|  | use std::collections::hash_map::Entry::{Occupied, Vacant}; | 
|  | use std::collections::{BinaryHeap, HashMap}; | 
|  |  | 
|  | use std::hash::Hash; | 
|  |  | 
|  | use super::visit::{EdgeRef, GraphBase, IntoEdges, VisitMap, Visitable}; | 
|  | use crate::scored::MinScored; | 
|  |  | 
|  | use crate::algo::Measure; | 
|  |  | 
|  | /// \[Generic\] A* shortest path algorithm. | 
|  | /// | 
|  | /// Computes the shortest path from `start` to `finish`, including the total path cost. | 
|  | /// | 
|  | /// `finish` is implicitly given via the `is_goal` callback, which should return `true` if the | 
|  | /// given node is the finish node. | 
|  | /// | 
|  | /// The function `edge_cost` should return the cost for a particular edge. Edge costs must be | 
|  | /// non-negative. | 
|  | /// | 
|  | /// The function `estimate_cost` should return the estimated cost to the finish for a particular | 
|  | /// node. For the algorithm to find the actual shortest path, it should be admissible, meaning that | 
|  | /// it should never overestimate the actual cost to get to the nearest goal node. Estimate costs | 
|  | /// must also be non-negative. | 
|  | /// | 
|  | /// The graph should be `Visitable` and implement `IntoEdges`. | 
|  | /// | 
|  | /// # Example | 
|  | /// ``` | 
|  | /// use petgraph::Graph; | 
|  | /// use petgraph::algo::astar; | 
|  | /// | 
|  | /// let mut g = Graph::new(); | 
|  | /// let a = g.add_node((0., 0.)); | 
|  | /// let b = g.add_node((2., 0.)); | 
|  | /// let c = g.add_node((1., 1.)); | 
|  | /// let d = g.add_node((0., 2.)); | 
|  | /// let e = g.add_node((3., 3.)); | 
|  | /// let f = g.add_node((4., 2.)); | 
|  | /// g.extend_with_edges(&[ | 
|  | ///     (a, b, 2), | 
|  | ///     (a, d, 4), | 
|  | ///     (b, c, 1), | 
|  | ///     (b, f, 7), | 
|  | ///     (c, e, 5), | 
|  | ///     (e, f, 1), | 
|  | ///     (d, e, 1), | 
|  | /// ]); | 
|  | /// | 
|  | /// // Graph represented with the weight of each edge | 
|  | /// // Edges with '*' are part of the optimal path. | 
|  | /// // | 
|  | /// //     2       1 | 
|  | /// // a ----- b ----- c | 
|  | /// // | 4*    | 7     | | 
|  | /// // d       f       | 5 | 
|  | /// // | 1*    | 1*    | | 
|  | /// // \------ e ------/ | 
|  | /// | 
|  | /// let path = astar(&g, a, |finish| finish == f, |e| *e.weight(), |_| 0); | 
|  | /// assert_eq!(path, Some((6, vec![a, d, e, f]))); | 
|  | /// ``` | 
|  | /// | 
|  | /// Returns the total cost + the path of subsequent `NodeId` from start to finish, if one was | 
|  | /// found. | 
|  | pub fn astar<G, F, H, K, IsGoal>( | 
|  | graph: G, | 
|  | start: G::NodeId, | 
|  | mut is_goal: IsGoal, | 
|  | mut edge_cost: F, | 
|  | mut estimate_cost: H, | 
|  | ) -> Option<(K, Vec<G::NodeId>)> | 
|  | where | 
|  | G: IntoEdges + Visitable, | 
|  | IsGoal: FnMut(G::NodeId) -> bool, | 
|  | G::NodeId: Eq + Hash, | 
|  | F: FnMut(G::EdgeRef) -> K, | 
|  | H: FnMut(G::NodeId) -> K, | 
|  | K: Measure + Copy, | 
|  | { | 
|  | let mut visited = graph.visit_map(); | 
|  | let mut visit_next = BinaryHeap::new(); | 
|  | let mut scores = HashMap::new(); | 
|  | let mut path_tracker = PathTracker::<G>::new(); | 
|  |  | 
|  | let zero_score = K::default(); | 
|  | scores.insert(start, zero_score); | 
|  | visit_next.push(MinScored(estimate_cost(start), start)); | 
|  |  | 
|  | while let Some(MinScored(_, node)) = visit_next.pop() { | 
|  | if is_goal(node) { | 
|  | let path = path_tracker.reconstruct_path_to(node); | 
|  | let cost = scores[&node]; | 
|  | return Some((cost, path)); | 
|  | } | 
|  |  | 
|  | // Don't visit the same node several times, as the first time it was visited it was using | 
|  | // the shortest available path. | 
|  | if !visited.visit(node) { | 
|  | continue; | 
|  | } | 
|  |  | 
|  | // This lookup can be unwrapped without fear of panic since the node was necessarily scored | 
|  | // before adding him to `visit_next`. | 
|  | let node_score = scores[&node]; | 
|  |  | 
|  | for edge in graph.edges(node) { | 
|  | let next = edge.target(); | 
|  | if visited.is_visited(&next) { | 
|  | continue; | 
|  | } | 
|  |  | 
|  | let mut next_score = node_score + edge_cost(edge); | 
|  |  | 
|  | match scores.entry(next) { | 
|  | Occupied(ent) => { | 
|  | let old_score = *ent.get(); | 
|  | if next_score < old_score { | 
|  | *ent.into_mut() = next_score; | 
|  | path_tracker.set_predecessor(next, node); | 
|  | } else { | 
|  | next_score = old_score; | 
|  | } | 
|  | } | 
|  | Vacant(ent) => { | 
|  | ent.insert(next_score); | 
|  | path_tracker.set_predecessor(next, node); | 
|  | } | 
|  | } | 
|  |  | 
|  | let next_estimate_score = next_score + estimate_cost(next); | 
|  | visit_next.push(MinScored(next_estimate_score, next)); | 
|  | } | 
|  | } | 
|  |  | 
|  | None | 
|  | } | 
|  |  | 
|  | struct PathTracker<G> | 
|  | where | 
|  | G: GraphBase, | 
|  | G::NodeId: Eq + Hash, | 
|  | { | 
|  | came_from: HashMap<G::NodeId, G::NodeId>, | 
|  | } | 
|  |  | 
|  | impl<G> PathTracker<G> | 
|  | where | 
|  | G: GraphBase, | 
|  | G::NodeId: Eq + Hash, | 
|  | { | 
|  | fn new() -> PathTracker<G> { | 
|  | PathTracker { | 
|  | came_from: HashMap::new(), | 
|  | } | 
|  | } | 
|  |  | 
|  | fn set_predecessor(&mut self, node: G::NodeId, previous: G::NodeId) { | 
|  | self.came_from.insert(node, previous); | 
|  | } | 
|  |  | 
|  | fn reconstruct_path_to(&self, last: G::NodeId) -> Vec<G::NodeId> { | 
|  | let mut path = vec![last]; | 
|  |  | 
|  | let mut current = last; | 
|  | while let Some(&previous) = self.came_from.get(¤t) { | 
|  | path.push(previous); | 
|  | current = previous; | 
|  | } | 
|  |  | 
|  | path.reverse(); | 
|  |  | 
|  | path | 
|  | } | 
|  | } |