There are n
cities numbered from 0
to n-1
. Given the array edges
where edges[i] = [fromi, toi, weighti]
represents a bidirectional and weighted edge between cities fromi
and toi
, and given the integer distanceThreshold
.
Return the city with the smallest number of cities that are reachable through some path and whose distance is at most distanceThreshold
, If there are multiple such cities, return the city with the greatest number.
Notice that the distance of a path connecting cities i and j is equal to the sum of the edges' weights along that path.
Input: n = 4, edges = [[0,1,3],[1,2,1],[1,3,4],[2,3,1]], distanceThreshold = 4 Output: 3 Explanation: The figure above describes the graph. The neighboring cities at a distanceThreshold = 4 for each city are: City 0 -> [City 1, City 2] City 1 -> [City 0, City 2, City 3] City 2 -> [City 0, City 1, City 3] City 3 -> [City 1, City 2] Cities 0 and 3 have 2 neighboring cities at a distanceThreshold = 4, but we have to return city 3 since it has the greatest number.
Input: n = 5, edges = [[0,1,2],[0,4,8],[1,2,3],[1,4,2],[2,3,1],[3,4,1]], distanceThreshold = 2 Output: 0 Explanation: The figure above describes the graph. The neighboring cities at a distanceThreshold = 2 for each city are: City 0 -> [City 1] City 1 -> [City 0, City 4] City 2 -> [City 3, City 4] City 3 -> [City 2, City 4] City 4 -> [City 1, City 2, City 3] The city 0 has 1 neighboring city at a distanceThreshold = 2.
2 <= n <= 100
1 <= edges.length <= n * (n - 1) / 2
edges[i].length == 3
0 <= fromi < toi < n
1 <= weighti, distanceThreshold <= 10^4
- All pairs
(fromi, toi)
are distinct.
use std::collections::BinaryHeap;
use std::collections::HashSet;
impl Solution {
pub fn find_the_city(n: i32, edges: Vec<Vec<i32>>, distance_threshold: i32) -> i32 {
let n = n as usize;
let mut to_cities = vec![vec![]; n];
let mut min_reachable = usize::MAX;
let mut ret = 0;
for edge in &edges {
if edge[2] <= distance_threshold {
to_cities[edge[0] as usize].push((edge[1] as usize, edge[2]));
to_cities[edge[1] as usize].push((edge[0] as usize, edge[2]));
}
}
for i in 0..n {
let mut heap = BinaryHeap::from([(0, i)]);
let mut visited = HashSet::new();
while let Some((weight, from)) = heap.pop() {
visited.insert(from);
for &(to, w) in &to_cities[from] {
if !visited.contains(&to) && -weight + w <= distance_threshold {
heap.push((weight - w, to));
}
}
}
if visited.len() <= min_reachable {
min_reachable = visited.len();
ret = i;
}
}
ret as i32
}
}