Day 6

Part 1

library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0      ✔ purrr   0.3.5 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.4.1 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

x <- read_lines("2022-12-6_assets/input.txt")

input <- tibble(signal = str_split(x, pattern = "")[[1]])

input_lagged <- 
  input |>
  mutate(lag1 = lag(signal, 1),
         lag2 = lag(signal, 2),
         lag3 = lag(signal, 3),
         n = 1:n())

input_lagged |>
  drop_na() |>
  mutate(sequence = str_c(signal, lag1, lag2, lag3),
         len_unique_sequence = map(sequence, ~.x |> 
                                     str_split("") |>
                                     simplify() |>
                                     unique() |>
                                     length()) |> simplify()) |> 
  filter(len_unique_sequence == 4) |>
  slice(1) |>
  pull(n)

[1] 1300

Part 2

I’ve seen the folly of my ways.

chunkup <- function(chunk_size, x){
  start_indices = seq(1,length(x)-chunk_size+1)
  end_indicies = seq(chunk_size, length(x))
  pad <- rep(NA, chunk_size - 1)
  out <- map2(start_indices, end_indicies, ~x[..1:..2])
  out <- c(pad, out)
  return(out)
}

Replicating part 1 just to check

input |>
  mutate(
    id = 1:n(),
    sequences = chunkup(4, signal),
    seq_unique_len = map(
      sequences, ~.x |> 
        unique() |>  
        length()
    ) |> 
      simplify()
  ) |>
  filter(seq_unique_len == 4)

# A tibble: 1,903 × 4
   signal    id sequences seq_unique_len
   <chr>  <int> <list>             <int>
 1 w       1300 <chr [4]>              4
 2 g       1301 <chr [4]>              4
 3 v       1302 <chr [4]>              4
 4 z       1303 <chr [4]>              4
 5 t       1304 <chr [4]>              4
 6 w       1305 <chr [4]>              4
 7 p       1309 <chr [4]>              4
 8 z       1310 <chr [4]>              4
 9 h       1311 <chr [4]>              4
10 p       1316 <chr [4]>              4
# … with 1,893 more rows

Looks good!

input |>
  mutate(
    id = 1:n(),
    sequences = chunkup(14, signal),
    seq_unique_len = map(
      sequences, ~.x |> 
        unique() |>  
        length()
    ) |> 
      simplify()
  ) |>
  filter(seq_unique_len == 14) |>
  slice(1) |>
  pull(id)

[1] 3986

Just for Fun

library(ggdark)
library(khroma)
library(showtext)

Loading required package: sysfonts

Loading required package: showtextdb

library(scales)

Attaching package: 'scales'

The following object is masked from 'package:purrr':

    discard

The following object is masked from 'package:readr':

    col_factor

library(emojifont)

font_add_google(name = "Mountains of Christmas", family = "christmas")
font_add(family = "Noto Emoji", regular = file.path(font_paths()[2], "NotoEmoji-VariableFont_wght.ttf"))
showtext_auto()

theme_set(dark_theme_gray() + 
            theme(title = element_text(family = "christmas", size = 20)))

Inverted geom defaults of fill and color/colour.
To change them back, use invert_geom_defaults().

input |>
  mutate(
    id = 1:n(),
    sequences = chunkup(14, signal),
    seq_unique_len = map(
      sequences, ~.x |> 
        unique() |>  
        length()
    ) |> 
      simplify()
  ) |>
  slice(14:n()) |>
  ggplot(aes(id, seq_unique_len))+
    geom_point(position = position_jitter(width = 0, height = 0.1))

Figure 1: the unique length of 14 character long strings

sequence_checker <- function(seq_len, df){
  df |>
    mutate(
      id = 1:n(),
      sequences = chunkup(seq_len, signal),
      !!quo_name(seq_len) := map(
        sequences, ~.x |> 
          unique() |>  
          length()
      ) |> 
        simplify()
    ) |>
    slice(seq_len:n()) |>
    select(id, !!quo_name(seq_len)) -> out
  return(out)
}

map(4:26, ~sequence_checker(.x, input)) |>
  reduce(left_join) |>
  pivot_longer(-1, names_to = "seq_len", values_to = "unique_len") |>
  drop_na() |>
  mutate(prop_unique = unique_len/as.numeric(seq_len)) -> unique_df

unique_df |>
  mutate(seq_len = as.numeric(seq_len)) |>
  filter(seq_len == unique_len) |>
  group_by(seq_len) |>
  slice(1) |>
  ggplot(aes(seq_len, id))+
    geom_text(label = emoji("snowflake"), 
              size = 12, 
              family = "Noto Emoji")+
    labs(x = "sequence length",
         y = "position of first unique sequence")

Figure 2: Location of first sequence n long

Looks like no sequence longer than 14 has a unique run of letters!

unique_df |>
  ggplot(aes(id, prop_unique))+
  stat_smooth(aes(group = seq_len, color = as.numeric(seq_len)))+
  scale_color_bam(name = "sequence\nlength", midpoint = median(4:26))+
  scale_x_continuous(labels = label_comma())+
  ylim(0,1)

Figure 3: Number of unique characters divided by sequence length