Kara Woo @karawoo.com · 08/12/2025Day 8 was very easy with igraph and #rstats built-in distance matrix function. #adventofcode 070
Kara Woo @karawoo.com · 08/12/2025My day 7 solution started out way more complicated (and, for part 2, just wrong). Had to come back to it the next day to realize a much simpler way. #adventofcode #rstats 150
Kara Woo @karawoo.com · 08/12/2025Day 6: the first #adventofcode puzzle I've done where the bulk of the puzzle was parsing the input data. I enjoyed this one a lot! #rstats 120
Kara Woo @karawoo.com · 05/12/2025I think day 5 has been my favorite so far. Also got my first `vector memory limit reached` error of the year. #adventofcode #rstats 160
Kara Woo @karawoo.com · 05/12/2025Day 4. Had an inscrutable bug in part 2 for the longest time; eventually scrapped it and rewrote it in almost the same way, and this time it worked 🤷♀️ #adventofcode #rstats 430
Kara Woo @karawoo.com · 05/12/2025Catching up on sharing my #adventofcode solutions in #rstats. Here's day 1; part 2 was trickier than I expected for the first day, but I got to a solution I'm pretty happy with. github.com/karawoo/adve... 2240
Kara Woo @karawoo.com · 07/04/2025I don't think there is a global setting but you can do it in channel-level settings 100
Kara Woo @karawoo.com · 26/01/2025Duck fat fried rice with chinese sausage and leftover duck confit 1290
Kara Woo @karawoo.com · 12/12/2024This is officially the farthest I've ever gotten in #adventofcode 0391
Kara Woo @karawoo.com · 12/12/2024Day 11: was way overcomplicating part 2 last night, but got it quickly with fresh eyes today. #adventofcode #rstats 0161
Kara Woo @karawoo.com · 10/12/2024Didn't have time to figure out my bug in 9.2, but I'm back with an igraph solution for day 10. Joined every index of the matrix, filtered for ones that were adjacent and where the value is 1 + current value, then used subcomponent() for part 1 and all_simple_paths() for part 2. #adventofcode #rstats 3130
Kara Woo @karawoo.com · 07/12/2024Day 7 of #adventofcode in #rstats was a lot easier than day 6 for me, though I'm sure there are more efficient solutions than what I wrote. `purrr::reduce2()` was super handy for this one. 2180
Kara Woo @karawoo.com · 04/12/2024My solution to day 4 of #adventofcode in #rstats. Lots of apply()/mapply() in this one. 3340
Kara Woo @karawoo.com · 03/12/2024Day 3 of #adventofcode in #rstats. Got hung up on part 2 at first because I was treating each line as its own program instead of part of one whole. 4260
Kara Woo @karawoo.com · 20/11/2024And a hike to Murhut Falls. The drive to the trailhead was as pretty as the hike itself. 070
Kara Woo @karawoo.com · 08/12/2023I always like to do at least one #adventofcode puzzle with R6, here's my solution for day 8 #rstats 010
Kara Woo @karawoo.com · 07/12/2023R's ordered factors were handy for day 7 of #adventofcode. #rstats 020
Kara Woo @karawoo.com · 06/12/2023I was silly not to use vectorized math in my first pass, so went back and simplified my day 6 solution. #adventofcode #rstats 000
Kara Woo @karawoo.com · 06/12/2023Day 6 of #adventofcode in #rstats, thankfully an easier one today 120
