README.md
In moodymudskipper/adventofcode2021: My Solutions for Advent Of Code 2021
adventofcode2021
My solutions for adventofcode2021. You can install it with
remotes::install_github("moodymudskipper/adventofcode2021")
The package contains functions day1, day2 etc, the README displays
the body of these functions.
day 1
function() {
# data
file <- system.file("extdata/day1.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = "\n", quiet = TRUE)
# part 1
part1 <- sum(diff(input) > 0)
# part 2
part2 <- sum(diff(diff(c(0, cumsum(input)), 3)) > 0)
# should be :
part2 <- sum(diff(input, 3) > 0)
list(part1 = part1, part2 = part2)
}
day 2
function() {
# data
file <- system.file("extdata/day2.txt", package = "adventofcode2021")
input <- scan(file, what = character(), sep = "\n", quiet = TRUE)
# part 1
# transform code into complex arithmetic and eval
code <- paste(input, collapse = "")
code <- gsub("forward ", "+", code)
code <- gsub("down (\\d+)", "+\\1i", code)
code <- gsub("up (\\d+)", "-\\1i", code)
pos <- eval(str2lang(code))
part1 <- Re(pos) * Im(pos)
# part1 again
# same with vectors rather than complex values
code <- paste(input, collapse = "")
code <- gsub("forward (\\d+)", "+c(\\1,0)", code)
code <- gsub("down (\\d+)", "+c(0,\\1)", code)
code <- gsub("up (\\d+)", "-c(0,\\1)", code)
pos <- eval(str2lang(code))
part1 <- prod(pos)
# part 2
# convert instructions to functions and reduce
code <- gsub("forward (\\d+)", "\\\\(x) x + c(\\1, x[3] * \\1, 0)", input)
code <- gsub("down (\\d+)", "\\\\(x) x + c(0, 0, \\1)", code)
code <- gsub("up (\\d+)", "\\\\(x) x - c(0, 0, \\1)", code)
pos <- Reduce(function(x, f) f(x), lapply(code, \(f) eval(str2lang(f))), c(0,0,0))
part2 <- prod(pos[1:2])
list(part1 = part1, part2 = part2)
}
day 3
function() {
# data
file <- system.file("extdata/day3.txt", package = "adventofcode2021")
input <- scan(file, what = character(), sep = "", quiet = TRUE)
mat <- do.call(rbind, strsplit(input, "")) == 1
# part 1
gamma <- colMeans(mat) >= .5
epsilon <- !gamma
powers <- 2^(rev(seq_along(gamma)-1))
part1 <- sum(powers * gamma) * sum(powers * epsilon)
# part 2
oxygen <- co2 <- mat
for (i in seq(ncol(mat))) {
if (is.matrix(oxygen))
oxygen <- oxygen[oxygen[,i] == (mean(oxygen[,i]) >= .5),]
if (is.matrix(co2))
co2 <- co2[co2[,i] == (mean(co2[,i]) < .5),]
}
part2 <- sum(powers * oxygen) * sum(powers * co2)
list(part1 = part1, part2 = part2)
}
day 4
function() {
# data
file <- system.file("extdata/day4.txt", package = "adventofcode2021")
draws <- scan(file, what = numeric(), sep = ",", quiet = TRUE, nlines = 1)
boards_raw <- read.delim(file, skip = 2, header = F, sep ="")
n <- ncol(boards_raw)
n_boards <- nrow(boards_raw) / n
boards <- data.frame(
num = unlist(boards_raw),
board = rep(1:n_boards, each = n),
col = rep(rep(1:n, each = n * n_boards)),
row = 1:n)
# the row/line indice is stored in `row` because "reshape"
boards_tidy <- reshape(
boards, idvar = c("num", "board"), direction = "long",
varying = list(c("row", "col")), times = c("row", "col"), timevar = "dir")
boards_tidy <- within(boards_tidy, {
match <- match(num, draws)
highest_match_by_line <- ave(match, board, dir, row, FUN = max)
winning_match_by_board <- ave(highest_match_by_line, board, FUN = min)
})
# part 1
ending_match <- min(boards_tidy$winning_match_by_board)
winning_board <- subset(
boards_tidy,
board == board[winning_match_by_board == ending_match] & match > ending_match)
part1 <- sum(winning_board$num) * draws[ending_match] / 2
# part 2, same but min -> max
ending_match <- max(boards_tidy$winning_match_by_board)
winning_board <- subset(
boards_tidy,
board == board[winning_match_by_board == ending_match] & match > ending_match)
part2 <- sum(winning_board$num) * draws[ending_match] / 2
list(part1 = part1, part2 = part2)
}
day 5
function() {
# data
file <- system.file("extdata/day5.txt", package = "adventofcode2021")
input <- unglue::unglue_data(readLines(file), "{x1},{y1}->{x2},{y2}", convert = TRUE) + 1
grid <- with(input, matrix(0, nrow = max(x1, x2), ncol = max(y1, y2)))
# part1
input1 <- subset(input, x1 == x2 | y1 == y2)
update_grid <- function(grid, coords) with(coords, {
grid[x1:x2, y1:y2] <- grid[x1:x2, y1:y2] + 1
grid})
grid1 <- Reduce(update_grid, x = split(input1, 1:nrow(input1)), init = grid)
part1 <- sum(grid1 >= 2)
# part 2
update_grid <- function(grid, coords) with(coords, {
if(x1 == x2 | y1 == y2)
grid[x1:x2, y1:y2] <- grid[x1:x2, y1:y2] + 1
else
diag(grid[x1:x2, y1:y2]) <- diag(grid[x1:x2, y1:y2]) + 1
grid})
grid2 <- Reduce(update_grid, x = split(input, 1:nrow(input)), init = grid)
part2 <- sum(grid2 >= 2)
# alternate solution
input <- unglue::unglue_data(readLines(file), "{x1},{y1}->{x2},{y2}", convert = TRUE) + 1
