The problem is to find the shortest distances between every pair of vertices in a given edge-weighted directed graph. The graph is represented as an adjacency matrix of size n*n. Matrix[i][j] denotes the weight of the edge from i to j. If Matrix[i][j]=-1, it means there is no edge from i to j.
Do it in-place.
Example 1:
Input: matrix = {{0,25},{-1,0}}
Output: {{0,25},{-1,0}}
Explanation: The shortest distance between
every pair is already given(if it exists).
Example 2:
Input: matrix = {{0,1,43},{1,0,6},{-1,-1,0}}
Output: {{0,1,7},{1,0,6},{-1,-1,0}}
Explanation: We can reach 2 from 0 as 0->1->2
and the cost will be 1+6=7 which is less than
43.
Your Task:
You don't need to read, return or print anything. Your task is to complete the function shortest_distance() which takes the matrix as input parameter and modifies the distances for every pair in-place.
Expected Time Complexity: O(n^{3})
Expected Space Complexity: O(1)
Constraints:
1 <= n <= 100
-1 <= matrix[ i ][ j ] <= 1000

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