Kara Woo
@karawoo.com
software engineer | #rstats | PDX | she/her
Day 8 was very easy with igraph and #rstats built-in distance matrix function. #adventofcode
![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@jpeg)
December 8, 2025 at 6:24 PM
Day 8 was very easy with igraph and #rstats built-in distance matrix function. #adventofcode
My 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
![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@jpeg)
December 8, 2025 at 6:22 PM
My 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
Day 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
![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@jpeg)
December 8, 2025 at 6:20 PM
Day 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
I think day 5 has been my favorite so far. Also got my first `vector memory limit reached` error of the year. #adventofcode #rstats
![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@jpeg)
December 5, 2025 at 7:18 PM
I think day 5 has been my favorite so far. Also got my first `vector memory limit reached` error of the year. #adventofcode #rstats
Day 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
![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@jpeg)
December 5, 2025 at 7:09 PM
Day 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
Quite pleased with my day 3. #adventofcode #rstats
![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@jpeg)
December 5, 2025 at 7:06 PM
Quite pleased with my day 3. #adventofcode #rstats
Day 2: not efficient but it works. #adventofcode #rstats
![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@jpeg)
December 5, 2025 at 6:54 PM
Day 2: not efficient but it works. #adventofcode #rstats
Catching 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...
github.com/karawoo/adve...
December 5, 2025 at 6:51 PM
Catching 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...
github.com/karawoo/adve...
thank you yes that answers my question
December 5, 2025 at 4:08 AM
thank you yes that answers my question
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)