solve <- \(x) x |>
split(1:nrow(x)) |>
lapply(\(row) data.frame(x = row$x1:row$x2, y = row$y1:row$y2, n = 1)) |>
do.call(what = rbind) |>
stats:::aggregate.formula(formula = n ~ x + y, FUN = sum) |>
subset(n > 1) |>
nrow()
# part1
input1 <- subset(input, x1 == x2 | y1 == y2)
part1 <- solve(input1)
# part2 (same but using unfiltered input)
part2 <- solve(input)
list(part1 = part1, part2 = part2)
}
day 6
function() {
# data
file <- system.file("extdata/day6.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = ",", quiet = TRUE)
input <- merge(data.frame(input = 0:8), as.data.frame(table(input)), all.x = TRUE)
input$Freq[is.na(input$Freq)] <- 0
input2 <- input
# part1
for(i in 1:80) {
input$input <- (input$input - 1) %% 9
input$Freq[input$input == 6] <-
input$Freq[input$input == 6] + input$Freq[input$input == 8]
}
sum(input$Freq)
# can be simplified into :
# for(i in (1 + (6 + 1:80) %% 9)) {
# input$Freq[i] <- input$Freq[i] + input$Freq[1 + (i + 1) %% 9]
# }
# sum(input$Freq)
# part2 (same thing)
for(i in 1:256) {
input2$input <- (input2$input - 1) %% 9
input2$Freq[input2$input == 6] <-
input2$Freq[input2$input == 6] + input2$Freq[input2$input == 8]
}
format(sum(input2$Freq), scientific = FALSE)
list(part1 = part1, part2 = part2)
}
day 7
function() {
# data
file <- system.file("extdata/day7.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = ",", quiet = TRUE)
counts <- transform(as.data.frame(table(input), stringsAsFactors = FALSE),
input = as.numeric(input))
grid <- merge(seq(max(input)), counts, by = NULL) |>
transform(dist = abs((x - input)))
# part1
part1 <- min(with(grid, tapply(dist * Freq, x, sum)))
# part2
part2 <- min(with(grid, tapply(dist * (dist+1) / 2 * Freq , x, sum)))
list(part1 = part1, part2 = part2)
}
day 8
function() {
# data
file <- system.file("extdata/day8ex.txt", package = "adventofcode2021")
input <- readLines(file)
pattern <- "{x0} {x1} {x2} {x3} {x4} {x5} {x6} {x7} {x8} {x9} | {y0} {y1} {y2} {y3}"
input_df <- unglue::unglue_data(input, pattern)
# part1
part1 <- sum(nchar(unlist(input_df[11:14])) %in% c(2,3,4,7))
# part2
library(tidyverse)
# establish number profiles
numbers <- tibble(
x0 = "abcefg", x1 = "cf", x2 = "acdeg", x3 = "acdfg", x4 = "bcdf",
x5 = "abdfg", x6 = "abdefg", x7 = "acf", x8 = "abcdefg", x9 = "abcdfg")
to_long <-
. %>%
mutate(line = 1:n()) %>%
pivot_longer(-line, names_to = "pos", values_to = "segment") %>%
separate_rows(segment, sep="") %>%
filter(segment != "") %>%
mutate(input = startsWith(pos, "x")) %>%
with_groups(c(line, segment), mutate, n_segment = sum(input)) %>%
with_groups(c(line, pos), summarise, key = list(sort(n_segment)))
numbers_long <- to_long(numbers) %>% transmute(key, num = 0:9)
input_long <- to_long(input_df)
part2 <- left_join(input_long, numbers_long, by = "key") %>%
filter(startsWith(pos, "y")) %>%
with_groups(line, summarise, num = sum(num * c(1000, 100, 10, 1))) %>%
pull(num) %>%
sum()
list(part1 = part1, part2 = part2)
}
day 9
function() {
# data
file <- system.file("extdata/day9.txt", package = "adventofcode2021")
input_mat <- do.call(rbind,strsplit(readLines(file), ""))
# pad with 9s
input_mat <- cbind("9", rbind("9", input_mat, "9"), "9")
n_rows <- nrow(input_mat)
input_vec <- as.numeric(input_mat)
# implement own base lag/lead padding with 9s
lag <- function(x, n = 1) c(rep(9, n), head(x, -n))
lead <- function(x, n = 1) c(tail(x, -n), rep(9, n))
## part1
lows_lgl <-
input_vec < lag(input_vec) &
input_vec < lead(input_vec) &
input_vec < lag(input_vec, n_rows) &
input_vec < lead(input_vec, n_rows)
part1 <- sum(input_vec[lows_lgl] + 1)
## part2
# every location next to a basin cell is from this basin, unless it's a 9
# first set low points to different negative values so we can keep track
input_vec[lows_lgl] <- -seq(sum(lows_lgl))
nines <- input_vec == 9
while(any(input_vec %in% 1:8)) {
input_vec <- pmin(
input_vec,
lag(input_vec),
lead(input_vec),
lag(input_vec, n_rows),
lead(input_vec, n_rows)
)
input_vec[nines] <- 9 # repair the walls
}
# visual check : matrix(input_vec, n_rows)
part2 <- prod(tail(sort(tabulate(-input_vec)),3))
list(part1 = part1, part2 = part2)
}
day10
function() {
# data
file <- system.file("extdata/day10ex.txt", package = "adventofcode2021")
input <- strsplit(readLines(file), "")
## part1
# fun fact: these numbers are cumprod(c(3,19,21,21)), is there a reason ?
mapper <- list("(" = -3, ")" = 3, "[" = -57, "]" = 57, "{" = -1197, "}" = 1197, "<" = -25137, ">" = 25137)
check_line <- function(l) {
l <- mapper[l]
n <- length(l)
i <- 2
while(i <= n) {
if(l[[i]] > 0) {
if(l[[i]] != -l[[i-1]]) return(l[[i]]) # corrupted chunk!
