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1976. Number of Ways to Arrive at Destination

Description

You are in a city that consists of n intersections numbered from 0 to n - 1 with bi-directional roads between some intersections. The inputs are generated such that you can reach any intersection from any other intersection and that there is at most one road between any two intersections.

You are given an integer n and a 2D integer array roads where roads[i] = [ui, vi, timei] means that there is a road between intersections ui and vi that takes timei minutes to travel. You want to know in how many ways you can travel from intersection 0 to intersection n - 1 in the shortest amount of time.

Return the number of ways you can arrive at your destination in the shortest amount of time. Since the answer may be large, return it modulo 109 + 7.

 

Example 1:

Input: n = 7, roads = [[0,6,7],[0,1,2],[1,2,3],[1,3,3],[6,3,3],[3,5,1],[6,5,1],[2,5,1],[0,4,5],[4,6,2]]
Output: 4
Explanation: The shortest amount of time it takes to go from intersection 0 to intersection 6 is 7 minutes.
The four ways to get there in 7 minutes are:
- 0 ➝ 6
- 0 ➝ 4 ➝ 6
- 0 ➝ 1 ➝ 2 ➝ 5 ➝ 6
- 0 ➝ 1 ➝ 3 ➝ 5 ➝ 6

Example 2:

Input: n = 2, roads = [[1,0,10]]
Output: 1
Explanation: There is only one way to go from intersection 0 to intersection 1, and it takes 10 minutes.

 

Constraints:

  • 1 <= n <= 200
  • n - 1 <= roads.length <= n * (n - 1) / 2
  • roads[i].length == 3
  • 0 <= ui, vi <= n - 1
  • 1 <= timei <= 109
  • ui != vi
  • There is at most one road connecting any two intersections.
  • You can reach any intersection from any other intersection.

Solutions

Solution 1: Naive Dijkstra Algorithm

We define the following arrays:

  • g represents the adjacency matrix of the graph. g[i][j] represents the shortest path length from point i to point j. Initially, all are infinity, while g[0][0] is 0. Then we traverse roads and update g[u][v] and g[v][u] to t.
  • dist[i] represents the shortest path length from the starting point to point i. Initially, all are infinity, while dist[0] is 0.
  • f[i] represents the number of shortest paths from the starting point to point i. Initially, all are 0, while f[0] is 1.
  • vis[i] represents whether point i has been visited. Initially, all are False.

Then, we use the naive Dijkstra algorithm to find the shortest path length from the starting point to the end point, and record the number of shortest paths for each point during the process.

Finally, we return f[n - 1]. Since the answer may be very large, we need to take the modulus of $10^9 + 7$.

The time complexity is $O(n^2)$, and the space complexity is $O(n^2)$, where $n$ is the number of points.

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class Solution:
    def countPaths(self, n: int, roads: List[List[int]]) -> int:
        g = [[inf] * n for _ in range(n)]
        for u, v, t in roads:
            g[u][v] = g[v][u] = t
        g[0][0] = 0
        dist = [inf] * n
        dist[0] = 0
        f = [0] * n
        f[0] = 1
        vis = [False] * n
        for _ in range(n):
            t = -1
            for j in range(n):
                if not vis[j] and (t == -1 or dist[j] < dist[t]):
                    t = j
            vis[t] = True
            for j in range(n):
                if j == t:
                    continue
                ne = dist[t] + g[t][j]
                if dist[j] > ne:
                    dist[j] = ne
                    f[j] = f[t]
                elif dist[j] == ne:
                    f[j] += f[t]
        mod = 10**9 + 7
        return f[-1] % mod
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class Solution {
    public int countPaths(int n, int[][] roads) {
        final long inf = Long.MAX_VALUE / 2;
        final int mod = (int) 1e9 + 7;
        long[][] g = new long[n][n];
        for (var e : g) {
            Arrays.fill(e, inf);
        }
        for (var r : roads) {
            int u = r[0], v = r[1], t = r[2];
            g[u][v] = t;
            g[v][u] = t;
        }
        g[0][0] = 0;
        long[] dist = new long[n];
        Arrays.fill(dist, inf);
        dist[0] = 0;
        long[] f = new long[n];
        f[0] = 1;
        boolean[] vis = new boolean[n];
        for (int i = 0; i < n; ++i) {
            int t = -1;
            for (int j = 0; j < n; ++j) {
                if (!vis[j] && (t == -1 || dist