 25, replace=T)
big_array_2 <- array(dim = c(5,5,10))
big_array_2[,,1] <- sample(c(40:50), 25, replace=T)
small_array <- array(dim = c(5,5,2))
small_array[,,] <- sample(c(20:30), 50, replace=T)
so each big array will have to have its second sheet (the third dimension) replaced by the second sheet of the small array, but I want to just be able to set a number (i.e. big array "1" or "2") to make this work in my code instead of change the name manually every time.
# So I know I can do this, but I want to avoid manually changing the "_1" to "_2" when I run the script
big_array_1[,,2] <- small_array[,,2]
# instead, I'm hoping I can use a variable and some kind of assign()
arraynumber <- 1
# but this gives an error for assigning a non-language object
get(paste0("big_array_",arraynumber))[,,2] <- small_array[,,2]
# and this gives an error for invalid first argument.
assign(get(paste0("big_array_",arraynumber))[,,2], small_array[,,2])
# even though get(paste0("big_array_",arraynumber))[,,2] works on its own.
Any suggestions?

Answer 1

In R, you cannot assign values to the result of get(). Additionally, it is not advisable to use assign even attach, eval+parse, list2env, and other environment-changing, dynamic methods that tend to be hard to debug.
As commented, simply use named lists for identically structured objects. Lists can contain any object from arrays to data frames to plots without a number limit. Even more, you avoid flooding global environment with separately named objects but work with a handful of lists containing many underlying elements which better manages data for assignment or iterative needs.
Definition
set.seed(8620)
# NAMED LIST OF TWO ARRAYS
big_array_list <- list(big_array_1 = array(dim = c(5,5,10)),
big_array_2 = array(dim = c(5,5,10)))
big_array_list$big_array_1[,,1] <- sample(c(1:10), 25, replace=TRUE)
big_array_list$big_array_2[,,1] <- sample(c(40:50), 25, replace=TRUE)
# NAMED LIST OF ONE ARRAY
small_array_list <- list(small_array_1 = array(sample(c(20:30), 50, replace=TRUE),
dim = c(5,5,2)))
Assignment
# ASSIGN BY FIXED NAME
big_array_list$big_array_1[,,2] <- small_array_list$small_array_1[,,2]
big_array_list$big_array_1[,,2]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 30 29 26 24 23
# [2,] 21 20 22 20 24
# [3,] 27 24 26 30 30
# [4,] 30 26 24 29 25
# [5,] 26 21 26 20 30
# ASSIGN BY DYNAMIC NAME
arraynumber <- 1
big_array_list[[paste0("big_array_",arraynumber)]][,,2] <- small_array_list[[paste0("small_array_",arraynumber)]][,,2]
big_array_list[[paste0("big_array_",arraynumber)]][,,2]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 30 29 26 24 23
# [2,] 21 20 22 20 24
# [3,] 27 24 26 30 30
# [4,] 30 26 24 29 25
# [5,] 26 21 26 20 30
# ASSIGN BY INDEX
big_array_list[[1]][,,2] <- small_array_list[[1]][,,2]
big_array_list[[1]][,,2]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 30 29 26 24 23
# [2,] 21 20 22 20 24
# [3,] 27 24 26 30 30
# [4,] 30 26 24 29 25
# [5,] 26 21 26 20 30
Iterative Needs
# RETURN DIMENSIONS OF EACH big_array
lapply(big_array_list, dim)
# SHOW FIRST 5 ELEMENTS OF EACH big_array
sapply(big_array_list, `[`, 1:5)
# RETURN LIST WHERE ALL big_arrays ARE EQUAL TO small_array
mapply(`<-`, big_array_list, small_array_list, SIMPLIFY=FALSE)