l[(i-1):i] <- NULL
i <- i-1
n <- n-2
} else {
i <- i + 1
}
}
0
}
scores <- sapply(input, check_line)
part1 <- sum(scores)
## part2
input2 <- input[scores == 0]
mapper2 <- list("(" = 1, ")" = -1, "[" = 2, "]" = -2, "{" = 3, "}" = -3, "<" = 4, ">" = -4)
complete_line <- function(l) {
l <- mapper2[l]
n <- length(l)
i <- 2
while(i <= n) {
if(l[[i]] < 0) {
l[(i-1):i] <- NULL
i <- i-1
n <- n-2
} else {
i <- i + 1
}
}
# reversed number in base 5
sum(unlist(l) * 5^(seq_along(l)-1))
}
scores2 <- sapply(input2, complete_line)
part2 <- median(scores2)
list(part1 = part1, part2 = part2)
}
day11
function() {
# data
file <- system.file("extdata/day11.txt", package = "adventofcode2021")
input_mat <- do.call(rbind, strsplit(readLines(file), ""))
# build walls of NAs so we don't have to bother with edge/corner cases <- lol
input_mat <- cbind(NA, rbind(NA, input_mat, NA), NA)
n_rows <- nrow(input_mat)
input_vec <- as.numeric(input_mat)
flashes <- i <- 0
repeat {
i <- i + 1
input_vec <- input_vec + 1
pos <- which(input_vec > 9)
while(new_flashes <- length(pos)) {
flashes <- flashes + new_flashes
input_vec[pos] <- -Inf # protect flashed cells
input_vec <- Reduce(
\(vec, j) { vec[pos + j] <- vec[pos + j] + 1 ; vec},
c((-n_rows-1):(-n_rows+1), -1, +1, (+n_rows-1):(+n_rows+1)),
input_vec)
pos <- which(input_vec > 9)
}
input_vec[input_vec == -Inf] <- 0
if (i == 100) {
part1 <- flashes
}
if(sum(input_vec, na.rm = TRUE) == 0) {
part2 <- i
break
}
}
list(part1 = part1, part2 = part2)
}
day12
function() {
# data
file <- system.file("extdata/day12.txt", package = "adventofcode2021")
input <- unglue::unglue_data(readLines(file), "{from}-{to}")
# paths go both ways
input <-
rbind(input, setNames(input, c("to", "from"))) |>
subset(to != "start")
edges <- with(input, split(to, from))
nodes <- with(input, unique(c(from, to)))
visited0 <- setNames(rep(FALSE, length(nodes)), nodes)
visited0[nodes == toupper(nodes)] <- NA
rec <- function(node = "start", visited = visited0, extra) {
if(isTRUE(visited[node])) {
if (!extra) return(0)
visited[node] <- FALSE
extra <- FALSE
}
if(node == "end") return(1)
visited[node] <- !visited[node]
sum(sapply(edges[[node]], rec, visited, extra))
}
part1 <- rec(extra = FALSE)
part2 <- rec(extra = TRUE)
list(part1 = part1, part2 = part2)
}
day13
function() {
# data
file <- system.file("extdata/day13.txt", package = "adventofcode2021")
coords1 <- coords2 <- na.omit(unglue::unglue_data(readLines(file), "{x},{y}", convert = TRUE))
x_folds <- na.omit(unglue::unglue_vec(readLines(file), "fold along x={val}", convert = TRUE))
y_folds <- na.omit(unglue::unglue_vec(readLines(file), "fold along y={val}", convert = TRUE))
# part 1
coords1$x <- abs(x_folds[1] - coords1$x) - 1
part1 <- nrow(unique(coords1))
# part 2
for (x in x_folds) {
coords2$x <- abs(x - coords2$x) - 1
}
for (y in y_folds) {
coords2$y <- abs(y - coords2$y) - 1
}
coords2 <- unique(coords2)
plot(transform(coords2, x = -x))
list(part1 = part1, part2 = NULL)
}
day14
function() {
# data
library(tidyverse)
file <- system.file("extdata/day14.txt", package = "adventofcode2021")
input <- readLines(file)
pairs <- tibble(
from = substring(input[1], 1:(nchar(input[1]) - 1), 2:nchar(input[1])),
n = 1)
first_letter <- substr(input[1], 1, 1)
mapper <-
unglue::unglue_data(input[-(1:2)], "{from} -> {to}") %>%
mutate(to = pmap(list(from, to), ~ c(
paste0(substr(.x, 1, 1), .y),
paste0(.y, substr(.x, 2, 2))))) %>%
unnest(to)
solve <- function(steps) {
for (i in 1:steps) {
pairs <-
left_join(pairs, mapper, by = "from") %>%
count(from = to, wt = n)
}
counts <-
pairs %>%
separate(from, c("from1", "from2"), sep = 1) %>%
count(letter = from2, wt = n) %>%
mutate(n = ifelse(letter == first_letter, n+1, n))
format(max(counts$n) - min(counts$n), scientific = FALSE)
}
part1 <- solve(10)
part2 <- solve(40)
list(part1 = part1, part2 = NULL)
}
day15
function() {
# data
library(tidyverse)
file <- system.file("extdata/day15.txt", package = "adventofcode2021")
input_mat <- do.call(rbind, lapply(strsplit(readLines(file), ""), as.numeric))
solve <- function(input_mat) {
# build walls of Inf simulating cells that cannot have their score improved
input_mat <- cbind(Inf, rbind(Inf, input_mat, Inf), Inf)
n_rows <- nrow(input_mat)
# start point
points <- c(n_rows + 2)
input_vec <- scores <- c(input_mat)
# at first we only know the lowest score to 1st cell is 0
scores[] <- Inf
scores[points] <- 0
# keep going if scores improve
while (length(points)) {
old_scores <- scores
# check if we can improve a score in any of the 4 directions
for (delta in c(+1, -1, +n_rows, -n_rows)) {
new_scores <- scores
new_scores[points + delta] <- scores[points] + input_vec[points + delta]
scores <- pmin(scores, new_scores) # keep best scores only
}
points <- which(scores != old_scores)
}
scores[length(scores)-n_rows-1]
}
# part1
part1 <- solve(input_mat)
# part2
input_mat2 <- do.call(rbind, replicate(5, input_mat, simplify = F))
input_mat2 <- do.call(cbind, replicate(5, input_mat2, simplify = F))
additions <- (col(input_mat2) -1) %/% ncol(input_mat) + (row(input_mat2) -1) %/% nrow(input_mat)
input_mat2 <- (input_mat2 + additions - 1) %% 9 + 1
part2 <- solve(input_mat2)
list(part1 = part1, part2 = NULL)
}
day16
function() {
# data
library(tidyverse)
file <- system.file("extdata/day16.txt", package = "adventofcode2021")
mapper <- setNames(
sapply(0:15, \(x) substr(paste(rev(as.integer(intToBits(x))), collapse=""), 29, 32)),
c(0:9, LETTERS[1:6]))
bin <- paste(mapper[strsplit(readLines(file), "")[[1]]], collapse = "")
solve <- function(bin, packet_pos = 1, max_pos = 1) {
len <- nchar(bin)
version <- strtoi(substr(bin, 1, 3), base = 2)
type <- strtoi(substr(bin, 4, 6), base = 2)