Kara Woo @karawoo.com · 05/12/2023My part 1 solution for day 5 of #adventofcode in #rstats. After a few false starts I think I know what approach I'd take for part 2, but I'm probably skipping that one. 120
Kara Woo @karawoo.com · 04/12/2023This is most likely due to antialiasing behavior of the graphics device, and different ones handle it differently. There is not much ggplot can do. For this case, quartz looks ok (i.e. ggsave(... device = png, type = "quartz")) 230
Kara Woo @karawoo.com · 04/12/2023Day 4 of #adventofcode in #rstats. mapply() for part 1, loop for part 2. 000
Kara Woo @karawoo.com · 01/12/2023Extremely rude to make me use lookaheads on day 1 #adventofcode 070
Kara Woo @karawoo.com · 21/09/2023I kept waiting for a Hyatt Regency sticker drop at #positconf2023, but alas no luck. 081
![Screenshot of the following code:
library("dplyr")
library("igraph")
dat <- read.table("input08.txt", sep = ",", col.names = c("x", "y", "z"))
dm <- as.matrix(dist(dat, method = "euclidean"))
xy <- t(combn(rownames(dat), 2))
dm_df <- data.frame(xy, dist = dm[xy]) |>
arrange(dist)
g <- make_empty_graph(n = nrow(dat), directed = FALSE)
## part 1
n <- 1000
for (i in seq_len(n)) {
g <- add_edges(g, c(dm_df[i, "X1"], dm_df[i, "X2"]))
}
prod(head(sort(components(g)$csize, decreasing = TRUE), 3))
## part 2
i <- n # continue where we left off on the loop above
while (!is_connected(g)) {
i <- i + 1
g <- add_edges(g, c(dm_df[i, "X1"], dm_df[i, "X2"]))
}
prod(dat[c(dm_df[i, "X1"], dm_df[i, "X2"]), "x"])](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihquvl2ftgcfheveeknpwrpndb7bndsmz4bimkynzfegl7fgurlgq)
![Screenshot of the following code:
library("readr")
options(scipen = 9999)
file <- "input07.txt"
dat <- read_fwf(
file,
col_positions = fwf_widths(rep(1, nchar(readLines(file)[1])))
) |>
as.matrix()
count <- 0
tl <- vector(mode = "numeric", length = ncol(dat))
tl[which(dat == "S", arr.ind = TRUE)[, "col"]] <- 1
for (row in seq_len(nrow(dat))) {
for (col in seq_along(dat[row, ])) {
if (dat[row, col] == "^") {
if (tl[col] > 0) {
count <- count + 1
tl[col - 1] <- tl[col - 1] + tl[col]
tl[col + 1] <- tl[col + 1] + tl[col]
tl[col] <- 0
}
}
}
}
## part 1
count
## part 2
sum(tl)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicgkh56ikumyer4eupznzx73nfqewy6n5vunrg2q5mdddb36tq7we)
![Screenshot of the following code:
library("readr")
library("purrr")
library("dplyr")
options(scipen = 9999)
file <- "input06.txt"
orig <- readLines(file)
ncol <- length(strsplit(orig[[1]], "\\s+")[[1]])
## part 1
dat1 <- read_fwf(file, n_max = length(orig) - 1) |>
mutate(across(everything(), as.numeric))
ops <- tail(orig, 1) |>
strsplit("\\s+")
ops <- ops[[1]]
math <- function(x, op) {
init <- ifelse(op == "*", 1, 0)
Reduce(function(x, y) do.call(op, as.list(c(x, y))), x = x, init = init)
}
sum(mapply(math, dat1, ops))
## part 2
# read the data in one character per column
dat2 <- read_fwf(file, col_positions = fwf_widths(rep(1, max(nchar(orig)))))
dat2 <- dat2[-nrow(dat2), ]
# split into groups based on where there's a column of all NAs
seps <- map_dbl(dat2, ~ all(is.na(.x)))
splits <- cumsum(c(1, diff(seps) != 0))
split_problems <- split.default(dat2, splits) |>
keep(~ !all(is.na(.x)))
ceph_math <- function(x, op) {
vals <- as.list(x) |>
map(~ paste0(na.omit(.x), collapse = "")) |>
map_dbl(as.numeric)
math(vals, op)
