Function petgraph::algo::k_shortest_path::k_shortest_path
source · pub fn k_shortest_path<G, F, K>(
graph: G,
start: G::NodeId,
goal: Option<G::NodeId>,
k: usize,
edge_cost: F,
) -> HashMap<G::NodeId, K>
Expand description
[Generic] k’th shortest path algorithm.
Compute the length of the k’th shortest path from start
to every reachable
node.
The graph should be Visitable
and implement IntoEdges
. The function
edge_cost
should return the cost for a particular edge, which is used
to compute path costs. Edge costs must be non-negative.
If goal
is not None
, then the algorithm terminates once the goal
node’s
cost is calculated.
Computes in *O(k * (|E| + |V|log(|V|))) time (average).
Returns a HashMap
that maps NodeId
to path cost.
§Example
use petgraph::Graph;
use petgraph::algo::k_shortest_path;
use petgraph::prelude::*;
use std::collections::HashMap;
let mut graph : Graph<(),(),Directed>= Graph::new();
let a = graph.add_node(()); // node with no weight
let b = graph.add_node(());
let c = graph.add_node(());
let d = graph.add_node(());
let e = graph.add_node(());
let f = graph.add_node(());
let g = graph.add_node(());
let h = graph.add_node(());
// z will be in another connected component
let z = graph.add_node(());
graph.extend_with_edges(&[
(a, b),
(b, c),
(c, d),
(d, a),
(e, f),
(b, e),
(f, g),
(g, h),
(h, e)
]);
// a ----> b ----> e ----> f
// ^ | ^ |
// | v | v
// d <---- c h <---- g
let expected_res: HashMap<NodeIndex, usize> = [
(a, 7),
(b, 4),
(c, 5),
(d, 6),
(e, 5),
(f, 6),
(g, 7),
(h, 8)
].iter().cloned().collect();
let res = k_shortest_path(&graph,b,None,2, |_| 1);
assert_eq!(res, expected_res);
// z is not inside res because there is not path from b to z.