if(type == 4) {
split_remainder <- strsplit(bin, "")[[1]][-(1:6)]
n_litteral <-
suppressWarnings(which.min(split_remainder == 1 | c(F, T, T, T, T)) + 4)
value <- split_remainder[1:n_litteral][c(F, T, T, T, T)]
value <- sum((value==1)*2^(rev(seq_along(value))-1))
remainder <- substr(bin, 6 + n_litteral + 1, len)
len <- len - nchar(remainder)
subpackets <- NULL
sum_of_versions <- version
} else {
length_type <- substr(bin, 7, 7)
if(length_type == 0) {
subpackets_length <- strtoi(substr(bin, 7+1, 7+15), base = 2)
subpackets_bin <- substr(bin, 7+15+1, 7+15+subpackets_length)
# we have a limit on chars but not on number of subpackets
subpackets <- solve(subpackets_bin, packet_pos = 1, max_pos = Inf)
remainder <- substr(bin, 8+15+subpackets_length, len)
len <- len - nchar(remainder)
} else {
subpackets_n <- strtoi(substr(bin, 7+1, 7+11), base = 2)
# we have a limit on number of subpackets, not on chars
subpackets_bin <- substr(bin, 7+11+1, len)
subpackets <- solve(subpackets_bin, packet_pos = 1, max_pos = subpackets_n)
covered_len <- 7 + 11 + sum(sapply(subpackets, \(x) x$len))
remainder <- substr(bin, covered_len + 1, len)
len <- covered_len
}
value <- switch(
as.character(type),
"0" = sum(sapply(subpackets, \(x) x$value)),
"1" = prod(sapply(subpackets, \(x) x$value)),
"2" = min(sapply(subpackets, \(x) x$value)),
"3" = max(sapply(subpackets, \(x) x$value)),
"5" = subpackets[[1]]$value > subpackets[[2]]$value,
"6" = subpackets[[1]]$value < subpackets[[2]]$value,
"7" = subpackets[[1]]$value == subpackets[[2]]$value
)
sum_of_versions <- version + sum(sapply(subpackets, \(x) x$sum_of_versions))
}
# 1st subpacket
res <- list(list(
value = value,
len = len,
subpackets = subpackets,
sum_of_versions = sum_of_versions))
# other subpackets
if(packet_pos != max_pos && remainder != "" && !grepl("^0+$", remainder)) {
res <- c(res, solve(remainder, packet_pos = packet_pos + 1, max_pos = max_pos))
}
res
}
packet1 <- solve(bin)[[1]]
part1 <- packet1$sum_of_versions
part2 <- packet1$value
list(part1 = part1, part2 = NULL) # 246225449979
}
day17
function() {
# data
library(tidyverse)
file <- system.file("extdata/day17.txt", package = "adventofcode2021")
input <- unglue::unglue_data(
readLines(file),
"target area: x={x_min}..{x_max}, y={y_min}..{y_max}",
convert = TRUE)
# part1
# we want to in one step as deep as allowed
# it also takes vy steps to go to the top, since we take back one unit per step
# and 1+..+n is n*(n-1)/2
n <- vy_max <- -input$y_min - 1
part1 <- n * vy_max - n*(n-1)/2
# part2 tidy
library(tidyverse)
max_steps <- 2*vy_max+2
# all combinations that would work vertically
y2 <-
crossing(n = 1:max_steps, vy = input$y_min:vy_max) %>%
mutate(y = n * vy - n^2/2 + n/2) %>%
filter(y >= input$y_min & y <= input$y_max)
# all combinations that would work horizontally
x2 <-
crossing(n = 1:max_steps, vx = 1:input$x_max) %>%
with_groups("vx", mutate, x = cummax(n * vx - n^2/2 + n/2)) %>%
filter(x >= input$x_min & x <= input$x_max)
# combine and count
part2 <-
inner_join(x2, y2, by = "n") %>%
distinct(vx, vy) %>%
nrow()
#---------------------------------------------------------------------------
# part2 base
max_steps <- 2*vy_max+2
n_seq <- 1: max_steps
# all combinations that would york vertically
y <- do.call(rbind, lapply(input$y_min:vy_max, function(vy) {
data.frame(vy, n = n_seq, y = n_seq * vy - n_seq^2/2 + n_seq/2) |>
subset(y >= input$y_min & y <= input$y_max)
}))
# all combinations that would work horizontally
x <- do.call(rbind, lapply(1:input$x_max, function(vx) {
data.frame(vx, n = n_seq, x = cummax(n_seq * vx - n_seq^2/2 + n_seq/2)) |>
subset(x >= input$x_min & x <= input$x_max)
}))
# combine and count
part2 <-
merge(x, y, by = "n")[c("vx", "vy")] |>
unique() |>
nrow()
list(part1 = part1, part2 = NULL) # 246225449979
}
day18
function() {
# data
library(tidyverse)
file <- system.file("extdata/day18.txt", package = "adventofcode2021")
add_pair <- function(x, y) {
snail_num <- paste0("[", x, ",", y, "]")
chars <- strsplit(snail_num, "")[[1]] # only 1 digit nums at this stage
repeat {
first_5th_bracket <- which(cumsum(chars == "[") - cumsum(chars == "]")== 5)[1]
all_num_pos <- grep("\\d", chars)
if(!is.na(first_5th_bracket)) {
# explode
before_bracket <- which(grep("\\d", chars) > first_5th_bracket)[1] - 1
num_pos <- all_num_pos[before_bracket + (0:3)]
if(before_bracket == 0) num_pos <- c(NA, num_pos)
if(!is.na(num_pos[1]))
chars[num_pos[1]] <- as.numeric(chars[num_pos[1]]) + as.numeric(chars[num_pos[2]])
if(!is.na(num_pos[4]))
chars[num_pos[4]] <- as.numeric(chars[num_pos[4]]) + as.numeric(chars[num_pos[3]])
chars <- c(chars[1:(first_5th_bracket-1)], "0", chars[(first_5th_bracket+5):length(chars)])
next
}
all_nums <- as.numeric(chars[all_num_pos])
first_big_num <- all_num_pos[all_nums >= 10][1]
if(!is.na(first_big_num)) {
#split
num <- all_nums[all_nums >= 10][1]
chars <- c(chars[1:(first_big_num-1)], "[", floor(num/2), "," , ceiling(num/2), "]", chars[(first_big_num+1):length(chars)])
next
}
break
}
paste(chars, collapse = "")
}
# part1
input <- readLines(file)
reduced <- Reduce(add_pair, input)
reduced_call <- gsub("\\[", "magn(", reduced)
reduced_call <- gsub("\\]", ")", reduced_call)
magn <- function(x, y) 3 * x + 2 * y
part1 <- eval(str2lang(reduced_call))
# part 2
grid <- merge(input, input, by = NULL) |> subset(x != y)
part2 <- with(grid, {
reduced <- mapply(add_pair, x, y)
reduced_call <- gsub("\\[", "magn(", reduced)
reduced_call <- gsub("\\]", ")", reduced_call)
max(sapply(parse(text=reduced_call), eval))
})
list(part1 = part1, part2 = NULL)
}
moodymudskipper/adventofcode2021 documentation built on Dec. 21, 2021, 9:01 p.m.
