pub struct PathCache<N: Neighborhood> { /* private fields */ }
Expand description
A struct to store the Hierarchical Pathfinding information.
Implementations§
Source§impl<N: Neighborhood + Sync> PathCache<N>
impl<N: Neighborhood + Sync> PathCache<N>
Sourcepub fn new<F: Sync + Fn((usize, usize)) -> isize>(
(width, height): (usize, usize),
get_cost: F,
neighborhood: N,
config: PathCacheConfig,
) -> PathCache<N>
pub fn new<F: Sync + Fn((usize, usize)) -> isize>( (width, height): (usize, usize), get_cost: F, neighborhood: N, config: PathCacheConfig, ) -> PathCache<N>
Creates a new PathCache
§Arguments
(width, height)
- the size of the Gridget_cost
- get the cost for walking over a Tile. (Cost < 0 means solid Tile)neighborhood
- the Neighborhood to use. (SeeNeighborhood
)config
- optional config for creating the cache. (SeePathCacheConfig
)
get_cost((x, y))
should return the cost for walking over the Tile at (x, y).
Costs below 0 are solid Tiles.
§Examples
Basic usage:
use hierarchical_pathfinding::prelude::*;
// create and initialize Grid
// 0 = empty, 1 = swamp, 2 = wall
let mut grid = [
[0, 2, 0, 0, 0],
[0, 2, 2, 2, 0],
[0, 1, 0, 0, 0],
[0, 1, 0, 2, 0],
[0, 0, 0, 2, 0],
];
let (width, height) = (grid.len(), grid[0].len());
type Grid = [[usize; 5]; 5];
const COST_MAP: [isize; 3] = [1, 10, -1];
fn cost_fn(grid: &Grid) -> impl '_ + Sync + Fn((usize, usize)) -> isize {
move |(x, y)| COST_MAP[grid[y][x]]
}
let mut pathfinding = PathCache::new(
(width, height), // the size of the Grid
cost_fn(&grid), // get the cost for walking over a Tile
ManhattanNeighborhood::new(width, height), // the Neighborhood
PathCacheConfig::with_chunk_size(3), // config
);
Sourcepub fn new_with_fn_mut<F: FnMut((usize, usize)) -> isize>(
(width, height): (usize, usize),
get_cost: F,
neighborhood: N,
config: PathCacheConfig,
) -> PathCache<N>
pub fn new_with_fn_mut<F: FnMut((usize, usize)) -> isize>( (width, height): (usize, usize), get_cost: F, neighborhood: N, config: PathCacheConfig, ) -> PathCache<N>
Sourcepub fn new_parallel<F: Sync + Fn((usize, usize)) -> isize>(
(width, height): (usize, usize),
get_cost: F,
neighborhood: N,
config: PathCacheConfig,
) -> PathCache<N>
👎Deprecated since 0.5.0: new
is automatically parallel
pub fn new_parallel<F: Sync + Fn((usize, usize)) -> isize>( (width, height): (usize, usize), get_cost: F, neighborhood: N, config: PathCacheConfig, ) -> PathCache<N>
new
is automatically parallelSame as new
, but uses multiple threads.
Note that get_cost
has to be Fn
instead of FnMut
.
Sourcepub fn find_path(
&self,
start: (usize, usize),
goal: (usize, usize),
get_cost: impl FnMut((usize, usize)) -> isize,
) -> Option<AbstractPath<N>>
pub fn find_path( &self, start: (usize, usize), goal: (usize, usize), get_cost: impl FnMut((usize, usize)) -> isize, ) -> Option<AbstractPath<N>>
Calculates the Path from start
to goal
on the Grid.
If no Path could be found, None
is returned.
get_cost((x, y))
should return the cost for walking over the Tile at (x, y).
Costs below 0 are solid Tiles.
§Examples
Basic usage:
let pathfinding: PathCache<_> = // ...
let start = (0, 0);
let goal = (4, 4);
// find_path returns Some(Path) on success
let path = pathfinding.find_path(
start,
goal,
cost_fn(&grid),
);
assert!(path.is_some());
let path = path.unwrap();
assert_eq!(path.cost(), 12);
The return Value gives the total Cost of the Path using cost()
and allows to iterate over
the Points in the Path.
