Day 25: Snowverload
Megathread guidelines
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FAQ
- What is this?: Here is a post with a large amount of details: https://programming.dev/post/6637268
- Where do I participate?: https://adventofcode.com/
- Is there a leaderboard for the community?: We have a programming.dev leaderboard with the info on how to join in this post: https://programming.dev/post/6631465
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Scala3
all done!
def parseLine(a: String): List[UnDiEdge[String]] = a match case s"$n: $r" => r.split(" ").map(_ ~ n).toList case _ => List() def removeShortestPath(g: Graph[String, UnDiEdge[String]], ns: List[String]) = g.removedAll(g.get(ns(0)).shortestPathTo(g.get(ns(1))).map(_.edges.map(_.outer)).getOrElse(List())) def removeTriple(g: Graph[String, UnDiEdge[String]], ns: List[String]) = List.fill(3)(ns).foldLeft(g)(removeShortestPath) def division(g: Graph[String, UnDiEdge[String]]): Option[Long] = val t = g.componentTraverser() Option.when(t.size == 2)(t.map(_.nodes.size).product) def task1(a: List[String]): Long = val g = Graph() ++ a.flatMap(parseLine) g.nodes.toList.combinations(2).map(a => removeTriple(g, a.map(_.outer))).flatMap(division).take(1).toList.head
Impressive!
Rust
First tried a really slow brute force, but after waiting many minutes heard others talk of Karger’s Algorithm, so I implemented that.
use rand::prelude::*; use std::collections::HashSet; type Graph = (V, E); type V = HashSet; type E = Vec<(String, String)>; fn parse_input(input: &str) -> Graph { let mut vertices = HashSet::new(); let mut edges = Vec::new(); for line in input.trim().lines() { let mut it = line.split(':'); let left = it.next().unwrap(); vertices.insert(left.to_owned()); for right in it.next().unwrap().trim().split_whitespace() { vertices.insert(right.to_owned()); edges.push((left.to_owned(), right.to_owned())); } } (vertices, edges) } fn part1(input: &str) -> usize { let (vertices, edges) = parse_input(input); let mut rng = rand::thread_rng(); // Karger's Algorithm loop { let mut vertices = vertices.clone(); let mut edges = edges.clone(); while vertices.len() > 2 { let i = rng.gen_range(0..edges.len()); let (v1, v2) = edges[i].clone(); // contract the edge edges.swap_remove(i); vertices.remove(&v1); vertices.remove(&v2); let new_v = format!("{}:{}", v1, v2); vertices.insert(new_v.clone()); for (e1, e2) in edges.iter_mut() { if *e1 == v1 || *e1 == v2 { *e1 = new_v.clone() } if *e2 == v1 || *e2 == v2 { *e2 = new_v.clone() } } // remove loops let mut j = 0; while j < edges.len() { let (e1, e2) = &edges[j]; if e1 == e2 { edges.swap_remove(j); } else { j += 1; } } } if edges.len() == 3 { break vertices .iter() .map(|s| s.split(':').count()) .product::(); } } }
Same. I am happy that it was a straightforward algorithm.
Python
import networkx as nx from .solver import Solver class Day25(Solver): def __init__(self): super().__init__(25) def presolve(self, input: str): self.graph = nx.Graph() for line in input.splitlines(): from_, to_line = line.split(': ') for to in to_line.split(' '): self.graph.add_edge(from_, to) def solve_first_star(self) -> int | str: cut_value, partition = nx.algorithms.stoer_wagner(self.graph) return len(partition[0]) * len(partition[1])