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adventofcode2021
My solutions for adventofcode2021. You can install it with
remotes::install_github("moodymudskipper/adventofcode2021")
The package contains functions day1, day2 etc, the README displays
the body of these functions.
day 1
function() {
# data
file <- system.file("extdata/day1.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = "\n", quiet = TRUE)
# part 1
part1 <- sum(diff(input) > 0)
# part 2
part2 <- sum(diff(diff(c(0, cumsum(input)), 3)) > 0)
# should be :
part2 <- sum(diff(input, 3) > 0)
list(part1 = part1, part2 = part2)
}
day 2
function() {
# data
file <- system.file("extdata/day2.txt", package = "adventofcode2021")
input <- scan(file, what = character(), sep = "\n", quiet = TRUE)
# part 1
# transform code into complex arithmetic and eval
code <- paste(input, collapse = "")
code <- gsub("forward ", "+", code)
code <- gsub("down (\\d+)", "+\\1i", code)
code <- gsub("up (\\d+)", "-\\1i", code)
pos <- eval(str2lang(code))
part1 <- Re(pos) * Im(pos)
# part1 again
# same with vectors rather than complex values
code <- paste(input, collapse = "")
code <- gsub("forward (\\d+)", "+c(\\1,0)", code)
code <- gsub("down (\\d+)", "+c(0,\\1)", code)
code <- gsub("up (\\d+)", "-c(0,\\1)", code)
pos <- eval(str2lang(code))
part1 <- prod(pos)
# part 2
# convert instructions to functions and reduce
code <- gsub("forward (\\d+)", "\\\\(x) x + c(\\1, x[3] * \\1, 0)", input)
code <- gsub("down (\\d+)", "\\\\(x) x + c(0, 0, \\1)", code)
code <- gsub("up (\\d+)", "\\\\(x) x - c(0, 0, \\1)", code)
pos <- Reduce(function(x, f) f(x), lapply(code, \(f) eval(str2lang(f))), c(0,0,0))
part2 <- prod(pos[1:2])
list(part1 = part1, part2 = part2)
}
day 3
function() {
# data
file <- system.file("extdata/day3.txt", package = "adventofcode2021")
input <- scan(file, what = character(), sep = "", quiet = TRUE)
mat <- do.call(rbind, strsplit(input, "")) == 1
# part 1
gamma <- colMeans(mat) >= .5
epsilon <- !gamma
powers <- 2^(rev(seq_along(gamma)-1))
part1 <- sum(powers * gamma) * sum(powers * epsilon)
# part 2
oxygen <- co2 <- mat
for (i in seq(ncol(mat))) {
if (is.matrix(oxygen))
oxygen <- oxygen[oxygen[,i] == (mean(oxygen[,i]) >= .5),]
if (is.matrix(co2))
co2 <- co2[co2[,i] == (mean(co2[,i]) < .5),]
}
part2 <- sum(powers * oxygen) * sum(powers * co2)
list(part1 = part1, part2 = part2)
}
day 4
function() {
# data
file <- system.file("extdata/day4.txt", package = "adventofcode2021")
draws <- scan(file, what = numeric(), sep = ",", quiet = TRUE, nlines = 1)
boards_raw <- read.delim(file, skip = 2, header = F, sep ="")
n <- ncol(boards_raw)
n_boards <- nrow(boards_raw) / n
boards <- data.frame(
num = unlist(boards_raw),
board = rep(1:n_boards, each = n),
col = rep(rep(1:n, each = n * n_boards)),
row = 1:n)
# the row/line indice is stored in `row` because "reshape"
boards_tidy <- reshape(
boards, idvar = c("num", "board"), direction = "long",
varying = list(c("row", "col")), times = c("row", "col"), timevar = "dir")
boards_tidy <- within(boards_tidy, {
match <- match(num, draws)
highest_match_by_line <- ave(match, board, dir, row, FUN = max)
winning_match_by_board <- ave(highest_match_by_line, board, FUN = min)
})
# part 1
ending_match <- min(boards_tidy$winning_match_by_board)
winning_board <- subset(
boards_tidy,
board == board[winning_match_by_board == ending_match] & match > ending_match)
part1 <- sum(winning_board$num) * draws[ending_match] / 2
# part 2, same but min -> max
ending_match <- max(boards_tidy$winning_match_by_board)
winning_board <- subset(
boards_tidy,
board == board[winning_match_by_board == ending_match] & match > ending_match)
part2 <- sum(winning_board$num) * draws[ending_match] / 2
list(part1 = part1, part2 = part2)
}
day 5
function() {
# data
file <- system.file("extdata/day5.txt", package = "adventofcode2021")
input <- unglue::unglue_data(readLines(file), "{x1},{y1}->{x2},{y2}", convert = TRUE) + 1
grid <- with(input, matrix(0, nrow = max(x1, x2), ncol = max(y1, y2)))
# part1
input1 <- subset(input, x1 == x2 | y1 == y2)
update_grid <- function(grid, coords) with(coords, {
grid[x1:x2, y1:y2] <- grid[x1:x2, y1:y2] + 1
grid})
grid1 <- Reduce(update_grid, x = split(input1, 1:nrow(input1)), init = grid)
part1 <- sum(grid1 >= 2)
# part 2
update_grid <- function(grid, coords) with(coords, {
if(x1 == x2 | y1 == y2)
grid[x1:x2, y1:y2] <- grid[x1:x2, y1:y2] + 1
else
diag(grid[x1:x2, y1:y2]) <- diag(grid[x1:x2, y1:y2]) + 1
grid})
grid2 <- Reduce(update_grid, x = split(input, 1:nrow(input)), init = grid)
part2 <- sum(grid2 >= 2)
# alternate solution
input <- unglue::unglue_data(readLines(file), "{x1},{y1}->{x2},{y2}", convert = TRUE) + 1
