Kara Woo
@karawoo.com
software engineer | #rstats | PDX | she/her
I don't think there is a global setting but you can do it in channel-level settings
April 7, 2025 at 4:26 PM
I don't think there is a global setting but you can do it in channel-level settings
Duck fat fried rice with chinese sausage and leftover duck confit
January 26, 2025 at 2:57 AM
Duck fat fried rice with chinese sausage and leftover duck confit
This is officially the farthest I've ever gotten in #adventofcode
![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@jpeg)
December 12, 2024 at 8:47 AM
This is officially the farthest I've ever gotten in #adventofcode
Day 11: was way overcomplicating part 2 last night, but got it quickly with fresh eyes today. #adventofcode #rstats
![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@jpeg)
December 12, 2024 at 5:04 AM
Day 11: was way overcomplicating part 2 last night, but got it quickly with fresh eyes today. #adventofcode #rstats
Didn'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
![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@jpeg)
December 10, 2024 at 3:15 PM
Didn'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
Day 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.
![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@jpeg)
December 7, 2024 at 6:41 AM
Day 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.
![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@jpeg)
My solution to day 4 of #adventofcode in #rstats. Lots of apply()/mapply() in this one.
![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@jpeg)
December 4, 2024 at 3:46 PM
My solution to day 4 of #adventofcode in #rstats. Lots of apply()/mapply() in this one.
Day 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.
![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@jpeg)
December 3, 2024 at 3:32 PM
Day 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.
My #rstats solution to #adventofcode day 2
![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@jpeg)
December 2, 2024 at 5:50 AM
My #rstats solution to #adventofcode day 2
it's #adventofcode time! here's my #rstats solution to day 1
December 1, 2024 at 8:13 AM
it's #adventofcode time! here's my #rstats solution to day 1
And a hike to Murhut Falls. The drive to the trailhead was as pretty as the hike itself.
November 20, 2024 at 10:17 PM
And a hike to Murhut Falls. The drive to the trailhead was as pretty as the hike itself.
A few from Port Townsend last weekend
November 20, 2024 at 10:09 PM
A few from Port Townsend last weekend
![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@jpeg)
I always like to do at least one #adventofcode puzzle with R6, here's my solution for day 8 #rstats
December 8, 2023 at 6:53 AM
I always like to do at least one #adventofcode puzzle with R6, here's my solution for day 8 #rstats
R's ordered factors were handy for day 7 of #adventofcode. #rstats
December 7, 2023 at 7:03 AM
R's ordered factors were handy for day 7 of #adventofcode. #rstats
I was silly not to use vectorized math in my first pass, so went back and simplified my day 6 solution. #adventofcode #rstats
![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@jpeg)
December 6, 2023 at 6:29 PM
I was silly not to use vectorized math in my first pass, so went back and simplified my day 6 solution. #adventofcode #rstats
Day 6 of #adventofcode in #rstats, thankfully an easier one today
![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@jpeg)
December 6, 2023 at 5:29 AM
Day 6 of #adventofcode in #rstats, thankfully an easier one today
My 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.
![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@jpeg)
December 5, 2023 at 5:12 PM
My 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.
This 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"))
December 4, 2023 at 7:07 PM
This 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"))
Day 4 of #adventofcode in #rstats. mapply() for part 1, loop for part 2.
![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@jpeg)
December 4, 2023 at 6:30 AM
Day 4 of #adventofcode in #rstats. mapply() for part 1, loop for part 2.
Extremely rude to make me use lookaheads on day 1 #adventofcode
![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@jpeg)
December 1, 2023 at 8:43 PM
Extremely rude to make me use lookaheads on day 1 #adventofcode
I kept waiting for a Hyatt Regency sticker drop at #positconf2023, but alas no luck.
September 21, 2023 at 5:52 PM
I kept waiting for a Hyatt Regency sticker drop at #positconf2023, but alas no luck.