Day 2: Red-Nosed Reports

library(tidyverse)

The lines have different numbers of reports, so loading it in using a rawer method than the usual read.csv and friends:

dat <- read_lines("aoc02.txt")

head(dat)

[1] "87 90 92 95 96 93"    "12 15 16 17 17"       "26 27 29 31 34 36 40"
[4] "79 80 82 85 87 88 95" "17 20 22 20 23 24"    "10 13 11 12 9"       

That’s a vector of strings. Next, split each string on the space and make a list of numeric vectors:

repl <- strsplit(dat, " ") |> map(as.numeric)
head(repl)

[[1]]
[1] 87 90 92 95 96 93

[[2]]
[1] 12 15 16 17 17

[[3]]
[1] 26 27 29 31 34 36 40

[[4]]
[1] 79 80 82 85 87 88 95

[[5]]
[1] 17 20 22 20 23 24

[[6]]
[1] 10 13 11 12  9

Part 1

The rules are:

• The levels are either all increasing or all decreasing.
• Any two adjacent levels differ by at least one and at most three.

Wrap in a function:

test_report <- function(nums) {
  test_diffs <- diff(nums, lag = 1, difference = 1)
  all(test_diffs %in% 1:3) || all(-test_diffs %in% 1:3) 
}

The answer:

res <- map_lgl(repl, test_report)
sum(res)

[1] 483

Part 2

I’m going to brute force this one and try dropping elements even if it’s unnecessary, as I don’t have time to be clever 🙃

robust_test_report <- function(nums) {
  if (test_report(nums)) {
    TRUE
  }
  else {
    res <- FALSE
    for (i in 1:length(nums)) {
      res <- test_report(nums[-i])
      if (res)
        break
    }
    res
  }
}

And it worked:

robust_res <- map_lgl(repl, robust_test_report)
sum(robust_res)

[1] 528