solve <- \(x) x |>
split(1:nrow(x)) |>
lapply(\(row) data.frame(x = row$x1:row$x2, y = row$y1:row$y2, n = 1)) |>
do.call(what = rbind) |>
stats:::aggregate.formula(formula = n ~ x + y, FUN = sum) |>
subset(n > 1) |>
nrow()
# part1
input1 <- subset(input, x1 == x2 | y1 == y2)
part1 <- solve(input1)
# part2 (same but using unfiltered input)
part2 <- solve(input)
list(part1 = part1, part2 = part2)
}
day 6
function() {
# data
file <- system.file("extdata/day6.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = ",", quiet = TRUE)
input <- merge(data.frame(input = 0:8), as.data.frame(table(input)), all.x = TRUE)
input$Freq[is.na(input$Freq)] <- 0
input2 <- input
# part1
for(i in 1:80) {
input$input <- (input$input - 1) %% 9
input$Freq[input$input == 6] <-
input$Freq[input$input == 6] + input$Freq[input$input == 8]
}
sum(input$Freq)
# can be simplified into :
# for(i in (1 + (6 + 1:80) %% 9)) {
# input$Freq[i] <- input$Freq[i] + input$Freq[1 + (i + 1) %% 9]
# }
# sum(input$Freq)
# part2 (same thing)
for(i in 1:256) {
input2$input <- (input2$input - 1) %% 9
input2$Freq[input2$input == 6] <-
input2$Freq[input2$input == 6] + input2$Freq[input2$input == 8]
}
format(sum(input2$Freq), scientific = FALSE)
list(part1 = part1, part2 = part2)
}
day 7
function() {
# data
file <- system.file("extdata/day7.txt", package = "adventofcode2021")
input <- scan(file, what = numeric(), sep = ",", quiet = TRUE)
counts <- transform(as.data.frame(table(input), stringsAsFactors = FALSE),
input = as.numeric(input))
grid <- merge(seq(max(input)), counts, by = NULL) |>
transform(dist = abs((x - input)))
# part1
part1 <- min(with(grid, tapply(dist * Freq, x, sum)))
# part2
part2 <- min(with(grid, tapply(dist * (dist+1) / 2 * Freq , x, sum)))
list(part1 = part1, part2 = part2)
}
day 8
function() {
# data
file <- system.file("extdata/day8ex.txt", package = "adventofcode2021")
input <- readLines(file)
pattern <- "{x0} {x1} {x2} {x3} {x4} {x5} {x6} {x7} {x8} {x9} | {y0} {y1} {y2} {y3}"
input_df <- unglue::unglue_data(input, pattern)
# part1
part1 <- sum(nchar(unlist(input_df[11:14])) %in% c(2,3,4,7))
# part2
library(tidyverse)
# establish number profiles
numbers <- tibble(
x0 = "abcefg", x1 = "cf", x2 = "acdeg", x3 = "acdfg", x4 = "bcdf",
x5 = "abdfg", x6 = "abdefg", x7 = "acf", x8 = "abcdefg", x9 = "abcdfg")
to_long <-
. %>%
mutate(line = 1:n()) %>%
pivot_longer(-line, names_to = "pos", values_to = "segment") %>%
separate_rows(segment, sep="") %>%
filter(segment != "") %>%
mutate(input = startsWith(pos, "x")) %>%
with_groups(c(line, segment), mutate, n_segment = sum(input)) %>%
with_groups(c(line, pos), summarise, key = list(sort(n_segment)))
numbers_long <- to_long(numbers) %>% transmute(key, num = 0:9)
input_long <- to_long(input_df)
part2 <- left_join(input_long, numbers_long, by = "key") %>%
filter(startsWith(pos, "y")) %>%
with_groups(line, summarise, num = sum(num * c(1000, 100, 10, 1))) %>%
pull(num) %>%
sum()
list(part1 = part1, part2 = part2)
}
day 9
function() {
# data
file <- system.file("extdata/day9.txt", package = "adventofcode2021")
input_mat <- do.call(rbind,strsplit(readLines(file), ""))
# pad with 9s
input_mat <- cbind("9", rbind("9", input_mat, "9"), "9")
n_rows <- nrow(input_mat)
input_vec <- as.numeric(input_mat)
# implement own base lag/lead padding with 9s
lag <- function(x, n = 1) c(rep(9, n), head(x, -n))
lead <- function(x, n = 1) c(tail(x, -n), rep(9, n))
## part1
lows_lgl <-
input_vec < lag(input_vec) &
input_vec < lead(input_vec) &
input_vec < lag(input_vec, n_rows) &
input_vec < lead(input_vec, n_rows)
part1 <- sum(input_vec[lows_lgl] + 1)
## part2
# every location next to a basin cell is from this basin, unless it's a 9
# first set low points to different negative values so we can keep track
input_vec[lows_lgl] <- -seq(sum(lows_lgl))
nines <- input_vec == 9
while(any(input_vec %in% 1:8)) {
input_vec <- pmin(
input_vec,
lag(input_vec),
lead(input_vec),
lag(input_vec, n_rows),
lead(input_vec, n_rows)
)
input_vec[nines] <- 9 # repair the walls
}
# visual check : matrix(input_vec, n_rows)
part2 <- prod(tail(sort(tabulate(-input_vec)),3))
list(part1 = part1, part2 = part2)
}
day10
function() {
# data
file <- system.file("extdata/day10ex.txt", package = "adventofcode2021")
input <- strsplit(readLines(file), "")
## part1
# fun fact: these numbers are cumprod(c(3,19,21,21)), is there a reason ?
mapper <- list("(" = -3, ")" = 3, "[" = -57, "]" = 57, "{" = -1197, "}" = 1197, "<" = -25137, ">" = 25137)
check_line <- function(l) {
l <- mapper[l]
n <- length(l)
i <- 2
while(i <= n) {
if(l[[i]] > 0) {
if(l[[i]] != -l[[i-1]]) return(l[[i]]) # corrupted chunk!
