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Formatted question description: https://leetcode.ca/all/1334.html
1334. Find the City With the Smallest Number of Neighbors at a Threshold Distance (Medium)
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.
Example 1:
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.
Example 2:
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.
Constraints:
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.
Related Topics:
Graph
Solution 1.
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class Solution { public int findTheCity(int n, int[][] edges, int distanceThreshold) { Map<Integer, List<int[]>> distancesMap = new HashMap<Integer, List<int[]>>(); for (int[] edge : edges) { int city1 = edge[0], city2 = edge[1], distance = edge[2]; List<int[]> list1 = distancesMap.getOrDefault(city1, new ArrayList<int[]>()); List<int[]> list2 = distancesMap.getOrDefault(city2, new ArrayList<int[]>()); list1.add(new int[]{city2, distance}); list2.add(new int[]{city1, distance}); distancesMap.put(city1, list1); distancesMap.put(city2, list2); } int[] reachableCounts = new int[n]; for (int i = 0; i < n; i++) { int[] distances = getDistance(n, i, distancesMap); for (int distance : distances) { if (distance > 0 && distance <= distanceThreshold) reachableCounts[i]++; } } int minReachable = n - 1; for (int i = 0; i < n; i++) minReachable = Math.min(minReachable, reachableCounts[i]); int cityIndex = 0; for (int i = n - 1; i >= 0; i--) { if (reachableCounts[i] == minReachable) { cityIndex = i; break; } } return cityIndex; } public int[] getDistance(int n, int source, Map<Integer, List<int[]>> distancesMap) { int[] distances = new int[n]; for (int i = 0; i < n; i++) distances[i] = Integer.MAX_VALUE; distances[source] = 0; PriorityQueue<CityDistance> priorityQueue = new PriorityQueue<CityDistance>(); priorityQueue.offer(new CityDistance(source, 0)); while (!priorityQueue.isEmpty()) { CityDistance cityDistance = priorityQueue.poll(); int city = cityDistance.city, distance = cityDistance.distance; if (distance > distances[city]) continue; List<int[]> adjacentCities = distancesMap.getOrDefault(city, new ArrayList<int[]>()); for (int[] adjacentCity : adjacentCities) { int nextCity = adjacentCity[0], nextDistance = adjacentCity[1]; int newDistance = distance + nextDistance; if (newDistance < distances[nextCity]) { distances[nextCity] = newDistance; priorityQueue.offer(new CityDistance(nextCity, newDistance)); } } } return distances; } } class CityDistance implements Comparable<CityDistance> { public int city; public int distance; public CityDistance(int city, int distance) { this.city = city; this.distance = distance; } public int compareTo(CityDistance cityDistance2) { return this.distance - cityDistance2.distance; } } ############ class Solution { private int n; private int[][] g; private int[] dist; private boolean[] vis; private int inf = 1 << 30; private int distanceThreshold; public int findTheCity(int n, int[][] edges, int distanceThreshold) { this.n = n; this.distanceThreshold = distanceThreshold; g = new int[n][n]; dist = new int[n]; vis = new boolean[n]; for (var e : g) { Arrays.fill(e, inf); } for (var e : edges) { int f = e[0], t = e[1], w = e[2]; g[f][t] = w; g[t][f] = w; } int ans = n, t = inf; for (int i = n - 1; i >= 0; --i) { int cnt = dijkstra(i); if (t > cnt) { t = cnt; ans = i; } } return ans; } private int dijkstra(int u) { Arrays.fill(dist, inf); Arrays.fill(vis, false); dist[u] = 0; for (int i = 0; i < n; ++i) { int k = -1; for (int j = 0; j < n; ++j) { if (!vis[j] && (k == -1 || dist[k] > dist[j])) { k = j; } } vis[k] = true; for (int j = 0; j < n; ++j) { dist[j] = Math.min(dist[j], dist[k] + g[k][j]); } } int cnt = 0; for (int d : dist) { if (d <= distanceThreshold) { ++cnt; } } return cnt; } }
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// OJ: https://leetcode.com/problems/find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance/ // Time: O(V * (E + VlogV)) // Space: O(E) class Solution { typedef pair<int, int> iPair; unordered_map<int, vector<iPair>> graph; int th, N, minNum = INT_MAX; int dijkstra(int i) { priority_queue<iPair, vector<iPair>, greater<iPair>> q; vector<int> dist(N, INT_MAX); q.push(make_pair(0, i)); dist[i] = 0; while (q.size()) { int u = q.top().second; q.pop(); for (auto ne : graph[u]) { int v = ne.first; int w = ne.second; if (dist[v] > dist[u] + w) { dist[v] = dist[u] + w; q.push(make_pair(dist[v], v)); } } } int cnt = 0; for (int j = 0; j < N; ++j) { if (j != i && dist[j] <= th) ++cnt; } return cnt; } public: int findTheCity(int n, vector<vector<int>>& edges, int distanceThreshold) { th = distanceThreshold; N = n; for (auto e : edges) { m[e[0]].push_back(make_pair(e[1], e[2])); m[e[1]].push_back(make_pair(e[0], e[2])); } int ans = 0; for (int i = 0; i < n; ++i) { int cnt = dijkstra(i); if (cnt <= minNum) { minNum = cnt; ans = i; } } return ans; } };
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class Solution: def findTheCity( self, n: int, edges: List[List[int]], distanceThreshold: int ) -> int: def dijkstra(u): dist = [inf] * n dist[u] = 0 vis = [False] * n for _ in range(n): k = -1 for j in range(n): if not vis[j] and (k == -1 or dist[k] > dist[j]): k = j vis[k] = True for j in range(n): dist[j] = min(dist[j], dist[k] + g[k][j]) return sum(d <= distanceThreshold for d in dist) g = [[inf] * n for _ in range(n)] for f, t, w in edges: g[f][t] = g[t][f] = w ans = n t = inf for i in range(n - 1, -1, -1): if (cnt := dijkstra(i)) < t: t = cnt ans = i return ans
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func findTheCity(n int, edges [][]int, distanceThreshold int) int { g := make([][]int, n) dist := make([]int, n) vis := make([]bool, n) const inf int = 1e7 for i := range g { g[i] = make([]int, n) for j := range g[i] { g[i][j] = inf } } for _, e := range edges { f, t, w := e[0], e[1], e[2] g[f][t], g[t][f] = w, w } ans, t := n, inf dijkstra := func(u int) (cnt int) { for i := range vis { vis[i] = false dist[i] = inf } dist[u] = 0 for i := 0; i < n; i++ { k := -1 for j := 0; j < n; j++ { if !vis[j] && (k == -1 || dist[j] < dist[k]) { k = j } } vis[k] = true for j := 0; j < n; j++ { dist[j] = min(dist[j], dist[k]+g[k][j]) } } for _, d := range dist { if d <= distanceThreshold { cnt++ } } return } for i := n - 1; i >= 0; i-- { cnt := dijkstra(i) if t > cnt { t = cnt ans = i } } return ans } func min(a, b int) int { if a < b { return a } return b }