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Make BinaryHeap Dijkstra example return Option

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jethrogb 2015-12-13 11:40:27 -08:00
parent 69adc883aa
commit 6e46a0fb95
1 changed files with 8 additions and 8 deletions
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16
src/libcollections/binary_heap.rs
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@ -66,7 +66,7 @@
//! // to each node. This implementation isn't memory-efficient as it may leave duplicate
//! // nodes in the queue. It also uses `usize::MAX` as a sentinel value,
//! // for a simpler implementation.
//! fn shortest_path(adj_list: &Vec<Vec<Edge>>, start: usize, goal: usize) -> usize {
//! fn shortest_path(adj_list: &Vec<Vec<Edge>>, start: usize, goal: usize) -> Option<usize> {
//! // dist[node] = current shortest distance from `start` to `node`
//! let mut dist: Vec<_> = (0..adj_list.len()).map(|_| usize::MAX).collect();
//!
@ -79,7 +79,7 @@
//! // Examine the frontier with lower cost nodes first (min-heap)
//! while let Some(State { cost, position }) = heap.pop() {
//! // Alternatively we could have continued to find all shortest paths
//! if position == goal { return cost; }
//! if position == goal { return Some(cost); }
//!
//! // Important as we may have already found a better way
//! if cost > dist[position] { continue; }
@ -99,7 +99,7 @@
//! }
//!
//! // Goal not reachable
//! usize::MAX
//! None
//! }
//!
//! fn main() {
@ -140,11 +140,11 @@
//! // Node 4
//! vec![]];
//!
//! assert_eq!(shortest_path(&graph, 0, 1), 1);
//! assert_eq!(shortest_path(&graph, 0, 3), 3);
//! assert_eq!(shortest_path(&graph, 3, 0), 7);
//! assert_eq!(shortest_path(&graph, 0, 4), 5);
//! assert_eq!(shortest_path(&graph, 4, 0), usize::MAX);
//! assert_eq!(shortest_path(&graph, 0, 1), Some(1));
//! assert_eq!(shortest_path(&graph, 0, 3), Some(3));
//! assert_eq!(shortest_path(&graph, 3, 0), Some(7));
//! assert_eq!(shortest_path(&graph, 0, 4), Some(5));
//! assert_eq!(shortest_path(&graph, 4, 0), None);
//! }
//! ```