mirror of
https://gitlab.com/veloren/veloren.git
synced 2024-08-30 18:12:32 +00:00
279 lines
9.5 KiB
Rust
279 lines
9.5 KiB
Rust
use crate::path::Path;
|
|
use core::{
|
|
cmp::Ordering::{self, Equal},
|
|
fmt,
|
|
hash::{BuildHasher, Hash},
|
|
};
|
|
use hashbrown::HashMap;
|
|
use std::collections::BinaryHeap;
|
|
|
|
#[derive(Copy, Clone, Debug)]
|
|
pub struct PathEntry<S> {
|
|
// cost so far + heursitic
|
|
cost_estimate: f32,
|
|
node: S,
|
|
}
|
|
|
|
impl<S: Eq> PartialEq for PathEntry<S> {
|
|
#[allow(clippy::unconditional_recursion)] // false positive as we use .node
|
|
fn eq(&self, other: &PathEntry<S>) -> bool { self.node.eq(&other.node) }
|
|
}
|
|
|
|
impl<S: Eq> Eq for PathEntry<S> {}
|
|
|
|
impl<S: Eq> Ord for PathEntry<S> {
|
|
// This method implements reverse ordering, so that the lowest cost
|
|
// will be ordered first
|
|
fn cmp(&self, other: &PathEntry<S>) -> Ordering {
|
|
other
|
|
.cost_estimate
|
|
.partial_cmp(&self.cost_estimate)
|
|
.unwrap_or(Equal)
|
|
}
|
|
}
|
|
|
|
impl<S: Eq> PartialOrd for PathEntry<S> {
|
|
fn partial_cmp(&self, other: &PathEntry<S>) -> Option<Ordering> { Some(self.cmp(other)) }
|
|
|
|
// This is particularily hot in `BinaryHeap::pop`, so we provide this
|
|
// implementation.
|
|
//
|
|
// NOTE: This probably doesn't handle edge cases like `NaNs` in a consistent
|
|
// manner with `Ord`, but I don't think we need to care about that here(?)
|
|
//
|
|
// See note about reverse ordering above.
|
|
fn le(&self, other: &PathEntry<S>) -> bool { other.cost_estimate <= self.cost_estimate }
|
|
}
|
|
|
|
pub enum PathResult<T> {
|
|
/// No reachable nodes were satisfactory.
|
|
///
|
|
/// Contains path to node with the lowest heuristic value (out of the
|
|
/// explored nodes).
|
|
None(Path<T>),
|
|
/// Either max_iters or max_cost was reached.
|
|
///
|
|
/// Contains path to node with the lowest heuristic value (out of the
|
|
/// explored nodes).
|
|
Exhausted(Path<T>),
|
|
/// Path succefully found.
|
|
///
|
|
/// Second field is cost.
|
|
Path(Path<T>, f32),
|
|
Pending,
|
|
}
|
|
|
|
impl<T> PathResult<T> {
|
|
/// Returns `Some((path, cost))` if a path reaching the target was
|
|
/// successfully found.
|
|
pub fn into_path(self) -> Option<(Path<T>, f32)> {
|
|
match self {
|
|
PathResult::Path(path, cost) => Some((path, cost)),
|
|
_ => None,
|
|
}
|
|
}
|
|
|
|
pub fn map<U>(self, f: impl FnOnce(Path<T>) -> Path<U>) -> PathResult<U> {
|
|
match self {
|
|
PathResult::None(p) => PathResult::None(f(p)),
|
|
PathResult::Exhausted(p) => PathResult::Exhausted(f(p)),
|
|
PathResult::Path(p, cost) => PathResult::Path(f(p), cost),
|
|
PathResult::Pending => PathResult::Pending,
|
|
}
|
|
}
|
|
}
|
|
|
|
// If node entry exists, this was visited!
|
|
#[derive(Clone, Debug)]
|
|
struct NodeEntry<S> {
|
|
/// Previous node in the cheapest path (known so far) that goes from the
|
|
/// start to this node.
|
|
///
|
|
/// If `came_from == self` this is the start node! (to avoid inflating the
|
|
/// size with `Option`)
|
|
came_from: S,
|
|
/// Cost to reach this node from the start by following the cheapest path
|
|
/// known so far. This is the sum of the transition costs between all the
|
|
/// nodes on this path.
|
|
cost: f32,
|
|
}
|
|
|
|
#[derive(Clone)]
|
|
pub struct Astar<S, Hasher> {
|
|
iter: usize,
|
|
max_iters: usize,
|
|
max_cost: f32,
|
|
potential_nodes: BinaryHeap<PathEntry<S>>, // cost, node pairs
|
|
visited_nodes: HashMap<S, NodeEntry<S>, Hasher>,
|
|
/// Node with the lowest heuristic value so far.
|
|
///
|
|
/// (node, heuristic value)
|
|
closest_node: Option<(S, f32)>,
|
|
}
|
|
|
|
/// NOTE: Must manually derive since Hasher doesn't implement it.
