Preserve names when coercing vector from binary to `as.numeric`? - r

Question

In R, when you coerce a vector from binary to numeric, the names are stripped away.
There are a few possible solutions, which I've outlined before. It seems dangerous to rely on implicit conversion by adding 0 to all the values, and the sapply() adds an additional loop to my operations (which seems inefficient). Is there any other way to preserve the names when converting a vector using as.numeric?
# Set the seed
set.seed(1045)
# Create a small sample vector and give it names
example_vec <- sample(x = c(TRUE,FALSE),size = 10,replace = TRUE)
names(example_vec) <- sample(x = LETTERS,size = 10,replace = FALSE)
example_vec
# Y N M P L J H O F D
# FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
as.numeric(x = example_vec)
# [1] 0 1 0 0 1 1 1 1 1 1
example_vec + 0
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1
sapply(X = example_vec,FUN = as.numeric)
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1

Answer 1

One possibility is to use the mode<- replacement function to change the internal storage mode (type) of the object. Also, integers are more appropriate than doubles (i.e. numerics) for this case of logical coercion.
mode(example_vec) <- "integer"
example_vec
# Y N M P L J H O F D
# 0 1 0 0 1 1 1 1 1 1
From help(mode) -
mode(x) <- "newmode" changes the mode of object x to newmode. This is only supported if there is an appropriate as.newmode function, for example "logical", "integer", "double", "complex", "raw", "character", "list", "expression", "name", "symbol" and "function". Attributes are preserved.
The documentation also notes that storage.mode<- is a more efficient primitive version of mode<-. So the following could also be used.
storage.mode(example_vec) <- "integer"
But as #joran pointed out in the comments, it looks like class<- also does the same thing.

Answer 2

Just to throw another option out there, since your input is a logical vector, you can use ifelse(). And one could argue this approach is more explicit and straightforward:
ifelse(example_vec,1L,0L);
## Y N M P L J H O F D
## 0 1 0 0 1 1 1 1 1 1
Benchmarking
library(microbenchmark);
ifelse. <- function(x) ifelse(x,1L,0L);
sapply. <- function(x) sapply(x,as.integer);
setstoragemode <- function(x) { storage.mode(x) <- 'integer'; x; };
setmode <- function(x) { mode(x) <- 'integer'; x; };
setclass <- function(x) { class(x) <- 'integer'; x; };
as.and.setnames <- function(x) setNames(as.integer(x),names(x));
plus <- function(x) +x;
addzero <- function(x) x+0L;
## small scale (OP's example input)
set.seed(1045L);
x <- sample(c(T,F),10L,T);
names(x) <- sample(LETTERS,10L);
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x));
## Unit: nanoseconds
## expr min lq mean median uq max neval
## ifelse.(x) 6843 8126.0 9627.13 8981 9837.0 21810 100
## sapply.(x) 18817 20100.5 23234.93 21383 22666.5 71418 100
## setstoragemode(x) 856 1283.0 1745.54 1284 1711.0 15396 100
## setmode(x) 7270 8126.0 9862.36 8982 10264.0 32074 100
## setclass(x) 429 1283.0 2138.97 1284 1712.0 32075 100
## as.and.setnames(x) 1283 1711.0 1997.78 1712 2139.0 7271 100
## plus(x) 0 428.0 492.39 428 428.5 9837 100
## addzero(x) 0 428.0 539.39 428 856.0 2566 100
## large scale
set.seed(1L);
N <- 1e5L;
x <- sample(c(T,F),N,T);
names(x) <- make.unique(rep_len(LETTERS,N));
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x));
## Unit: microseconds
## expr min lq mean median uq max neval
## ifelse.(x) 7633.598 7757.1900 16615.71251 7897.4600 29401.112 96503.642 100
## sapply.(x) 86353.737 102576.0945 125547.32957 123909.1120 137900.406 264442.788 100
## setstoragemode(x) 84.676 92.8015 343.46124 98.3605 113.543 23939.133 100
## setmode(x) 124.020 155.0245 603.15744 167.2125 181.111 22395.736 100
## setclass(x) 85.104 92.3740 328.25393 100.2850 118.460 21807.713 100
## as.and.setnames(x) 70.991 78.2610 656.98177 82.3235 88.953 35710.697 100
## plus(x) 40.200 42.9795 48.68026 44.9040 49.608 88.953 100
## addzero(x) 181.326 186.4580 196.34882 189.6650 201.211 282.679 100
## very large scale
set.seed(1L);
N <- 1e7L;
x <- sample(c(T,F),N,T);
names(x) <- make.unique(rep_len(LETTERS,N));
ex <- ifelse.(x);
identical(ex,sapply.(x));
## [1] TRUE
identical(ex,setstoragemode(x));
## [1] TRUE
identical(ex,setmode(x));
## [1] TRUE
identical(ex,setclass(x));
## [1] TRUE
identical(ex,as.and.setnames(x));
## [1] TRUE
identical(ex,plus(x));
## [1] TRUE
identical(ex,addzero(x));
## [1] TRUE
microbenchmark(ifelse.(x),sapply.(x),setstoragemode(x),setmode(x),setclass(x),as.and.setnames(x),plus(x),addzero(x),times=5L);
## Unit: milliseconds
## expr min lq mean median uq max neval
## ifelse.(x) 1082.220903 1308.106967 3452.639836 1473.723533 6306.320235 7092.82754 5
## sapply.(x) 16766.199371 17431.458634 18401.672635 18398.345499 18843.890150 20568.46952 5
## setstoragemode(x) 13.298283 13.648103 173.574496 19.661753 24.736278 796.52806 5
## setmode(x) 19.043796 19.878573 75.669779 19.969235 39.683589 279.77370 5
## setclass(x) 14.025292 14.119804 259.627934 14.414457 26.838618 1228.74150 5
## as.and.setnames(x) 12.889875 24.241484 178.243948 24.962934 25.103631 804.02182 5
## plus(x) 7.577576 7.676364 9.047674 8.245142 8.253266 13.48602 5
## addzero(x) 18.861615 18.960403 71.284716 26.622226 26.950662 265.02867 5
Looks like the unary plus takes the cake. (And my ifelse() idea kinda sucks.)