}
sum(mapply(ceph_math, split_problems, ops))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreie3tl2styhiwyx6mxaseod37ttmugl7dt2zsqgtkbmsg5fffj3gle)
![Screenshot of the following code:
dat <- readLines("input05.txt")
ranges <- dat[1:(which(dat == "") - 1)] |>
strsplit("-") |>
lapply(as.numeric)
ingredients <- as.numeric(dat[(which(dat == "") + 1):length(dat)])
## part 1
count <- 0
for (i in ingredients) {
for (j in ranges) {
if (i >= j[1] && i <= j[2]) {
count <- count + 1
break
}
}
}
count
## part 2
sorted_ranges <- ranges[order(sapply(ranges, `[[`, 1))]
highest <- 0
count <- 0
for (i in sorted_ranges) {
if (i[2] <= highest) {
next
} else if (i[1] > highest) {
count <- count + (i[2] - i[1]) + 1
} else {
count <- count + (i[2] - (highest))
}
if (i[2] > highest) {
highest <- i[2]
}
}
count](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreid2r4332uq6xihy3qxgcbnwtutiwlk5vrmkfocnpc2462vuf37hmu)
![Screenshot of the following code:
library("tidyverse")
file <- "input04.txt"
dat <- read_fwf(
file,
col_positions = fwf_widths(rep(1, nchar(readLines(file, n = 1))))
) |>
as.matrix()
oob <- function(x, dat) {
x == 0 | x > max(dim(dat)) # assumes square matrix
}
get_neighbors <- function(row, col, dat) {
x <- row
y <- col
possible <- list(
tl = c(row - 1, col - 1),
t = c(row - 1, col),
tr = c(row - 1, col + 1),
l = c(row, col - 1),
r = c(row, col + 1),
bl = c(row + 1, col - 1),
b = c(row + 1, col),
br = c(row + 1, col + 1)
)
neighbors <- do.call(rbind, possible)
colnames(neighbors) <- c("row", "col")
neighbors[!oob(neighbors[1, ], dat) && !oob(neighbors[2, ], dat), ]
}
is_movable <- function(neighbors, dat) {
sum(dat[as.matrix(neighbors)] == "@") < 4
}
rolls <- which(dat == "@")
rolls_xy <- arrayInd(rolls, dim(dat))
neighbors <- apply(rolls_xy, 1, function(x) get_neighbors(x[1], x[2], dat))
## part 1
neighbors |>
map_lgl(is_movable, dat) |>
sum()
## part 2
clear <- function(rolls, neighbors, dat) {
moved <- neighbors |>
map_lgl(is_movable, dat)
dat[rolls[moved]] <- "."
if (any(moved)) {
clear(rolls[!moved], neighbors[!moved], dat)
} else {
return(dat)
}
}
sum(dat == "@") - sum(clear(rolls, neighbors, dat) == "@")](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreidou7gwksiajgzsmjoxaucz4p3edsnabtzbh742kkdvzqlgol4yim)
![Screenshot of the following R code:
library("purrr")
dat <- readLines("input11.txt") |>
strsplit(" ")
dat <- as.numeric(dat[[1]])
change <- function(stone) {
char <- as.character(stone)
if (stone == 0) {
return(1)
} else if (nchar(char) %% 2 == 0) {
return(
c(
as.numeric(substr(char, 1, nchar(char) / 2)),
as.numeric(substr(char, nchar(char) / 2 + 1, nchar(char)))
)
)
} else {
return(stone * 2024)
}
}
blink <- function(dat, times) {
x <- table(dat)
for (i in seq_len(times)) {
tmp <- imap(x, function(x, idx) {
new <- change(as.numeric(idx))
setNames(rep(x, length(new)), new)
}) |>
unname() |>
unlist()
x <- tapply(tmp, names(tmp), sum)
}
x
}
## part 1
sum(blink(dat, 25))
## part 2
sum(blink(dat, 75))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicon6cjs5qzl76fjplixfprxrqeo226ouuekghw44crojkmvlld5e)
![screenshot of the following R code:
library("readr")
library("tidyverse")
library("igraph")
dat <- read_fwf(
"input10.txt",
