Whats the best way to optimize this for loop (letter to number) function?

Question

I have a input stream of cleaned letters that I want to convert into a vector of numbers from 1 to 27 (all letters including space). I can't imagine a nested for loop is the best way to do this though. Is it possible without the loops?

space_letters = append(letters, " ")

text_to_numbers = function (input_stream) {

  input_stream = unlist(strsplit(input_stream, split = ""))

  for(i in 1:length(input_stream)) {
    for(j in 1:length(space_letters) {
      if(input_stream[i] == space_letters[j]) {
        input_stream[i] = j
      }
    }
  }
  return(as.integer(input_stream))
}

Answer 1

Here is a base R alternative using match

text_to_numbers <- function(ss)
    as.numeric(sapply(strsplit(ss, ""), function(x) match(x, c(letters, " "))))

text_to_numbers("abcdef")
#[1] 1 2 3 4 5 6

text_to_numbers("the cat")
#[1] 20  8  5 27  3  1 20

---

Or the purrr/stringr equivalent:

library(tidyverse)
text_to_numbers <- function(ss)
    map_int(str_split(ss, "", simplify = T), ~match(.x, c(letters, " ")))

Answer 2

As you have defined the problem, another possible solution is to take advantage of ASCII encoding to obtain the desired numerical codes.

v <- 'AbcdefGHijklmnopqrstuvwxyz '

char_to_num <- function(x) {
    v <- as.numeric(charToRaw(tolower(x))) - 96
    ifelse(v==-64, 27, v)
}

char_to_num(v)

[1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Answer 3

Here's one base-R way using a named vector as a dictionary-style data structure. You can also do the same thing with tidyverse functions, as shown below.

Note that as written this assumes you are passing length-one character vectors; if you want to pass longer vectors you'll need to modify a little.

lipsum <- "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua ut enim ad minim veniam quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur excepteur sint occaecat cupidatat non proident sunt in culpa qui officia deserunt mollit anim id est laborum"

text_to_numbers <- function (input_stream) {
  lookup <- 1:27
  names(lookup) <- append(letters, " ")
  input_stream = unlist(strsplit(input_stream, split = ""))
  numbers <- sapply(input_stream, function(x) lookup[[x]])
  names(numbers) <- NULL
  return(numbers)
}
text_to_numbers(lipsum)
#>   [1] 12 15 18  5 13 27  9 16 19 21 13 27  4 15 12 15 18 27 19  9 20 27  1
#>  [24] 13  5 20 27  3 15 14 19  5  3 20  5 20 21 18 27  1  4  9 16  9 19  3
#>  [47]  9 14  7 27  5 12  9 20 27 19  5  4 27  4 15 27  5  9 21 19 13 15  4
#>  [70] 27 20  5 13 16 15 18 27  9 14  3  9  4  9  4 21 14 20 27 21 20 27 12
#>  [93]  1  2 15 18  5 27  5 20 27  4 15 12 15 18  5 27 13  1  7 14  1 27  1
#> [116] 12  9 17 21  1 27 21 20 27  5 14  9 13 27  1  4 27 13  9 14  9 13 27
#> [139] 22  5 14  9  1 13 27 17 21  9 19 27 14 15 19 20 18 21  4 27  5 24  5
#> [162] 18  3  9 20  1 20  9 15 14 27 21 12 12  1 13  3 15 27 12  1  2 15 18
#> [185]  9 19 27 14  9 19  9 27 21 20 27  1 12  9 17 21  9 16 27  5 24 27  5
#> [208]  1 27  3 15 13 13 15  4 15 27  3 15 14 19  5 17 21  1 20 27  4 21  9
#> [231] 19 27  1 21 20  5 27  9 18 21 18  5 27  4 15 12 15 18 27  9 14 27 18
#> [254]  5 16 18  5  8  5 14  4  5 18  9 20 27  9 14 27 22 15 12 21 16 20  1
#> [277] 20  5 27 22  5 12  9 20 27  5 19 19  5 27  3  9 12 12 21 13 27  4 15
#> [300] 12 15 18  5 27  5 21 27  6 21  7  9  1 20 27 14 21 12 12  1 27 16  1
#> [323] 18  9  1 20 21 18 27  5 24  3  5 16 20  5 21 18 27 19  9 14 20 27 15
#> [346]  3  3  1  5  3  1 20 27  3 21 16  9  4  1 20  1 20 27 14 15 14 27 16
#> [369] 18 15  9  4  5 14 20 27 19 21 14 20 27  9 14 27  3 21 12 16  1 27 17
#> [392] 21  9 27 15  6  6  9  3  9  1 27  4  5 19  5 18 21 14 20 27 13 15 12
#> [415] 12  9 20 27  1 14  9 13 27  9  4 27  5 19 20 27 12  1  2 15 18 21 13

