use crate::path::Path; use core::cmp::Ordering::Equal; use hashbrown::{HashMap, HashSet}; use std::cmp::Ordering; use std::collections::BinaryHeap; use std::f32; use std::hash::Hash; #[derive(Copy, Clone, Debug)] pub struct PathEntry { cost: f32, node: S, } impl PartialEq for PathEntry { fn eq(&self, other: &PathEntry) -> bool { self.node.eq(&other.node) } } impl Eq for PathEntry {} impl Ord for PathEntry { // This method implements reverse ordering, so that the lowest cost // will be ordered first fn cmp(&self, other: &PathEntry) -> Ordering { other.cost.partial_cmp(&self.cost).unwrap_or(Equal) } } impl PartialOrd for PathEntry { fn partial_cmp(&self, other: &PathEntry) -> Option { Some(self.cmp(other)) } } pub enum PathResult { None(Path), Exhausted(Path), Path(Path), Pending, } #[derive(Clone, Debug)] pub struct Astar { iter: usize, max_iters: usize, potential_nodes: BinaryHeap>, came_from: HashMap, cheapest_scores: HashMap, final_scores: HashMap, visited: HashSet, lowest_cost: Option, } impl Astar { pub fn new(max_iters: usize, start: S, heuristic: impl FnOnce(&S) -> f32) -> Self { Self { max_iters, iter: 0, potential_nodes: std::iter::once(PathEntry { cost: 0.0, node: start.clone(), }) .collect(), came_from: HashMap::default(), cheapest_scores: std::iter::once((start.clone(), 0.0)).collect(), final_scores: std::iter::once((start.clone(), heuristic(&start))).collect(), visited: std::iter::once(start).collect(), lowest_cost: None, } } pub fn poll( &mut self, iters: usize, mut heuristic: impl FnMut(&S) -> f32, mut neighbors: impl FnMut(&S) -> I, mut transition: impl FnMut(&S, &S) -> f32, mut satisfied: impl FnMut(&S) -> bool, ) -> PathResult where I: Iterator, { while self.iter < self.max_iters.min(self.iter + iters) { if let Some(PathEntry { node, .. }) = self.potential_nodes.pop() { if satisfied(&node) { return PathResult::Path(self.reconstruct_path_to(node)); } else { self.lowest_cost = Some(node.clone()); for neighbor in neighbors(&node) { let node_cheapest = self.cheapest_scores.get(&node).unwrap_or(&f32::MAX); let neighbor_cheapest = self.cheapest_scores.get(&neighbor).unwrap_or(&f32::MAX); let cost = node_cheapest + transition(&node, &neighbor); if cost < *neighbor_cheapest { self.came_from.insert(neighbor.clone(), node.clone()); self.cheapest_scores.insert(neighbor.clone(), cost); let neighbor_cost = cost + heuristic(&neighbor); self.final_scores.insert(neighbor.clone(), neighbor_cost); if self.visited.insert(neighbor.clone()) { self.potential_nodes.push(PathEntry { node: neighbor.clone(), cost: neighbor_cost, }); } } } } } else { return PathResult::None( self.lowest_cost .clone() .map(|lc| self.reconstruct_path_to(lc)) .unwrap_or_default(), ); } self.iter += 1 } if self.iter >= self.max_iters { PathResult::Exhausted( self.lowest_cost .clone() .map(|lc| self.reconstruct_path_to(lc)) .unwrap_or_default(), ) } else { PathResult::Pending } } fn reconstruct_path_to(&mut self, end: S) -> Path { let mut path = vec![end.clone()]; let mut cnode = &end; while let Some(node) = self.came_from.get(cnode) { path.push(node.clone()); cnode = node; } path.into_iter().rev().collect() } }