23: Opening the Turing Lock

library(mistlecode)

To install `mistlecode` yourself, run `devtools::install_github('guslipkin/mistlecode')`.

 Also loading:  cipheR data.table dplyr purrr slider stringr tidyverse glue

instructions <- function(instruction) {
  force(instruction)
  function(dt_i) {
    dt <- dt_i[[1]]; i <- dt_i[[2]]; a <- dt_i[[3]]; b <- dt_i[[4]];
    if (!is.na(dt[[i]]$register)) {
      x <- if (dt[[i]]$register == "a") a else b
      x <- case_match(
        instruction,
        "hlf" ~ x / 2,
        "tpl" ~ x * 3,
        "inc" ~ x + 1,
        .default = x
      )
      if (dt[[i]]$register == "a") a <- x else b <- x
    } else { x <- NA }
    
    if (instruction == "jmp" | 
        (instruction == "jio" & x == 1) |
        (instruction == "jie" & x %% 2 == 0)) {
      i <- i + dt[[i]]$offset
    } else {
      i <- i + 1
    }
    
    if (i > length(dt)) { return(list(a, b)) }
    return(list(dt, i, a, b))
  }
}

dt <-
  readLines("input.txt") |>
  str_split("[, \\+]+") |>
  map(\(x) {
    if (x[1] == "jmp") {
      x <- list(x[1], NA, x[2])
    } else if (length(x) == 2) {
      x <- list(x[1], x[2], NA)
    } else {
      x <- as.list(x)
    }
    names(x) <- c("instruction", "register", "offset")
    x$instruction <- instructions(x$instruction)
    x$offset <- as.integer(x$offset)
    return(x)
  })

Part 1

This was very annoying. I’m happy I got to use function factories, but I really do need to find a better way to write these “follow instructions” style programs. Maybe something with S4 or S7 so I can self reference?

dt_i <- dt[[1]]$instruction(list(dt, 1, 0, 0))
repeat {
  dt_i <- dt_i[[1]][[dt_i[[2]]]]$instruction(dt_i)
  if (length(dt_i) == 2) { break }
}
dt_i[[2]]

[1] 255

Part 2

Oh jeez. A super easy copy/paste part 2!

dt_i <- dt[[1]]$instruction(list(dt, 1, 1, 0))
repeat {
  dt_i <- dt_i[[1]][[dt_i[[2]]]]$instruction(dt_i)
  if (length(dt_i) == 2) { break }
}
dt_i[[2]]

[1] 334