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#![deny( missing_docs, // missing_doc_code_examples, missing_debug_implementations, missing_copy_implementations, trivial_casts, trivial_numeric_casts, unsafe_code, unstable_features, unused_import_braces, unused_qualifications )] #![allow(clippy::upper_case_acronyms)] //! A crate to quickly approximate Paths on a Grid. //! //! # Use Case //! //! Finding Paths on a Grid is an expensive Operation. Consider the following Setup: //! //! ![The Setup](https://github.com/mich101mich/hierarchical_pathfinding/blob/master/img/problem.png?raw=true) //! //! In order to calculate a Path from Start to End using regular A*, it is necessary to check a //! lot of Tiles: //! //! ![A*](https://github.com/mich101mich/hierarchical_pathfinding/blob/master/img/a_star.png?raw=true) //! //! (This is simply a small example, longer Paths require a quadratic increase in Tile checks, //! and unreachable Goals require the check of _**every single**_ Tile) //! //! The Solution that Hierarchical Pathfinding provides is to divide the Grid into Chunks and //! cache the Paths between Chunk entrances as a Graph of Nodes: //! //! ![The Graph](https://github.com/mich101mich/hierarchical_pathfinding/blob/master/img/hpa.png?raw=true) //! //! This allows Paths to be generated by connecting the Start and End to the Nodes within the //! Chunk and using the Graph for the rest: //! //! ![The Solution](https://github.com/mich101mich/hierarchical_pathfinding/blob/master/img/hpa_solution.png?raw=true) //! //! Since the Graph is not an exact representation of the Grid, **the resulting Paths will //! be slightly worse than the actual best Path** (unless [`config.perfect_paths`](PathCacheConfig::perfect_paths) //! is set to `true`). This is usually not a problem, since the purpose of Hierarchical Pathfinding //! is to quickly find the next direction to go in or a Heuristic for the Cost and existence //! of a Path. //! //! The only time where the actual best Path would noticeably differ is in the case of short Paths. //! That is why this crate calls the regular A* search after HPA* confirmed the length and //! existence. (This behavior can be turned of using the Config). //! //! This crate provides an implementation of a Hierarchical Pathfinding Algorithm for any generic Grid. //! Paths can be searched using either A* for a Path to a single Tile, or Dijkstra for searching //! multiple Targets. It handles solid walls in the Grid and actually finding a Path to a wall. //! //! # Examples //! ##### Creating the Cache //! First is the Grid itself. **How it is stored doesn't matter**, but lookup has to be fast. //! //! For this example, we shall use a 2D-Array: //! ```ignore //! // 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()); //! //! let cost_map = [ //! 1, // empty //! 10, // swamp //! -1, // wall = solid //! ]; //! ``` //! Now for creating the [`PathCache`]: //! ``` //! # 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()); //! # let cost_map = [ //! # 1, // empty //! # 10, // swamp //! # -1, // wall. Negative number == solid //! # ]; //! use hierarchical_pathfinding::prelude::*; //! //! let mut pathfinding = PathCache::new( //! (width, height), // the size of the Grid //! |(x, y)| cost_map[grid[y][x]], // get the cost for walking over a Tile //! ManhattanNeighborhood::new(width, height), // the Neighborhood //! PathCacheConfig { chunk_size: 3, ..Default::default() }, // config //! ); //! ``` //! The [`PathCache`] never takes the actual Grid, to allow for any storage format to be used //! (`Array`, `Vec`, `HashMap`, `kd-tree`, ...). Instead, it takes a callback function that //! indicates, how "expensive" walking across a Tile is (negative numbers for solid obstacles). //! //! Unfortunately, it is necessary to provide this function to every method of PathCache, since //! storing it would make the Grid immutable. See also [Updating the PathCache](#updating-the-pathcache). //! //! [Currying](https://en.wikipedia.org/wiki/Currying) can be used to reduce duplication: //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # // 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]; // now const for ownership reasons //! //! // only borrows the Grid when called //! fn cost_fn(grid: &Grid) -> impl '_ + FnMut((usize, usize)) -> isize { //! move |(x, y)| COST_MAP[grid[y][x]] //! } //! //! let mut pathfinding = PathCache::new( //! (width, height), // the size of the Grid //! //! // simply call the creator function to take a reference of the Grid //! cost_fn(&grid), //! // ... //! # ManhattanNeighborhood::new(width, height), // the Neighborhood //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, // config //! # ); //! ``` //! //! ##### Pathfinding //! Finding the Path to a single Goal: //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][grid[y][x]] //! # } //! # let mut pathfinding = PathCache::new( //! # (width, height), //! # cost_fn(&grid), //! # ManhattanNeighborhood::new(width, height), //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, //! # ); //! # //! 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); //! ``` //! For more information, see [`find_path`](PathCache::find_path). //! //! Finding multiple Goals: //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][grid[y][x]] //! # } //! # let mut pathfinding = PathCache::new( //! # (width, height), //! # cost_fn(&grid), //! # ManhattanNeighborhood::new(width, height), //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, //! # ); //! # //! 