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Markus Brueckner 2024-12-22 17:32:20 +01:00
parent ba21e5fdb0
commit b83e13d0bb
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# This file is automatically @generated by Cargo.
# It is not intended for manual editing.
version = 3
[[package]]
name = "day22"
version = "0.1.0"

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[package]
name = "day22"
version = "0.1.0"
edition = "2021"
[dependencies]

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# Solution Day 22
One of the few later ones I actually did on the day. The pseudo-random number generator is easy enough to
implement. If you read correctly, that is… I read "round to the nearest integer" first and was slightly off
with my numbers, until I saw that little "down" in there, which makes the whole thing _much_ easier. You don't
actually need to round, you can just do integer division, which will cut off the fractional part, leaving you
with the already rounded-down number.
## Task 1
After implementing the pseudo-random generator, it's easy enough to run it 2000x for each start number and
sum up the resulting numbers. Nothing special to see here.
## Task 2
This one was more complex. My initial naïve approach was to calculate all 4-digit sub-sequences, search for them
in all sequences and sum up the assiciated price. While this would probably yield the result _at some point_, the
complexity is _O(n² * m²)_ (with _n_ being the number of starting numbers and _m_ being the sequence length for each
starting number, assuming I got my maths right). Let's just say: not fun, definitely too slow.
My less naïve approach involves pre-calculating the first price of each sub-sequence for each starting number and
then afterwards going through them, summing them up grouped by sub-sequence and finding the maximum number of those
sums. This involves the heavy use of `HashMap`s (to keep track of the found sub-sequences and their associated number),
but brings complexity down to _ O(n * m)_ (for all three steps, actually. Pre-calculating the sequences and prices is _O(n * m)_,
calculating the sums and then finding the maximum is as well). This is then actually fast enough to finish before I
get bored.

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#![feature(map_try_insert)]
use std::collections::{HashMap, VecDeque};
fn mix_and_prune(intermediate: i64, number: i64) -> i64 {
(intermediate ^ number) % 16777216
}
fn next_secret_number(number: i64) -> i64 {
let mut result = mix_and_prune(number * 64, number);
result = mix_and_prune(result / 32, result);
result = mix_and_prune(result * 2048, result);
result
}
fn nth_secret_number(start: i64, n: u32) -> i64 {
let mut result = start;
for _ in 0..n {
result = next_secret_number(result);
}
result
}
fn task1() {
let numbers = include_str!("../input.txt")
.lines()
.map(|line| line.parse::<i64>().unwrap());
let sum: i64 = numbers.map(|number| nth_secret_number(number, 2000)).sum();
println!("Task 1: sum {sum}");
}
fn calculate_sequence(number: i64) -> HashMap<Vec<i64>, i64> {
let mut current_number = number;
let mut result = HashMap::new();
let mut current_pattern = VecDeque::new();
for _ in 0..2000 {
let next_number = next_secret_number(current_number);
let next_last_digit = next_number % 10;
let current_last_digit = current_number % 10;
current_pattern.push_back(next_last_digit - current_last_digit);
if current_pattern.len() == 4 {
// we're only ever interested in the first occurence of a pattern in the sequence, because that's what counts
let _ = result.try_insert(
Vec::from_iter(current_pattern.iter().cloned()),
next_last_digit,
);
current_pattern.pop_front(); // throw away the first digit. The pattern is a sliding window over the sequence
}
current_number = next_number;
}
result
}
fn task2() {
let numbers = include_str!("../input.txt")
.lines()
.map(|line| line.parse::<i64>().unwrap());
let sequences: Vec<_> = numbers.map(calculate_sequence).collect();
let mut banana_counters = HashMap::new();
for sequence in sequences.iter() {
for (pattern, price) in sequence.iter() {
banana_counters.insert(
pattern,
banana_counters.get(pattern).unwrap_or(&0_i64) + price,
);
}
}
let sum = banana_counters.values().max();
println!("Task 2: sum: {sum:?}");
}
fn main() {
task1();
task2();
}