R Subsetting nested lists, select multiple entries - r

Question

I frequently work with large datasets, resulting in me creating nested lists sometimes to reduce the objects in the environment.
When subsetting such a list and wanting to go to the first entry along all steps, it would look like this:
llra[[1]][[1]][[1]]
In some of my current scripts the data in these scripts are aligned to that each of the entries of the last step down the list are comparable. If I would like to compare these or make a calculation it would look something like this:
mean(llra[[1]][[1]][[1]], llra[[1]][[2]][[1]], llra[[1]][[3]][[1]])
Is there a way to subset them differently so I could write it something like this:
mean(llra[[1]][[c(1:3)]][[1]])
Thanks for your help!

Answer 1

You can use purrr::map.
mean(map_dbl(1:3, ~llra[[1]][[.x]][[1]]))

Answer 2

Create a small helper function. This creates a grid of indexes and extracts each one. Finally it unlists the result. No packages are used.
unravel <- function(L, ...) {
if (...length()) L <-
apply(expand.grid(...), 1, function(ix) L[[ix]], simplify = FALSE)
unlist(L)
}
# test
L <- list(a = list(b = list(1:3, 4:5), c = list(11:12, 20:25)))
# Example 1
mean(unravel(L, 1, 1:2, 1))
## [1] 5.8
# check
mean(c(L[[1]][[1]][[1]], L[[1]][[2]][[1]]))
## [1] 5.8
# Example 2
mean(unravel(L, 1, 1, 1:2))
## [1] 3
# check
mean(c(L[[1]][[1]][[1]], L[[1]][[1]][[2]]))
## [1] 3
Update
Generalize unravel so that it does not assume three levels or which level(s) are specified as scalar or vector indices.

Answer 3

Thank you for your answers, both Grothendieck's and Novotny's approaches work.
I simplified my example and since I am using raster layers in the last step of the list I made it work like this:
unravel method:
mean(stack(unravel(llra, 1, 1:3,1)))
map method:
mean(stack(map(1:3, ~llra[[1]][[.x]][[1]])))
It seems like a basic thing, strange that this isn't implemented in R yet.