Optimizing function speed on 3D array

Question

I am applying a user-defined function to individual cells of a 3D array. The contents of each cell are one of the following possibilities, all of which are character vectors because of prior formatting:

"N"
"A"
""
"1"
"0"

I want to create a new 3D array of the same dimensions, where cells contain either NA or a numeric vector containing 1 or 0. Thus, I wrote a function named Numericize and used aaply to apply it to the entire array. However, it takes forever to apply it.

Numericize <- function(x){
  if(!is.na(x)){
    x[x=="N"] <- NA; x
    x[x=="A"] <- NA; x
    x[x==""] <- NA; x
    x <- as.integer(x)
  }
  return(x)
}

The dimensions original array are 480x866x366. The function takes forever to apply using the following code:

Final.Daily.Array <- aaply(.data = Complete.Daily.Array,
                           .margins = c(1,2,3),
                           .fun = Numericize,
                           .progress = "text")

I am unsure if the speed issue comes from an inefficient Numericize, an inefficient aaply, or something else entirely. I considered trying to set up parallel computing using the plyr package but I wouldn't think that such a simple command would require parallel processing.

On one hand I am concerned that I created a stack overflow for myself (see this for more), but I have applied other functions to similar arrays without problems.

ex.array <- array(dim = c(3,3,3))

ex.array[,,1] <- c("N","A","","1","0","N","A","","1")
ex.array[,,2] <- c("0","N","A","","1","0","N","A","")
ex.array[,,3] <- c("1","0","N","A","","1","0","N","A")

desired.array <- array(dim = c(3,3,3))

desired.array[,,1] <- c(NA,NA,NA,1,0,NA,NA,NA,1)
desired.array[,,2] <- c(0,NA,NA,NA,1,0,NA,NA,NA)
desired.array[,,3] <- c(1,0,NA,NA,NA,1,0,NA,NA)

ex.array
desired.array

Any suggestions?

Maybe just array(as.numeric(ex.array), dim = dim(ex.array)), because identical(array(as.numeric(ex.array), dim = dim(ex.array)), desired.array) is TRUE. — lukeA
– lukeA, Commented Sep 18, 2017 at 19:10
Thank you for this elegantly simple answer. This approach comes with a warning that NA values are introduced by coercion but that is to be expected based on what goes in and what is expected to come out. — JepsonNomad
– JepsonNomad, Commented Sep 18, 2017 at 19:18
jep, I'd ignore that warning (or rather take note of it, because often times it's valuable). — lukeA
– lukeA, Commented Sep 18, 2017 at 19:20

F. Privé · Accepted Answer · 2017-09-18 21:08:57Z

1

You can just use a vectorized approach:

ex.array[ex.array %in% c("", "N", "A")] <- NA
storage.mode(ex.array) <- "integer"

You can simply use the second line and it will introduce NAs by coercion.

edited Sep 18, 2017 at 21:08

answered Sep 18, 2017 at 20:11

F. Privé

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