col_positions = fwf_widths(rep(1, nchar(readLines("input10.txt", n = 1))))
) |>
as.matrix()
## Create graph where each node is connected to adjacent squares in the matrix
## that have a value of n+1
long_dat <- as.data.frame.table(dat) |>
rename(row = Var1, col = Var2, value = Freq) |>
mutate(id = paste0(row, ",", col))
dat_adj <- expand_grid(x = long_dat$id, y = long_dat$id) |>
left_join(long_dat, by = join_by(x == id)) |>
left_join(long_dat, by = join_by(y == id)) |>
mutate(across(matches("^(row|col)"), as.numeric)) |>
filter(
abs(col.y - col.x) == 1 & row.y == row.x |
abs(row.y - row.x) == 1 & col.y == col.x
) |>
filter(value.y - value.x == 1)
g <- graph_from_data_frame(
dat_adj[, c("x", "y")],
vertices = unique(long_dat[, c("id", "value")])
)
starts <- which(vertex_attr(g, "value") == 0)
## part 1
count_9s <- function(start, g) {
sum(vertex_attr(g, "value", subcomponent(g, start, "out")) == 9)
}
map_dbl(starts, count_9s, g) |>
sum()
## part 2
count_paths <- function(start, g) {
sub <- subcomponent(g, start, "out")
ends <- sub[which(sub$value == 9)]
paths <- 0
if (length(ends) > 0) {
for (i in seq_along(ends)) {
paths <- paths + length(all_simple_paths(g, start, ends[i]))
}
}
paths
}
map_dbl(starts, count_paths, g) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihb7oztipeu7kvu6gkmkrnudkw4rpcter2nw5tnjjs3zyuintgcyu)
![Screenshot of the following R code:
library("stringr")
library("purrr")
library("gtools")
library("parallel")
library("parallelly")
dat <- readLines("input07.txt") |>
str_split(":?\\s") |>
map(as.numeric)
results <- map(dat, `[[`, 1)
eqs <- map(dat, \(x) x[2:length(x)])
calculate <- function(x, y, fun = c("sum", "prod", "paste0")) {
as.numeric(do.call(fun, list(x, y)))
}
find_true_eq <- function(input, result, operators) {
perms <- permutations(
length(operators),
length(input) - 1,
operators,
repeats.allowed = TRUE
)
for (i in seq_len(nrow(perms))) {
output <- reduce2(input, perms[i, ], calculate)
if (isTRUE(output == result)) {
return(result)
}
}
}
## part 1
p1 <- mapply(
find_true_eq,
eqs,
results,
MoreArgs = list(operators = c("sum", "prod"))
)
sum(unlist(p1))
## part 2
p2 <- mcmapply(
find_true_eq,
eqs,
results,
MoreArgs = list(operators = c("sum", "prod", "paste0")),
mc.cores = availableCores()
)
sum(unlist(p2))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreigvndxagqffcmvraldh6hne2m3c6eenbj5tj2hwdgjwrryzx4qbbq)
![Screenshot of the following R code:
library("stringr")
library("readr")
library("purrr")
dat <- read_fwf("input04.txt", col_positions = fwf_widths(rep(1, 140)))|>
as.matrix()
## part 1
## get horizontal, vertical, and diagonal lines in the matrix
h <- apply(dat, 1, paste, collapse = "")
v <- apply(dat, 2, paste, collapse = "")
d1 <- row(dat) - col(dat)
d2 <- row(dat) + col(dat)
diag1 <- split(dat, d1) |> map_chr(paste, collapse = "")
diag2 <- split(dat, d2) |> map_chr(paste, collapse = "")
all_ways <- c(h, v, diag1, diag2)
sum(str_count(all_ways, "XMAS"), str_count(all_ways, "SAMX"))
## part 2
## find the indices of the letter A when it's not in the outer rows & columns
a <- which(dat == "A", arr.ind = TRUE)
a_interior <- a[apply(a, 1, \(x) !any(x %in% c(1, 140))), ]
## get the diagonals crossing each A
get_diagonals <- function(idx, dat) {
rows <- seq(idx["row"] - 1, idx["row"] + 1)