Note: Setting config.cache_paths
to false
means
that the Paths need to be recalculated as needed. This means that for any sections of the
Path that are not present, safe_next
needs to be called to supply the Cost function.
Calling next
in that scenario would lead to a Panic.
Using the Path:
let mut player = Player {
pos: (0, 0),
//...
};
let goal = (4, 4);
let mut path = pathfinding.find_path(
player.pos,
goal,
cost_fn(&grid),
).unwrap();
player.move_to(path.next().unwrap());
assert_eq!(player.pos, (0, 1));
// wait for next turn or whatever
player.move_to(path.next().unwrap());
assert_eq!(player.pos, (0, 2));
If the Grid changes, any Path objects still in use may become invalid. You can still use them if you are certain that nothing in relation to that Path changed, but it is discouraged and can lead to undefined behavior or panics.
Obtaining the entire Path:
// ...
let path = path.unwrap();
let points: Vec<(usize, usize)> = path.collect();
assert_eq!(
points,
vec![(0, 1), (0, 2), (0, 3), (0, 4), (1, 4), (2, 4),
(2, 3), (2, 2), (3, 2), (4, 2), (4, 3), (4, 4)],
);
Sourcepub fn find_paths(
&self,
start: (usize, usize),
goals: &[(usize, usize)],
get_cost: impl FnMut((usize, usize)) -> isize,
) -> HashMap<(usize, usize), AbstractPath<N>>
pub fn find_paths( &self, start: (usize, usize), goals: &[(usize, usize)], get_cost: impl FnMut((usize, usize)) -> isize, ) -> HashMap<(usize, usize), AbstractPath<N>>
Calculates the Paths from one start
to several goals
on the Grid.
This is equivalent to find_path
, except that it is optimized to handle multiple Goals
at once. However, it is slower for very few goals, since it does not use a heuristic like
find_path
does.
Instead of returning a single Option, it returns a Hashmap, where the position of the Goal is the key, and the Value is a Tuple of the Path and the Cost of that Path.
get_cost((x, y))
should return the cost for walking over the Tile at (x, y).
Costs below 0 are solid Tiles.
See find_path
for more details on how to use the returned Paths.
§Examples
Basic usage:
let pathfinding: PathCache<_> = // ...
let start = (0, 0);
let goals = [(4, 4), (2, 0)];
// find_paths returns a HashMap<goal, Path> for all successes
let paths = pathfinding.find_paths(
start,
&goals,
cost_fn(&grid),
);
// (4, 4) is reachable
assert!(paths.contains_key(&goals[0]));
// (2, 0) is not reachable
assert!(!paths.contains_key(&goals[1]));
The returned Path is always equivalent to the one returned by find_path
:
let start = (0, 0);
let goal = (4, 4);
let paths = pathfinding.find_paths(
start,
&[goal],
cost_fn(&grid),
);
let dijkstra_path: Vec<_> = paths[&goal].clone().collect();
let a_star_path: Vec<_> = pathfinding.find_path(
start,
goal,
cost_fn(&grid),
).unwrap().collect();
assert_eq!(dijkstra_path, a_star_path);
Sourcepub fn find_closest_goal(
&self,
start: (usize, usize),
goals: &[(usize, usize)],
get_cost: impl FnMut((usize, usize)) -> isize,
) -> Option<((usize, usize), AbstractPath<N>)>
pub fn find_closest_goal( &self, start: (usize, usize), goals: &[(usize, usize)], get_cost: impl FnMut((usize, usize)) -> isize, ) -> Option<((usize, usize), AbstractPath<N>)>
Finds the closest from a list of goals.
Returns a tuple of the goal and the Path to that goal, or None
if none of the goals are
reachable.
Similar to find_paths
in performance and search strategy, but
stops after the first goal is found.