l[(i-1):i] <- NULL
i <- i-1
n <- n-2
} else {
i <- i + 1
}
}
0
}
scores <- sapply(input, check_line)
part1 <- sum(scores)
## part2
input2 <- input[scores == 0]
mapper2 <- list("(" = 1, ")" = -1, "[" = 2, "]" = -2, "{" = 3, "}" = -3, "<" = 4, ">" = -4)
complete_line <- function(l) {
l <- mapper2[l]
n <- length(l)
i <- 2
while(i <= n) {
if(l[[i]] < 0) {
l[(i-1):i] <- NULL
i <- i-1
n <- n-2
} else {
i <- i + 1
}
}
# reversed number in base 5
sum(unlist(l) * 5^(seq_along(l)-1))
}
scores2 <- sapply(input2, complete_line)
part2 <- median(scores2)
list(part1 = part1, part2 = part2)
}
day11
function() {
# data
file <- system.file("extdata/day11.txt", package = "adventofcode2021")
input_mat <- do.call(rbind, strsplit(readLines(file), ""))
# build walls of NAs so we don't have to bother with edge/corner cases <- lol
input_mat <- cbind(NA, rbind(NA, input_mat, NA), NA)
n_rows <- nrow(input_mat)
input_vec <- as.numeric(input_mat)
flashes <- i <- 0
repeat {
i <- i + 1
input_vec <- input_vec + 1
pos <- which(input_vec > 9)
while(new_flashes <- length(pos)) {
flashes <- flashes + new_flashes
input_vec[pos] <- -Inf # protect flashed cells
input_vec <- Reduce(
\(vec, j) { vec[pos + j] <- vec[pos + j] + 1 ; vec},
c((-n_rows-1):(-n_rows+1), -1, +1, (+n_rows-1):(+n_rows+1)),
input_vec)
pos <- which(input_vec > 9)
}
input_vec[input_vec == -Inf] <- 0
if (i == 100) {
part1 <- flashes
}
if(sum(input_vec, na.rm = TRUE) == 0) {
part2 <- i
break
}
}
list(part1 = part1, part2 = part2)
}
day12
function() {
# data
file <- system.file("extdata/day12.txt", package = "adventofcode2021")
input <- unglue::unglue_data(readLines(file), "{from}-{to}")
# paths go both ways
input <-
rbind(input, setNames(input, c("to", "from"))) |>
subset(to != "start")
edges <- with(input, split(to, from))
nodes <- with(input, unique(c(from, to)))
visited0 <- setNames(rep(FALSE, length(nodes)), nodes)
visited0[nodes == toupper(nodes)] <- NA
rec <- function(node = "start", visited = visited0, extra) {
if(isTRUE(visited[node])) {
if (!extra) return(0)
visited[node] <- FALSE
extra <- FALSE
}
if(node == "end") return(1)
visited[node] <- !visited[node]
sum(sapply(edges[[node]], rec, visited, extra))
}
part1 <- rec(extra = FALSE)
part2 <- rec(extra = TRUE)
list(part1 = part1, part2 = part2)
}
day13
function() {
# data
file <- system.file("extdata/day13.txt", package = "adventofcode2021")
coords1 <- coords2 <- na.omit(unglue::unglue_data(readLines(file), "{x},{y}", convert = TRUE))
x_folds <- na.omit(unglue::unglue_vec(readLines(file), "fold along x={val}", convert = TRUE))
y_folds <- na.omit(unglue::unglue_vec(readLines(file), "fold along y={val}", convert = TRUE))
# part 1
coords1$x <- abs(x_folds[1] - coords1$x) - 1
part1 <- nrow(unique(coords1))
# part 2
for (x in x_folds) {
coords2$x <- abs(x - coords2$x) - 1
}
for (y in y_folds) {
coords2$y <- abs(y - coords2$y) - 1
}
coords2 <- unique(coords2)
plot(transform(coords2, x = -x))
list(part1 = part1, part2 = NULL)
}
day14
function() {
# data
library(tidyverse)
file <- system.file("extdata/day14.txt", package = "adventofcode2021")
input <- readLines(file)
pairs <- tibble(
from = substring(input[1], 1:(nchar(input[1]) - 1), 2:nchar(input[1])),
n = 1)
first_letter <- substr(input[1], 1, 1)
mapper <-
unglue::unglue_data(input[-(1:2)], "{from} -> {to}") %>%
mutate(to = pmap(list(from, to), ~ c(
paste0(substr(.x, 1, 1), .y),
paste0(.y, substr(.x, 2, 2))))) %>%
unnest(to)
solve <- function(steps) {
for (i in 1:steps) {
pairs <-
left_join(pairs, mapper, by = "from") %>%
count(from = to, wt = n)
}
counts <-
pairs %>%
separate(from, c("from1", "from2"), sep = 1) %>%
count(letter = from2, wt = n) %>%
mutate(n = ifelse(letter == first_letter, n+1, n))
format(max(counts$n) - min(counts$n), scientific = FALSE)
}
part1 <- solve(10)
part2 <- solve(40)
list(part1 = part1, part2 = NULL)
}
day15
function() {
# data
library(tidyverse)
file <- system.file("extdata/day15.txt", package = "adventofcode2021")
input_mat <- do.call(rbind, lapply(strsplit(readLines(file), ""), as.numeric))
solve <- function(input_mat) {
# build walls of Inf simulating cells that cannot have their score improved
input_mat <- cbind(Inf, rbind(Inf, input_mat, Inf), Inf)
n_rows <- nrow(input_mat)
# start point
points <- c(n_rows + 2)
input_vec <- scores <- c(input_mat)
# at first we only know the lowest score to 1st cell is 0
scores[] <- Inf
scores[points] <- 0
# keep going if scores improve
while (length(points)) {
old_scores <- scores
# check if we can improve a score in any of the 4 directions
for (delta in c(+1, -1, +n_rows, -n_rows)) {
new_scores <- scores
new_scores[points + delta] <- scores[points] + input_vec[points + delta]
scores <- pmin(scores, new_scores) # keep best scores only
}
points <- which(scores != old_scores)
}
scores[length(scores)-n_rows-1]
}
# part1
part1 <- solve(input_mat)
# part2
input_mat2 <- do.call(rbind, replicate(5, input_mat, simplify = F))
input_mat2 <- do.call(cbind, replicate(5, input_mat2, simplify = F))
additions <- (col(input_mat2) -1) %/% ncol(input_mat) + (row(input_mat2) -1) %/% nrow(input_mat)
input_mat2 <- (input_mat2 + additions - 1) %% 9 + 1
part2 <- solve(input_mat2)
list(part1 = part1, part2 = NULL)
}
day16
function() {
# data
library(tidyverse)
file <- system.file("extdata/day16.txt", package = "adventofcode2021")
mapper <- setNames(
sapply(0:15, \(x) substr(paste(rev(as.integer(intToBits(x))), collapse=""), 29, 32)),
c(0:9, LETTERS[1:6]))
bin <- paste(mapper[strsplit(readLines(file), "")[[1]]], collapse = "")
solve <- function(bin, packet_pos = 1, max_pos = 1) {
len <- nchar(bin)
version <- strtoi(substr(bin, 1, 3), base = 2)