cols <- seq(idx["col"] - 1, idx["col"] + 1)
diags <- list(
mapply(\(x, y) dat[x, y], rows, cols),
mapply(\(x, y) dat[x, y], rows, rev(cols))
)
map_chr(diags, paste, collapse = "")
}
diags <- apply(a_interior, 1, get_diagonals, dat = dat, simplify = FALSE)
sum(map_lgl(diags, \(x) all(x %in% c("MAS", "SAM"))))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreifrh65ionrzfb5egfux3mwalzauunp6f4rra7wg3h5cj5edzgl4bm)
![Screenshot of the following R code:
library("stringr")
library("purrr")
dat <- readLines("input03.txt")
run_program <- function(data) {
str_extract_all(data, "(?<=mul\\()\\d{1,3},\\d{1,3}(?=\\))") |>
unlist() |>
str_split(",") |>
map_dbl(\(x) prod(as.numeric(x))) |>
sum()
}
## part 1
run_program(dat)
## part 2
str_split(paste(dat, collapse = ""), "do\\(\\)")[[1]] |>
str_split_i("(don't\\(\\)|$)", 1) |>
run_program()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreigxgdpb5f7vfvadryg5gxgvafbuadsl22bpblp6shxkbxwc2vjhve)
![Screenshot of the following R code:
library("readr")
library("stringr")
dat <- read_lines("input06.txt") %>%
str_extract_all("\\d+") %>%
lapply(as.numeric) %>%
setNames(c("time", "duration"))
race_result <- function(duration) {
hold_time <- 0:duration
move_time <- duration - hold_time
hold_time * move_time
}
get_winning_times <- function(poss_results, record) {
sum(poss_results > record)
}
get_answer <- function(dat) {
poss_results <- lapply(dat[["time"]], race_result)
prod(mapply(get_winning_times, poss_results, dat[["duration"]]))
}
## Part 1
get_answer(dat)
## Part 2
dat <- lapply(dat, function(x) as.numeric(paste0(x, collapse = "")))
get_answer(dat)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreifag3dirzsn7k7nveoep6hhqy4atielr6azt47tzin4nfhpfnt3ym)
![library("readr")
library("stringr")
library("purrr")
dat_orig <- read_file("input05.txt") %>%
str_split("\\n+")
dat_orig <- dat_orig[[1]][!dat_orig[[1]] == ""]
split_data <- function(x) {
split_points <- which(c(1, diff(cumsum(str_detect(x, "map")))) == 1)
dat_list <- split(x, cumsum(seq_along(x) %in% split_points))
names(dat_list)[[1]] <- "seeds:"
dat_list[[1]] <- str_remove(dat_list[[1]], "seeds: ")
for (i in 2:length(dat_list)) {
names(dat_list)[[i]] <- dat_list[[i]][[1]]
dat_list[[i]] <- dat_list[[i]][-1]
}
dat_list
}
dat <- dat_orig %>%
split_data() %>%
map(str_split, " +") %>%
map_depth(.depth = 2, as.numeric)
map_input_to_dest <- function(input, map) {
result <- input
for (i in map) {
if (i[[2]] <= input && input <= i[[2]] + i[[3]]) {
result <- i[[1]] + (input - i[[2]])
break
}
}
result
}
results <- vector(mode = "list", length = length(dat))
results[[1]] <- dat[[1]][[1]]
for (i in 2:length(dat)) {
results[[i]] <- vappl](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibf6iko3d7u7y37w6pzgwln5eszn7b36cy4nt2hmmwiyjxwxyeop4)
![Screenshot of the following R code
library("readr")
library("stringr")
dat <- read_lines("input04.txt")
nums <- str_remove_all(dat, "Card +\\d+: +") %>%
str_split(" \\| +") %>%
lapply(function(x) lapply(str_split(x, " +"), as.numeric))
winning <- lapply(nums, `[[`, 1)
cards <- lapply(nums, `[[`, 2)
## Part 1
score <- function(card, winning) {
any(card %in% winning) * 2^(sum(card %in% winning) - 1)
}
sum(mapply(score, cards, winning))
## Part 2
copies <- rep(1, length(cards))