library(tidyverse)
tidy_text_to_numbers <- function(input_stream){
  lookup <- 1:27 %>%
    set_names(append(letters, " "))
  input_stream %>%
    str_split("") %>%
    unlist %>%
    map_int(~ lookup[[.]])
}
tidy_text_to_numbers(lipsum)
#>   [1] 12 15 18  5 13 27  9 16 19 21 13 27  4 15 12 15 18 27 19  9 20 27  1
#>  [24] 13  5 20 27  3 15 14 19  5  3 20  5 20 21 18 27  1  4  9 16  9 19  3
#>  [47]  9 14  7 27  5 12  9 20 27 19  5  4 27  4 15 27  5  9 21 19 13 15  4
#>  [70] 27 20  5 13 16 15 18 27  9 14  3  9  4  9  4 21 14 20 27 21 20 27 12
#>  [93]  1  2 15 18  5 27  5 20 27  4 15 12 15 18  5 27 13  1  7 14  1 27  1
#> [116] 12  9 17 21  1 27 21 20 27  5 14  9 13 27  1  4 27 13  9 14  9 13 27
#> [139] 22  5 14  9  1 13 27 17 21  9 19 27 14 15 19 20 18 21  4 27  5 24  5
#> [162] 18  3  9 20  1 20  9 15 14 27 21 12 12  1 13  3 15 27 12  1  2 15 18
#> [185]  9 19 27 14  9 19  9 27 21 20 27  1 12  9 17 21  9 16 27  5 24 27  5
#> [208]  1 27  3 15 13 13 15  4 15 27  3 15 14 19  5 17 21  1 20 27  4 21  9
#> [231] 19 27  1 21 20  5 27  9 18 21 18  5 27  4 15 12 15 18 27  9 14 27 18
#> [254]  5 16 18  5  8  5 14  4  5 18  9 20 27  9 14 27 22 15 12 21 16 20  1
#> [277] 20  5 27 22  5 12  9 20 27  5 19 19  5 27  3  9 12 12 21 13 27  4 15
#> [300] 12 15 18  5 27  5 21 27  6 21  7  9  1 20 27 14 21 12 12  1 27 16  1
#> [323] 18  9  1 20 21 18 27  5 24  3  5 16 20  5 21 18 27 19  9 14 20 27 15
#> [346]  3  3  1  5  3  1 20 27  3 21 16  9  4  1 20  1 20 27 14 15 14 27 16
#> [369] 18 15  9  4  5 14 20 27 19 21 14 20 27  9 14 27  3 21 12 16  1 27 17
#> [392] 21  9 27 15  6  6  9  3  9  1 27  4  5 19  5 18 21 14 20 27 13 15 12
#> [415] 12  9 20 27  1 14  9 13 27  9  4 27  5 19 20 27 12  1  2 15 18 21 13

Created on 2018-10-01 by the reprex package (v0.2.0).

Answer 4

Here's a data.table alternative with a dictionary created by setkey().

library(data.table)

input_stream  <- "lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod tempor incididunt ut labore et dolore magna aliqua ut enim ad minim veniam quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur excepteur sint occaecat cupidatat non proident sunt in culpa qui officia deserunt mollit anim id est laborum"

dict <- data.table(number = 1:27, letter = append(letters, " "))
setkey(dict, letter)

dict[strsplit(input_stream , "")]$number

# [1] 12 15 18  5 13 27  9 16 19 21 13 27  4 15 12 15 18 27 19  9 20 27
# [23]  1 13  5 20 27  3 15 14 19  5  3 20  5 20 21 18 27  1  4  9 16  9
# [45] 19  3  9 14  7 27  5 12  9 20 27 19  5  4 27  4 15 27  5  9 21 19
# [67] 13 15  4 27 20  5 13 16 15 18 27  9 14  3  9  4  9  4 21 14 20 27
# [89] 21 20 27 12  1  2 15 18  5 27  5 20 27  4 15 12 15 18  5 27 13  1
# [111]  7 14  1 27  1 12  9 17 21  1 27 21 20 27  5 14  9 13 27  1  4 27
# [133] 13  9 14  9 13 27 22  5 14  9  1 13 27 17 21  9 19 27 14 15 19 20
# [155] 18 21  4 27  5 24  5 18  3  9 20  1 20  9 15 14 27 21 12 12  1 13
# [177]  3 15 27 12  1  2 15 18  9 19 27 14  9 19  9 27 21 20 27  1 12  9
# [199] 17 21  9 16 27  5 24 27  5  1 27  3 15 13 13 15  4 15 27  3 15 14
# [221] 19  5 17 21  1 20 27  4 21  9 19 27  1 21 20  5 27  9 18 21 18  5
# [243] 27  4 15 12 15 18 27  9 14 27 18  5 16 18  5  8  5 14  4  5 18  9
# [265] 20 27  9 14 27 22 15 12 21 16 20  1 20  5 27 22  5 12  9 20 27  5
# [287] 19 19  5 27  3  9 12 12 21 13 27  4 15 12 15 18  5 27  5 21 27  6
# [309] 21  7  9  1 20 27 14 21 12 12  1 27 16  1 18  9  1 20 21 18 27  5
# [331] 24  3  5 16 20  5 21 18 27 19  9 14 20 27 15  3  3  1  5  3  1 20
# [353] 27  3 21 16  9  4  1 20  1 20 27 14 15 14 27 16 18 15  9  4  5 14
# [375] 20 27 19 21 14 20 27  9 14 27  3 21 12 16  1 27 17 21  9 27 15  6
# [397]  6  9  3  9  1 27  4  5 19  5 18 21 14 20 27 13 15 12 12  9 20 27
# [419]  1 14  9 13 27  9  4 27  5 19 20 27 12  1  2 15 18 21 13

Answer 5

We could also use factors:

  input_stream <- "the cat"
  input_stream <- strsplit(input_stream, "")[[1]]
  as.numeric(factor(input_stream,c(letters," ")))
  # [1] 20  8  5 27  3  1 20