drob-advent-of-code-2023-day-5.R

# My (NOT WORKING) solution to day 5 Part 2
library(tidyverse)
library(adventdrob)
library(intervals)
library(broom)

# Utility to turn Intervals::intervals into tibble
tidy.Intervals_full <- function(intervals) {
  intervals %>%
    as.data.frame() %>%
    setNames(c("start", "end")) %>%
    as_tibble()
}

d <- advent_input(5, 2023)

seed_ranges <- str_extract_all(d$x[[1]], "\\d+")[[1]] %>%
  as.numeric() %>%
  tibble(seed = .) %>%
  mutate(pair = (row_number() - 1) %/% 2) %>%
  group_by(pair) %>%
  mutate(key = c("start", "length")) %>%
  spread(key, seed) %>%
  mutate(end = start + length - 1) %>%
  select(-length)

maps <- d %>%
  slice(-1) %>%
  mutate(map_number = cumsum(str_detect(x, "map"))) %>%
  filter(!str_detect(x, "map")) %>%
  separate(x, c("dest_start", "source_start", "range_length"), convert = TRUE) %>%
  filter(!is.na(dest_start)) %>%
  mutate(source_end = source_start + range_length - 1) %>%
  select(-range_length)

# Create intervals::Intervals for each of the start-end ranges to get the "excluded from all" intervals
interval_maps <- maps %>%
  group_by(map_number) %>%
  # Hack: to ensure that we include the boundaries of the original intervals, make them 1 unit wider
  # Otherwise e.g. [60, 70] doesn't overlap with (70, 80)
  mutate(source_start = source_start - 1,
         source_end = source_end + 1) %>%
  summarize(intervals = list(Intervals(cbind(source_start, source_end))))

join_range <- function(source, i) {
  # Find the overlapping intervals, and adjust each 
  overlaps <- source %>%
    crossing(maps %>% filter(map_number == i)) %>%
    filter(start <= source_end, end >= source_start) %>%
    mutate(new_start = pmax(start, source_start) - source_start + dest_start,
           new_end = pmin(end, source_end) - source_start + dest_start)

  # Find intervals that don't overlap with *any* map using the Intervals package
  source_intervals = Intervals(source[c("start", "end")])
  mapping_intervals = interval_maps$intervals[[i]]
  non_overlap <- interval_difference(source_intervals, mapping_intervals)

  overlaps %>%
    select(start = new_start, end = new_end) %>%
    bind_rows(tidy(non_overlap))
}

# Run it with map_numbers 1-7
final_seed_ranges <- purrr::reduce(1:7, join_range, .init = seed_ranges)

final_seed_ranges %>%
  summarize(min(start))