score2 <- function(copies, i, cards, winning) {
n_copies <- copies[[i]]
n_new <- sum(cards[[i]] %in% winning[[i]])
if (n_new > 0) {
copies[(i+1):(i+n_new)] <- copies[(i+1):(i+n_new)] + n_copies
}
copies
}
for (i in seq_along(copies)) {
copies <- score2(copies, i, cards, winning)
}
sum(copies)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreiexdhucgxs7ue3q5ooinomrj2t5yjm5cqsmk5aflfresc2pk6r42i)
![Screenshot of the following code:
library("purrr")
options(scipen = 9999)
dat <- readLines("input03.txt") |>
strsplit("")
joltage <- function(bank, n) {
if (n > 0) {
candidates <- head(bank, length(bank) - n + 1)
i <- which.max(candidates)
paste0(bank[i], joltage(bank[(i + 1):length(bank)], n = n - 1))
}
}
## part 1
map_dbl(dat, ~ as.numeric(joltage(.x, n = 2))) |>
sum()
## part 2
map_dbl(dat, ~ as.numeric(joltage(.x, n = 12))) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicienemuhrysulljy777fs7iscbrc2kh3fdhxwq7kza2km2bspmpm)
![Screenshot of the following code:
library("stringr")
library("purrr")
dat <- readLines("input02.txt")
# discard any that have more than length/2 unique digits
candidate <- function(val) {
val_str <- str_split(val, "")[[1]]
length(unique(val_str)) <= (length(val_str) / 2)
}
to_check <- str_split(dat, ",")[[1]] |>
str_split("-") |>
map(~ seq(.x[1], .x[2])) |>
unlist() |>
keep(candidate)
## part 1
invalid1 <- function(x) {
x <- str_split(x, "")[[1]]
if (identical(head(x, length(x) / 2), tail(x, length(x) / 2))) {
as.numeric(paste0(x, collapse = ""))
} else {
0
}
}
map_dbl(to_check, invalid1) |>
sum()
## part 2
## divide up string into pieces of length n
split_group_size <- function(string, n) {
x <- str_split(string, "")[[1]]
groups <- ceiling(seq_along(x) / n)
split(x, groups) |>
map(paste0, collapse = "")
}
invalid2 <- function(x) {
for (i in seq_len(nchar(x)) / 2) {
pieces <- split_group_size(x, i)
if (length(unique(unlist(pieces))) == 1) {
return(sum(as.numeric(x)))
}
}
0
}
## it's slowww
map_dbl(to_check, invalid2) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreib26fxkc2w5gh6ovxftt57onr67ozbvnlinvhghgwi5k5bjn6q2ea)
![Screenshot of the following text in green and yellow on a dark background:
[2024] 23*
[2023] 21*
[2022] 15*
[2021] 15*
[2020]
[2019]
[2018]
[2017]
[2016]
[2015]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreih5caipuc3trzkjhgetx6gdvazge7c4urdseg3y234oz5lchrcqh4)
![Screenshot of the following R code:
dat <- readLines("input05.txt")
rules <- dat[1:which(dat == "") - 1] |>
strsplit("\\|") |>
lapply(as.numeric)
updates <- dat[(which(dat == "") + 1):length(dat)] |>
strsplit(",") |>
lapply(as.numeric)
is_ok <- function(u, rules) {
for (rule in rules) {
if (isTRUE(which(u == rule[1]) > which(u == rule[2]))) {
return(FALSE)
}
}
TRUE
}
## part 1
sapply(updates, \(x) ifelse(is_ok(x, rules), x[ceiling(length(x) / 2)], 0)) |>
sum()
## part 2
bad <- updates[sapply(updates, \(x) !is_ok(x, rules))]
sum <- 0
for (update in bad) {
for (i in seq_len(length(update) - 1)) {
for (j in 2:length(update)) {
if (!is_ok(update[(j-1):j], rules)) {
update[(j-1):j] <- rev(update[(j-1):j])
}
}
}
sum <- sum + update[ceiling(length(update) / 2)]
}
sum](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibspp3w4n6di2zfde32r2d5aol4ecgurhmhmnup3hljhoweilyryq)
