Rasmus Bååth
Advent of Code is a fun creative coding challenge where there is a new coding challenge each of the 25 day leading up to Christmas. Here are my solutionions using R. I strive for few lines, clean solutions, and slooow performance :)
# Part 1
sum(floor(scan("input/1.txt") / 3) - 2)
## [1] 3263320
# Part 2
fuel_requirement <- function(masses) {
needed_fuels <- pmax(0, (floor(masses / 3) - 2))
if(all(needed_fuels == 0) ) {
0
} else {
sum(needed_fuels) + fuel_requirement(needed_fuels)
}
}
fuel_requirement(scan("input/1.txt"))
## [1] 4892135
# Part 1
library(tidyverse)
# A Hack to make vectors of the memory class zero indexed
as.memory <- function(x) {
class(x) <- "memory"
x
}
`[.memory` <- function(x, i) {
i <- i + 1
NextMethod()
}
`[<-.memory` <- function(x, i, value) {
i <- i + 1
NextMethod()
}
make_operator_op <- function(operator) {
function(memory, p) {
x1 <- memory[memory[p]]
x2 <- memory[memory[p + 1]]
memory[memory[p + 2]] <- operator(x1, x2)
list(memory = memory, p = p + 3)
}
}
ops <- list(
add = make_operator_op(`+`),
mutl = make_operator_op(`*`)
)
run <- function(memory) {
state <- list(memory = as.memory(memory), p = 0)
while(TRUE) {
opcode <- state$memory[state$p]
if(opcode == 99) break
state <- ops[[opcode]](state$memory, state$p + 1)
}
state
}
memory <- as.memory(scan("input/2.txt", sep = ","))
memory[1:2] <- c(12, 2)
run(memory)$memory[0]
## [1] 4690667
# Part 2
expand.grid(noun = 0:99, verb = 0:99) %>%
mutate(output = map2_dbl(noun, verb , ~ {
memory[1:2] <- c(.x, .y)
run(memory)$memory[0]
})) %>%
filter(output == 19690720) %>%
mutate(answer = 100 * noun + verb)
## noun verb output answer
## 1 62 55 19690720 6255
library(tidyverse)
input <- readLines("input/3.txt") %>%
str_split(",") %>%
map_dfr( ~ tibble(stretch = seq_along(.x), dir_length = .x), .id = "wire") %>%
extract(dir_length, c("direction", "length"), "([RUDL])(.+)", convert = TRUE)
input
## # A tibble: 602 x 4
## wire stretch direction length
## <chr> <int> <chr> <int>
## 1 1 1 R 995
## 2 1 2 U 671
## 3 1 3 R 852
## 4 1 4 U 741
## 5 1 5 R 347
## 6 1 6 U 539
## 7 1 7 R 324
## 8 1 8 U 865
## 9 1 9 R 839
## 10 1 10 U 885
## # … with 592 more rows
create_path <- function(input, positions = tibble(x = 0, y = 0)) {
if(nrow(input) == 0) return(positions)
direction <- input$direction[1]
length <- input$length[1]
x = positions$x[nrow(positions)]
y = positions$y[nrow(positions)]
new_positions <-
if(direction == "U") {
tibble(x, y = y + seq_len(length))
} else if(direction == "D") {
tibble(x, y = y - seq_len(length))
} else if(direction == "R") {
tibble(x = x + seq_len(length), y)
} else {
tibble(x = x - seq_len(length), y)
}
create_path(input[-1, ], rbind(positions, new_positions))
}
wire_paths <- input %>%
group_by(wire) %>%
group_modify(~ create_path(.x)) %>%
mutate(step = row_number() - 1) %>%
ungroup()
n_wires = n_distinct(wire_paths$wire)
closest_crossing <- wire_paths %>%
filter(x != 0 & y != 0) %>%
group_by(x, y) %>%
filter(n_distinct(wire) >= n_wires) %>%
mutate(distance = abs(x) + abs(y)) %>%
arrange(distance) %>%
head(1)
closest_crossing
## # A tibble: 1 x 5
## # Groups: x, y [1]
## wire x y step distance
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 1 562 -4757 96669 5319
ggplot(wire_paths, aes(x, y, color = wire)) +
geom_path() +
annotate("point", x = 0, y = 0) +
annotate("point", x = closest_crossing$x, y = closest_crossing$y)
# Part 2
closest_crossing <- wire_paths %>%
filter(x != 0 & y != 0) %>%
group_by(x, y) %>%
filter(n_distinct(wire) >= n_wires) %>%
group_by(wire, x, y) %>%
summarise(step = min(step)) %>%
group_by(x, y) %>%
summarise(total_steps = sum(step)) %>%
arrange(total_steps) %>%
head(1)
closest_crossing
## # A tibble: 1 x 3
## # Groups: x [1]
## x y total_steps
## <dbl> <dbl> <dbl>
## 1 562 -5065 122514
ggplot(wire_paths, aes(x, y, color = wire)) +
geom_path() +
annotate("point", x = 0, y = 0) +
annotate("point", x = closest_crossing$x, y = closest_crossing$y)
library(tidyverse)
# Part 1
136818:685979 %>%
str_split("") %>%
map(as.numeric) %>%
keep( ~any(rle(.x)$lengths >= 2)) %>%
keep( ~all(diff(.x) >= 0)) %>%
length()
## [1] 1919
# Part 2
136818:685979 %>%
str_split("") %>%
map(as.numeric) %>%
keep( ~any(rle(.x)$lengths == 2)) %>%
keep( ~all(diff(.x) >= 0)) %>%
length()
## [1] 1291
# Part 1
library(igraph)
orbits <- graph_from_data_frame(directed = FALSE,
read.delim("input/6.txt", sep = ")", header = FALSE))
sum(distances(orbits, to = "COM"))
## [1] 223251
# Part 2
distances(orbits, v="YOU",to = "SAN") - 2
## SAN
## YOU 430
library(tidyverse)
# Part 1
input = as.numeric(str_split(readLines("input/8.txt"), pattern = "")[[1]])
n_cols = 25
n_rows = 6
n_frames <- length(input) / (n_cols * n_rows)
image = expand_grid(frame = seq_len(n_frames), row = seq_len(n_rows), col = seq_len(n_cols)) %>%
mutate(digit = input)
image
## # A tibble: 15,000 x 4
## frame row col digit
## <int> <int> <int> <dbl>
## 1 1 1 1 2
## 2 1 1 2 2
## 3 1 1 3 2
## 4 1 1 4 2
## 5 1 1 5 2
## 6 1 1 6 2
## 7 1 1 7 2
## 8 1 1 8 2
## 9 1 1 9 2
## 10 1 1 10 2
## # … with 14,990 more rows
image %>%
count(frame, digit) %>%
pivot_wider(names_from = digit, values_from = n, names_prefix = "n_") %>%
arrange(n_0) %>%
head(1) %>%
mutate(answer = n_1 * n_2)
## # A tibble: 1 x 5
## frame n_0 n_1 n_2 answer
## <int> <int> <int> <int> <int>
## 1 6 4 14 132 1848
# Part 2
image %>%
filter(digit != 2) %>%
mutate(color = recode(digit, `0` = "black", `1` = "white")) %>%
arrange(desc(frame)) %>%
ggplot(aes(x = col, y = -row, fill = color)) +
geom_raster() +
scale_fill_identity()