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])); //! ``` //! For more information, see [`find_paths`](PathCache::find_paths). //! //! ##### Using a Path //! - Path exists: `path.is_some()` | `paths.contains_key()` //! - Useful as a Heuristic for other Algorithms //! - **100% correct** (`true` if and only if path can be found) //! - Total Cost of the Path: [`path.cost()`](internals::AbstractPath::cost) //! - Correct for this Path, may be slightly larger than for optimal Path //! - The cost is simply returned; `cost()` does no calculations //! - Total Length of the Path: [`path.length()`](internals::AbstractPath::length) //! - Correct for this Path, may be slightly longer than the optimal Path //! - The length is simply returned; `length()` does no calculations //! - Next Position: [`path.next()`](internals::AbstractPath::next) | [`path.safe_next(cost_fn)`](internals::AbstractPath::safe_next) //! - [`safe_next`](internals::AbstractPath::safe_next) is needed if [`config.cache_paths`](crate::PathCacheConfig::cache_paths) is set to `false` //! - can be called several times to iterate Path //! - path implements `Iterator<Item = (usize, usize)>` //! - Entire Path: `path.collect::<Vec<_>>()` | [`path.resolve(cost_fn)`](internals::AbstractPath::resolve) //! - [`resolve`](internals::AbstractPath::resolve) is needed if [`config.cache_paths`](crate::PathCacheConfig::cache_paths) is set to `false` //! - Returns a `Vec<(usize, usize)>` //! //! Note that [`resolve`](internals::AbstractPath::resolve) calculates any missing segments (if [`config.cache_paths`](crate::PathCacheConfig::cache_paths) ` == false`) //! and allocates a [`Vec`](std::vec::Vec) with the resulting Points. Not recommended if only the //! beginning of the Path is needed. //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][grid[y][x]] //! # } //! # let mut pathfinding = PathCache::new( //! # (width, height), //! # cost_fn(&grid), //! # ManhattanNeighborhood::new(width, height), //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, //! # ); //! # struct Player{ pos: (usize, usize) } //! # impl Player { //! # pub fn move_to(&mut self, pos: (usize, usize)) { //! # self.pos = pos; //! # } //! # } //! # //! 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)); //! //! // iterating is possible //! for new_pos in path { //! player.move_to(new_pos); //! } //! assert_eq!(player.pos, goal); //! ``` //! //! ##### Updating the PathCache //! The PathCache does not contain a copy or reference of the Grid for mutability and Ownership reasons. //! This means however, that the user is responsible for storing and maintaining both the Grid and the PathCache. //! It is also necessary to update the PathCache when the Grid has changed to keep it consistent: //! ```should_panic //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][grid[y][x]] //! # } //! # let mut pathfinding = PathCache::new( //! # (width, height), //! # cost_fn(&grid), //! # ManhattanNeighborhood::new(width, height), //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, //! # ); //! # //! let (start, goal) = ((0, 0), (2, 0)); //! //! let path = pathfinding.find_path(start, goal, cost_fn(&grid)); //! assert!(path.is_none()); // from previous example //! //! // Clear a way to the goal //! grid[1][2] = 0; // at (2, 1): the wall below the goal //! //! let path = pathfinding.find_path(start, goal, cost_fn(&grid)); //! assert!(path.is_some()); // there should be a Path now! //! ``` //! [`tiles_changed`](PathCache::tiles_changed) must be called with all changed Tiles: //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][grid[y][x]] //! # } //! # let mut pathfinding = PathCache::new( //! # (width, height), //! # cost_fn(&grid), //! # ManhattanNeighborhood::new(width, height), //! # PathCacheConfig { chunk_size: 3, ..Default::default() }, //! # ); //! # //! let (start, goal) = ((0, 0), (2, 0)); //! //! let path = pathfinding.find_path(start, goal, cost_fn(&grid)); //! assert!(path.is_none()); //! //! // Clear a way to the goal //! grid[1][2] = 0; // at (2, 1): the wall below the goal //! //! pathfinding.tiles_changed( //! &[(2, 1)], //! cost_fn(&grid), //! ); //! //! let path = pathfinding.find_path(start, goal, cost_fn(&grid)); //! assert!(path.is_some()); //! ``` //! `tiles_changed` takes a slice of Points, and it is recommended to bundle changes together for //! performance reasons. //! //! ##### Configuration //! The last parameter for PathCache::new is a [`PathCacheConfig`] object with different options to have more control over the generated PathCache. //! These options are mostly used to adjust the balance between Performance and Memory Usage, with the default values aiming more at Performance. //! The PathCacheConfig struct also provides defaults for low Memory Usage [`PathCacheConfig::LOW_MEM`] //! or best Performance [`PathCacheConfig::HIGH_PERFORMANCE`] //! ``` //! # use hierarchical_pathfinding::prelude::*; //! # let mut grid = [ //! # [0, 2, 0, 0, 0], //! # [0, 2, 2, 2, 2], //! # [0, 1, 0, 0, 0], //! # [0, 1, 0, 2, 0], //! # [0, 0, 0, 2, 0], //! # ]; //! # let (width, height) = (grid.len(), grid[0].len()); //! # fn cost_fn(grid: &[[usize; 5]; 5]) -> impl '_ + FnMut((usize, usize)) -> isize { //! # move |(x, y)| [1, 10, -1][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 { //! chunk_size: 3, //! ..PathCacheConfig::LOW_MEM //! } //! ); //! //! assert_eq!(pathfinding.config().chunk_size, 3); //! ``` type Point = (usize, usize); type PointMap<V> = std::collections::HashMap<Point, V, fnv::FnvBuildHasher>; type PointSet = std::collections::HashSet<Point, fnv::FnvBuildHasher>; mod path_cache; pub use self::path_cache::{PathCache, PathCacheConfig}; mod path; mod utils; pub(crate) use utils::*; pub mod neighbors; mod graph; mod grid; /// Internal stuff that is returned by other function pub mod internals { pub use crate::path::AbstractPath; pub use crate::path_cache::{CacheInspector, NodeInspector}; } /// The prelude for this crate. pub mod prelude { pub use crate::{ neighbors::{ManhattanNeighborhood, MooreNeighborhood, Neighborhood}, PathCache, PathCacheConfig, }; }