![Screenshot of the following R code:
library("purrr")
library("stringr")
dat <- readLines("input02.txt") %>%
str_extract_all("\\d+") %>%
map(as.numeric)
safe <- function(x, dampener = FALSE) {
d <- diff(x)
if (length(unique(sign(d))) > 1 || max(abs(d)) > 3 || min(abs(d)) < 1) {
if (dampener) {
return(any(map_lgl(seq_along(x), \(i) safe(x[-i]))))
} else {
return(FALSE)
}
}
TRUE
}
## part 1
sum(map_lgl(dat, safe))
## part 2
sum(map_lgl(dat, safe, dampener = TRUE))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreiepjoeo577pcovmmmk34cwr22l2mmml54ttvc3x7vcllzc4yxamxi)
![Screenshot of the following R code
library("readr")
library("stringr")
dat <- read_lines("input09.txt") %>%
str_split(" ") %>%
lapply(as.numeric)
get_next_val <- function(dat, dir = "forward") {
i <- 1
diffs <- list(dat)
while (!all(diffs[[i]] == 0)) {
i <- i + 1
diffs[[i]] <- diff(diffs[[i - 1]])
}
diffs <- rev(diffs)
for (i in 2:length(diffs)) {
if (dir == "forward") {
diffs[[i]] <- c(diffs[[i]], diffs[[i]][length(diffs[[i]])] + tail(diffs[[i - 1]], 1))
} else {
diffs[[i]] <- c(diffs[[i]][1] - head(diffs[[i - 1]], 1), diffs[[i]])
}
}
if (dir == "forward") {
return(tail(diffs[[length(diffs)]], 1))
} else {
return(head(diffs[[length(diffs)]], 1))
}
}
sum(vapply(dat, get_next_val, numeric(1), dir = "forward"))
sum(vapply(dat, get_next_val, numeric(1), dir = "backward"))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihjpnqtikho2idqtfqhb3uqtqud4atd5k6gcz3zgtphalfcgl4knu)
![Screenshot of the following R code:
library("readr")
library("stringr")
dat <- read_lines("input06.txt") %>%
str_extract_all("\\d+") %>%
lapply(as.numeric) %>%
setNames(c("time", "duration"))
race_result <- function(hold_time, duration) {
move_time <- duration - hold_time
hold_time * move_time
}
get_possible_results <- function(duration) {
vapply(0:duration, race_result, numeric(1), duration = duration)
}
get_winning_times <- function(poss_results, record) {
sum(poss_results > record)
}
## Part 1
poss_results <- lapply(dat[["time"]], get_possible_results)
prod(mapply(get_winning_times, poss_results, dat[["duration"]]))
## Part 2
dat2 <- lapply(dat, function(x) as.numeric(paste0(x, collapse = "")))
poss_results2 <- get_possible_results(dat2[["time"]])
prod(get_winning_times(poss_results2, dat2[["duration"]]))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibsxsuuwsxrd3vhx542w2jv7tgbrzp6jcxg3pxaolvcenswy3hofe)
![Screenshot of the following R code
library("readr")
library("stringr")
library("tidyverse")
dat <- read_lines("input01.txt")
## Part 1
str_extract_all(dat, "[[:digit:]]") %>%
vapply(
function(x) as.numeric(paste(x[1], x[length(x)], sep = "")),
double(1)
) %>%
sum()
## Part 2
char_to_num <- function(x) {
case_when(
x == "one" ~ "1",
x == "two" ~ "2",
x == "three" ~ "3",
x == "four" ~ "4",
x == "five" ~ "5",
x == "six" ~ "6",
x == "seven" ~ "7",
x == "eight" ~ "8",
x == "nine" ~ "9",
TRUE ~ x
)
}
str_match_all(
dat,
"(?=([[:digit:]]|one|two|three|four|five|six|seven|eight|nine))"
) %>%
lapply(function(x) x[, 2]) %>%
lapply(char_to_num) %>%
vapply(function(x) as.numeric(paste0(x[1], x[length(x)])), numeric(1)) %>%
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreieqsfjkn7cptzfl25g4gtfi2qyhihevu3sbz7nz4fbeiurwupgdci)