type <- strtoi(substr(bin, 4, 6), base = 2)
if(type == 4) {
split_remainder <- strsplit(bin, "")[[1]][-(1:6)]
n_litteral <-
suppressWarnings(which.min(split_remainder == 1 | c(F, T, T, T, T)) + 4)
value <- split_remainder[1:n_litteral][c(F, T, T, T, T)]
value <- sum((value==1)*2^(rev(seq_along(value))-1))
remainder <- substr(bin, 6 + n_litteral + 1, len)
len <- len - nchar(remainder)
subpackets <- NULL
sum_of_versions <- version
} else {
length_type <- substr(bin, 7, 7)
if(length_type == 0) {
subpackets_length <- strtoi(substr(bin, 7+1, 7+15), base = 2)
subpackets_bin <- substr(bin, 7+15+1, 7+15+subpackets_length)
# we have a limit on chars but not on number of subpackets
subpackets <- solve(subpackets_bin, packet_pos = 1, max_pos = Inf)
remainder <- substr(bin, 8+15+subpackets_length, len)
len <- len - nchar(remainder)
} else {
subpackets_n <- strtoi(substr(bin, 7+1, 7+11), base = 2)
# we have a limit on number of subpackets, not on chars
subpackets_bin <- substr(bin, 7+11+1, len)
subpackets <- solve(subpackets_bin, packet_pos = 1, max_pos = subpackets_n)
covered_len <- 7 + 11 + sum(sapply(subpackets, \(x) x$len))
remainder <- substr(bin, covered_len + 1, len)
len <- covered_len
}
value <- switch(
as.character(type),
"0" = sum(sapply(subpackets, \(x) x$value)),
"1" = prod(sapply(subpackets, \(x) x$value)),
"2" = min(sapply(subpackets, \(x) x$value)),
"3" = max(sapply(subpackets, \(x) x$value)),
"5" = subpackets[[1]]$value > subpackets[[2]]$value,
"6" = subpackets[[1]]$value < subpackets[[2]]$value,
"7" = subpackets[[1]]$value == subpackets[[2]]$value
)
sum_of_versions <- version + sum(sapply(subpackets, \(x) x$sum_of_versions))
}
# 1st subpacket
res <- list(list(
value = value,
len = len,
subpackets = subpackets,
sum_of_versions = sum_of_versions))
# other subpackets
if(packet_pos != max_pos && remainder != "" && !grepl("^0+$", remainder)) {
res <- c(res, solve(remainder, packet_pos = packet_pos + 1, max_pos = max_pos))
}
res
}
packet1 <- solve(bin)[[1]]
part1 <- packet1$sum_of_versions
part2 <- packet1$value
list(part1 = part1, part2 = NULL) # 246225449979
}
day17
function() {
# data
library(tidyverse)
file <- system.file("extdata/day17.txt", package = "adventofcode2021")
input <- unglue::unglue_data(
readLines(file),
"target area: x={x_min}..{x_max}, y={y_min}..{y_max}",
convert = TRUE)
# part1
# we want to in one step as deep as allowed
# it also takes vy steps to go to the top, since we take back one unit per step
# and 1+..+n is n*(n-1)/2
n <- vy_max <- -input$y_min - 1
part1 <- n * vy_max - n*(n-1)/2
# part2 tidy
library(tidyverse)
max_steps <- 2*vy_max+2
# all combinations that would work vertically
y2 <-
crossing(n = 1:max_steps, vy = input$y_min:vy_max) %>%
mutate(y = n * vy - n^2/2 + n/2) %>%
filter(y >= input$y_min & y <= input$y_max)
# all combinations that would work horizontally
x2 <-
crossing(n = 1:max_steps, vx = 1:input$x_max) %>%
with_groups("vx", mutate, x = cummax(n * vx - n^2/2 + n/2)) %>%
filter(x >= input$x_min & x <= input$x_max)
# combine and count
part2 <-
inner_join(x2, y2, by = "n") %>%
distinct(vx, vy) %>%
nrow()
#---------------------------------------------------------------------------
# part2 base
max_steps <- 2*vy_max+2
n_seq <- 1: max_steps
# all combinations that would york vertically
y <- do.call(rbind, lapply(input$y_min:vy_max, function(vy) {
data.frame(vy, n = n_seq, y = n_seq * vy - n_seq^2/2 + n_seq/2) |>
subset(y >= input$y_min & y <= input$y_max)
}))
# all combinations that would work horizontally
x <- do.call(rbind, lapply(1:input$x_max, function(vx) {
data.frame(vx, n = n_seq, x = cummax(n_seq * vx - n_seq^2/2 + n_seq/2)) |>
subset(x >= input$x_min & x <= input$x_max)
}))
# combine and count
part2 <-
merge(x, y, by = "n")[c("vx", "vy")] |>
unique() |>
nrow()
list(part1 = part1, part2 = NULL) # 246225449979
}
day18
function() {
# data
library(tidyverse)
file <- system.file("extdata/day18.txt", package = "adventofcode2021")
add_pair <- function(x, y) {
snail_num <- paste0("[", x, ",", y, "]")
chars <- strsplit(snail_num, "")[[1]] # only 1 digit nums at this stage
repeat {
first_5th_bracket <- which(cumsum(chars == "[") - cumsum(chars == "]")== 5)[1]
all_num_pos <- grep("\\d", chars)
if(!is.na(first_5th_bracket)) {
# explode
before_bracket <- which(grep("\\d", chars) > first_5th_bracket)[1] - 1
num_pos <- all_num_pos[before_bracket + (0:3)]
if(before_bracket == 0) num_pos <- c(NA, num_pos)
if(!is.na(num_pos[1]))
chars[num_pos[1]] <- as.numeric(chars[num_pos[1]]) + as.numeric(chars[num_pos[2]])
if(!is.na(num_pos[4]))
chars[num_pos[4]] <- as.numeric(chars[num_pos[4]]) + as.numeric(chars[num_pos[3]])
chars <- c(chars[1:(first_5th_bracket-1)], "0", chars[(first_5th_bracket+5):length(chars)])
next
}
all_nums <- as.numeric(chars[all_num_pos])
first_big_num <- all_num_pos[all_nums >= 10][1]
if(!is.na(first_big_num)) {
#split
num <- all_nums[all_nums >= 10][1]
chars <- c(chars[1:(first_big_num-1)], "[", floor(num/2), "," , ceiling(num/2), "]", chars[(first_big_num+1):length(chars)])
next
}
break
}
paste(chars, collapse = "")
}
# part1
input <- readLines(file)
reduced <- Reduce(add_pair, input)
reduced_call <- gsub("\\[", "magn(", reduced)
reduced_call <- gsub("\\]", ")", reduced_call)
magn <- function(x, y) 3 * x + 2 * y
part1 <- eval(str2lang(reduced_call))
# part 2
grid <- merge(input, input, by = NULL) |> subset(x != y)
part2 <- with(grid, {
reduced <- mapply(add_pair, x, y)
reduced_call <- gsub("\\[", "magn(", reduced)
reduced_call <- gsub("\\]", ")", reduced_call)
max(sapply(parse(text=reduced_call), eval))
})
list(part1 = part1, part2 = NULL)
}
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