aoc_2024/day_9.R at main · bcrossman/aoc_2024 · GitHub

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library(tidyverse)
input <- (readLines("inputs/input9.txt"))

data <-
  tibble(value = input) %>%
  separate_rows(value, sep = "") %>%
  filter(value != "") %>%
  mutate(
    value = as.integer(value),
  ) %>%
  rowid_to_column("index")

file_size <- data %>% filter(index %% 2 != 0)
free_space <- data %>% filter(index %% 2 == 0)

free_space_remaining <- free_space %>% mutate(assigned_index = NA_integer_)
output_list <- list()

# PART I

for (i in nrow(file_size):1) {
  # i <- 10
  # if(i == 5282){asd}

  current_index <- file_size$index[i]
  translated_index <- (current_index-1)/2
  current_value <- file_size$value[i]
  # print(i)
  # print(current_index)
  # print(free_space_remaining$index[1])

  assigned_rows <- free_space_remaining %>%
    mutate(cumulative_sum = cumsum(value)) %>%
    filter(cumulative_sum <= current_value) %>%
    mutate(assigned_index = current_index)

  if(nrow(assigned_rows)!=0 && max(assigned_rows$index)>current_index){

    assigned_rows <- free_space_remaining %>%
      filter(index<current_index) %>%
      mutate(assigned_index = current_index)

    assigned_rows <-
      assigned_rows %>%
      bind_rows(
       tibble(index = current_index, assigned_index = current_index, value = current_value- sum(assigned_rows$value))
      )
    output_list[[as.character(i)]] <- assigned_rows
    break}

  remaining_value <- current_value - sum(assigned_rows$value, na.rm = TRUE)

  if (remaining_value > 0) {
    partial_row <- free_space_remaining[nrow(assigned_rows) + 1, ]
    partial_row$value <- remaining_value
    partial_row$assigned_index <- current_index

    free_space_remaining <- free_space_remaining %>% filter(!(index %in% assigned_rows$index))

    free_space_remaining$value[1] <- free_space_remaining$value[1] - remaining_value
    assigned_rows <- bind_rows(assigned_rows, partial_row)

  }else{
    free_space_remaining <- free_space_remaining %>% filter(!(index %in% assigned_rows$index))
  }

  assigned_rows <- assigned_rows %>% select(-cumulative_sum)
  remaining_value_unprocessed <- current_value-sum(assigned_rows$value)

  output_list[[as.character(i)]] <- assigned_rows
  if(nrow(free_space_remaining)==0){break}
}
#
# if(remaining_value_unprocessed>0){
# last_file_size <- tibble(index = current_index, value = remaining_value_unprocessed)}

used_free_space <- bind_rows(output_list)

df <-
  file_size %>%
  filter(!(index %in% used_free_space$assigned_index)) %>%
  mutate(check_sum_1 = (index-1)/2) %>%
  bind_rows(used_free_space) %>%
  mutate(check_sum_2 = (assigned_index-1)/2) %>%
  arrange(index) %>%
  mutate(checksum = coalesce(check_sum_1, check_sum_2)) %>%
  filter(value !=0) %>%
  mutate(cumsum = cumsum(value)) %>%
  mutate(
    lag_cumsum = lag(cumsum, default = 0),
    multiplier = map2(lag_cumsum + 1, cumsum, `:`)
  ) %>% #View()
  select(-lag_cumsum) %>%
  unnest(multiplier) %>%
  mutate(multiplier = multiplier - 1)

# df %>% View()

df %>%
  mutate(product = checksum * multiplier) %>%
  mutate(cum_product = as.character(cumsum(product))) %>% #View()
  pull(product) %>%
  sum() %>% as.character()

## Part II
free_space_remaining <- free_space %>% mutate(assigned_index = NA_integer_)
output_list <- list()

for (i in nrow(file_size):1) {
  current_index <- file_size$index[i]
  translated_index <- (current_index-1)/2
  current_value <- file_size$value[i]
  possible <- free_space_remaining %>%
    filter(value >= current_value) %>%
    filter(index<current_index)

  if(nrow(possible)<1){next}

  assigned_rows <- possible %>%
    slice(1) %>%
    mutate(assigned_index = current_index)

  remaining_value <- sum(assigned_rows$value, na.rm = TRUE) - current_value

  if (remaining_value > 0) {
    free_space_remaining$value[free_space_remaining$index== assigned_rows$index] <- remaining_value
    assigned_rows$value <- current_value

    free_space_remaining <-
      free_space_remaining %>%
      bind_rows(
        tibble(index = current_index, value = current_value)) %>%
      arrange(index)
  }else{
    free_space_remaining <- free_space_remaining %>% filter(!(index %in% assigned_rows$index))

    free_space_remaining <-
      free_space_remaining %>%
      bind_rows(
        tibble(index = current_index, value = current_value)) %>%
      arrange(index)
  }
output_list[[as.character(i)]] <- assigned_rows
}
#
# if(remaining_value_unprocessed>0){
# last_file_size <- tibble(index = current_index, value = remaining_value_unprocessed)}

used_free_space <- bind_rows(output_list)

df <-
  file_size %>%
  filter(!(index %in% used_free_space$assigned_index)) %>%
  mutate(check_sum_1 = (index-1)/2) %>%
  bind_rows(used_free_space) %>%
  mutate(check_sum_2 = (assigned_index-1)/2) %>%
  mutate(index = as.numeric(index)) %>%
  bind_rows(free_space_remaining %>%
              mutate(check_sum_1 = 0) %>%
              mutate(index = as.numeric(index)+.1)) %>%
  arrange(index) %>%
  mutate(checksum = coalesce(check_sum_1, check_sum_2)) %>%
  filter(value !=0) %>%
  mutate(cumsum = cumsum(value)) %>%
  mutate(
    lag_cumsum = lag(cumsum, default = 0),
    multiplier = map2(lag_cumsum + 1, cumsum, `:`)
  ) %>% #View()
  select(-lag_cumsum) %>%
  unnest(multiplier) %>%
  mutate(multiplier = multiplier - 1)

df %>%
  mutate(product = checksum * multiplier) %>%
  mutate(cum_product = as.character(cumsum(product))) %>% #View()
  pull(product) %>%
  sum() %>% as.character()