|
|
impl<S: Clone + Eq + Hash + fmt::Debug, H: BuildHasher> fmt::Debug for Astar<S, H> {
|
|
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
|
f.debug_struct("Astar")
|
|
.field("iter", &self.iter)
|
|
.field("max_iters", &self.max_iters)
|
|
.field("potential_nodes", &self.potential_nodes)
|
|
.field("visited_nodes", &self.visited_nodes)
|
|
.field("closest_node", &self.closest_node)
|
|
.finish()
|
|
}
|
|
}
|
|
|
|
impl<S: Clone + Eq + Hash, H: BuildHasher + Clone> Astar<S, H> {
|
|
pub fn new(max_iters: usize, start: S, hasher: H) -> Self {
|
|
Self {
|
|
max_iters,
|
|
max_cost: f32::MAX,
|
|
iter: 0,
|
|
potential_nodes: core::iter::once(PathEntry {
|
|
cost_estimate: 0.0,
|
|
node: start.clone(),
|
|
})
|
|
.collect(),
|
|
visited_nodes: {
|
|
let mut s = HashMap::with_capacity_and_hasher(1, hasher);
|
|
s.extend(core::iter::once((start.clone(), NodeEntry {
|
|
came_from: start,
|
|
cost: 0.0,
|
|
})));
|
|
s
|
|
},
|
|
closest_node: None,
|
|
}
|
|
}
|
|
|
|
pub fn with_max_cost(mut self, max_cost: f32) -> Self {
|
|
self.max_cost = max_cost;
|
|
self
|
|
}
|
|
|
|
pub fn poll<I>(
|
|
&mut self,
|
|
iters: usize,
|
|
// Estimate how far we are from the target? but we are given two nodes...
|
|
// (current, previous)
|
|
mut heuristic: impl FnMut(&S, &S) -> f32,
|
|
// get neighboring nodes
|
|
mut neighbors: impl FnMut(&S) -> I,
|
|
// have we reached target?
|
|
mut satisfied: impl FnMut(&S) -> bool,
|
|
) -> PathResult<S>
|
|
where
|
|
I: Iterator<Item = (S, f32)>, // (node, transition cost)
|
|
{
|
|
let iter_limit = self.max_iters.min(self.iter + iters);
|
|
while self.iter < iter_limit {
|
|
if let Some(PathEntry {
|
|
node,
|
|
cost_estimate,
|
|
}) = self.potential_nodes.pop()
|
|
{
|
|
let (node_cost, came_from) = self
|
|
.visited_nodes
|
|
.get(&node)
|
|
.map(|n| (n.cost, n.came_from.clone()))
|
|
.expect("All nodes in the queue should be included in visisted_nodes");
|
|
|
|
if satisfied(&node) {
|
|
return PathResult::Path(self.reconstruct_path_to(node), node_cost);
|
|
// Note, we assume that cost_estimate isn't an overestimation
|
|
// (i.e. that `heuristic` doesn't overestimate).
|
|
} else if cost_estimate > self.max_cost {
|
|
return PathResult::Exhausted(
|
|
self.closest_node
|
|
.clone()
|
|
.map(|(lc, _)| self.reconstruct_path_to(lc))
|
|
.unwrap_or_default(),
|
|
);
|
|
} else {
|
|
for (neighbor, transition_cost) in neighbors(&node) {
|
|
if neighbor == came_from {
|
|
continue;
|
|
}
|
|
let neighbor_cost = self
|
|
.visited_nodes
|
|
.get(&neighbor)
|
|
.map_or(f32::MAX, |n| n.cost);
|
|
|
|
// compute cost to traverse to each neighbor
|
|
let cost = node_cost + transition_cost;
|
|
|
|
if cost < neighbor_cost {
|
|
let previously_visited = self
|
|
.visited_nodes
|
|
.insert(neighbor.clone(), NodeEntry {
|
|
came_from: node.clone(),
|
|
cost,
|
|
})
|
|
.is_some();
|
|
let h = heuristic(&neighbor, &node);
|
|
// note that `cost` field does not include the heuristic
|
|
// priority queue does include heuristic
|
|
let cost_estimate = cost + h;
|
|
|
|
if self
|
|
.closest_node
|
|
.as_ref()
|
|
.map(|&(_, ch)| h < ch)
|
|
.unwrap_or(true)
|
|
{
|
|
self.closest_node = Some((node.clone(), h));
|
|
};
|
|
|
|
// TODO: I think the if here should be removed
|
|
// if we hadn't already visited, add this to potential nodes, what about
|
|
// its neighbors, wouldn't they need to be revisted???
|
|
if !previously_visited {
|
|
self.potential_nodes.push(PathEntry {
|
|
cost_estimate,
|
|
node: neighbor,
|
|
});
|
|
}
|
|
}
|
|
}
|
|
}
|
|
} else {
|
|
return PathResult::None(
|
|
self.closest_node
|
|
.clone()
|
|
.map(|(lc, _)| self.reconstruct_path_to(lc))
|
|
.unwrap_or_default(),
|
|
);
|
|
}
|
|
|
|
self.iter += 1
|
|
}
|
|
|
|
if self.iter >= self.max_iters {
|
|
PathResult::Exhausted(
|
|
self.closest_node
|
|
.clone()
|
|
.map(|(lc, _)| self.reconstruct_path_to(lc))
|
|
.unwrap_or_default(),
|
|
)
|
|
} else {
|
|
PathResult::Pending
|
|
}
|
|
}
|
|
|
|
fn reconstruct_path_to(&mut self, end: S) -> Path<S> {
|
|
let mut path = vec![end.clone()];
|
|
let mut cnode = &end;
|
|
while let Some(node) = self
|
|
.visited_nodes
|
|
.get(cnode)
|
|
.map(|n| &n.came_from)
|
|
.filter(|n| *n != cnode)
|
|
{
|
|
path.push(node.clone());
|
|
cnode = node;
|
|
}
|
|
path.into_iter().rev().collect()
|
|
}
|
|
}
|