§Examples
Basic usage:
let pathfinding: PathCache<_> = // ...
let start = (0, 0);
let goals = [(4, 4), (2, 0), (2, 2)];
// find_closest_goal returns Some((goal, Path)) on success
let (goal, path) = pathfinding.find_closest_goal(
start,
&goals,
cost_fn(&grid),
).unwrap();
assert_eq!(goal, goals[2]);
let naive_closest = pathfinding
.find_paths(start, &goals, cost_fn(&grid))
.into_iter()
.min_by_key(|(_, path)| path.cost())
.unwrap();
assert_eq!(goal, naive_closest.0);
let path: Vec<_> = path.collect();
let naive_path: Vec<_> = naive_closest.1.collect();
assert_eq!(path, naive_path);
Comparison with find_paths
:
let (goal, path) = pathfinding.find_closest_goal(
start,
&goals,
cost_fn(&grid),
).unwrap();
let naive_closest = pathfinding
.find_paths(start, &goals, cost_fn(&grid))
.into_iter()
.min_by_key(|(_, path)| path.cost())
.unwrap();
assert_eq!(goal, naive_closest.0);
let path: Vec<_> = path.collect();
let naive_path: Vec<_> = naive_closest.1.collect();
assert_eq!(path, naive_path);
Sourcepub fn tiles_changed<F: Sync + Fn((usize, usize)) -> isize>(
&mut self,
tiles: &[(usize, usize)],
get_cost: F,
)
pub fn tiles_changed<F: Sync + Fn((usize, usize)) -> isize>( &mut self, tiles: &[(usize, usize)], get_cost: F, )
Notifies the PathCache that the Grid changed.
This Method updates any internal Paths that might have changed when the Grid changed. This
is an expensive operation and should only be performed if the change affected the walking
cost of a tile and the PathCache is needed again. If possible, try to bundle as many
changes as possible into a single call to tiles_changed
to avoid unnecessary
recalculations.
Side note: if anybody has a way to improve this method, open a GitHub Issue / Pull Request.
§Examples
Basic usage:
let mut pathfinding: PathCache<_> = // ...
let (start, goal) = ((0, 0), (2, 0));
let path = pathfinding.find_path(start, goal, cost_fn(&grid));
assert!(path.is_none());
grid[1][2] = 0;
grid[3][2] = 2;
assert_eq!(grid, [
[0, 2, 0, 0, 0],
[0, 2, 0, 2, 2],
[0, 1, 0, 0, 0],
[0, 1, 2, 2, 0],
[0, 0, 0, 2, 0],
]);
pathfinding.tiles_changed(
&[(2, 1), (2, 3)],
cost_fn(&grid),
);
let path = pathfinding.find_path(start, goal, cost_fn(&grid));
assert!(path.is_some());
Sourcepub fn tiles_changed_with_fn_mut<F: FnMut((usize, usize)) -> isize>(
&mut self,
tiles: &[(usize, usize)],
get_cost: F,
)
pub fn tiles_changed_with_fn_mut<F: FnMut((usize, usize)) -> isize>( &mut self, tiles: &[(usize, usize)], get_cost: F, )
Same as tiles_changed
, but doesn’t use threads to allow FnMut
.
Equivalent to tiles_changed
if parallel
feature is disabled.
Note that this is way slower than tiles_changed
with parallel
.
Sourcepub fn inspect_nodes(&self) -> CacheInspector<'_, N> ⓘ
pub fn inspect_nodes(&self) -> CacheInspector<'_, N> ⓘ
Allows for debugging and visualizing the PathCache
The returned object gives read-only access to the current state of the PathCache, mainly the Nodes and how they are connected to each other
§Examples
Basic usage:
let pathfinding: PathCache<_> = // ...
// only draw the connections between Nodes once
let mut visited = HashSet::new();
for node in pathfinding.inspect_nodes() {
let pos = node.pos();
// draw Node at x: pos.0, y: pos.1
visited.insert(node.id());
for (neighbor, cost) in node.connected().filter(|(n, _)| !visited.contains(&n.id())) {
let other_pos = neighbor.pos();
// draw Line from pos to other_pos, colored by cost
}
}
Sourcepub fn config(&self) -> &PathCacheConfig
pub fn config(&self) -> &PathCacheConfig
Returns the config used to create this PathCache
Trait Implementations§
Auto Trait Implementations§
impl<N> Freeze for PathCache<N>where
N: Freeze,
impl<N> RefUnwindSafe for PathCache<N>where
N: RefUnwindSafe,
impl<N> Send for PathCache<N>where
N: Send,
impl<N> Sync for PathCache<N>where
N: Sync,
impl<N> Unpin for PathCache<N>where
N: Unpin,
impl<N> UnwindSafe for PathCache<N>where
N: UnwindSafe,
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
self
into a Left
variant of Either<Self, Self>
if into_left
is true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
self
into a Left
variant of Either<Self, Self>
if into_left(&self)
returns true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read more