1 Setup
1.1 Libraries
library(httr)
library(xml2)
library(magrittr)
library(dplyr)
library(purrr)
library(stringr)
library(knitr)
1.2 Retrieve Data from AoC
session_cookie <- set_cookies(session = keyring::key_get("AoC-GitHub-Cookie"))
base_url <- paste0("https://adventofcode.com/2024/day/", params$task_nr)
puzzle <- GET(base_url,
session_cookie) %>%
content(encoding = "UTF-8") %>%
xml_find_all("///article") %>%
lapply(as.character)
puzzle_data <- local({
GET(paste0(base_url, "/input"),
session_cookie) %>%
content(encoding = "UTF-8") %>%
str_split("\n") %>%
extract2(1L) %>%
head(-1L) %>%
str_split("") %>%
do.call(rbind, .)
})
2 Puzzle Day 4
2.1 Part 1
2.1.1 Description
— Day 4: Ceres Search —
“Looks like the Chief’s not here. Next!” One of The Historians pulls out a device and pushes the only button on it. After a brief flash, you recognize the interior of the Ceres monitoring station!
As the search for the Chief continues, a small Elf who lives on the station tugs on your shirt; she’d like to know if you could help her with her word search (your puzzle input). She only has to find one word: XMAS
.
This word search allows words to be horizontal, vertical, diagonal, written backwards, or even overlapping other words. It’s a little unusual, though, as you don’t merely need to find one instance of XMAS
- you need to find all of them. Here are a few ways XMAS
might appear, where irrelevant characters have been replaced with .
:
..X...
.SAMX.
.A..A.
XMAS.S
.X....
The actual word search will be full of letters instead. For example:
MMMSXXMASM
MSAMXMSMSA
AMXSXMAAMM
MSAMASMSMX
XMASAMXAMM
XXAMMXXAMA
SMSMSASXSS
SAXAMASAAA
MAMMMXMMMM
MXMXAXMASX
In this word search, XMAS
occurs a total of 18
times; here’s the same word search again, but where letters not involved in any XMAS
have been replaced with .
:
....XXMAS.
.SAMXMS...
...S..A...
..A.A.MS.X
XMASAMX.MM
X.....XA.A
S.S.S.S.SS
.A.A.A.A.A
..M.M.M.MM
.X.X.XMASX
Take a look at the little Elf’s word search. How many times does XMAS
appear?
2.1.2 Solution
First, we define a function that, from a given starting point extracts all 8 words:
get_word <- function(row, col, .data = puzzle_data, .length = 4L) {
pos <- expand.grid(
row_offset = -1:1,
column_offset = -1:1
) %>%
as_tibble() %>%
filter(row_offset !=0 | column_offset != 0) %>%
pmap(function(row_offset, column_offset) {
t(outer(c(row_offset, column_offset), seq(0, .length - 1L)) + c(row, col))
})
dd <- dim(.data)
valid_pos <- pos %>%
discard(\(m) {
any(m <= 0L | m[, 1] > dd[1L] | m[, 2L] > dd[2L])
})
valid_pos %>%
map_chr(\(idx) paste(c(.data[idx]), collapse = ""))
}
For instance, the 3 words from position (1 / 1)
(to the left, down and down left, the
other directions would be out of bounds) are XSMS, XMMX, and XAAX.
What is left is to get all positions starting with an X
and get all the words from
there. Then, we count how often we get the word XMAS
:
xpos <- which(puzzle_data == "X", arr.ind = TRUE) %>%
as_tibble()
pmap(xpos, get_word) %>%
flatten() %>%
str_count(fixed("XMAS")) %>%
sum()
## [1] 2654
2.2 Part 2
2.2.1 Description
— Part Two —
The Elf looks quizzically at you. Did you misunderstand the assignment?
Looking for the instructions, you flip over the word search to find that this isn’t actually an XMAS
puzzle; it’s an X-MAS
puzzle in which you’re supposed to find two MAS
in the shape of an X
. One way to achieve that is like this:
M.S
.A.
M.S
Irrelevant characters have again been replaced with .
in the above diagram. Within the X
, each MAS
can be written forwards or backwards.
Here’s the same example from before, but this time all of the X-MAS
es have been kept instead:
.M.S......
..A..MSMS.
.M.S.MAA..
..A.ASMSM.
.M.S.M....
..........
S.S.S.S.S.
.A.A.A.A..
M.M.M.M.M.
..........
In this example, an X-MAS
appears 9
times.
Flip the word search from the instructions back over to the word search side and try again. How many times does an X-MAS
appear?
2.2.2 Solution
We apply the same idea, first for each position we get the x-shaped words (note that the position is the middle point):
get_xword <- function(row, col, .data = puzzle_data) {
idx <- rbind(
c(-1, 0, 1, -1, 1),
c(-1, 0, -1, 1, 1)
) + c(row, col)
paste(c(.data[t(idx)]), collapse = "")
}
Each A
is the middle point of a potential x-word (exclude As
in first / last
column row as they cannot be a middle point). For each of these positions check whether
the x-word is any of the permutations of MAS
(we pasted the letters top-left / middle /
bottom-left / top-right / bottom-right), those are MAMSS
, MASMS
, SAMSM
and
SASMM
.
apos <- which(puzzle_data == "A", arr.ind = TRUE) %>%
as_tibble() %>%
filter(between(row, 2, nrow(puzzle_data) - 1),
between(col, 2, ncol(puzzle_data) - 1))
pmap(apos, get_xword) %>%
flatten() %>%
str_count("MAMSS|MASMS|SAMSM|SASMM") %>%
sum()
## [1] 1990