834. Sum of Distances in Tree
Difficulty: Hard
Topics: Dynamic Programming
, Tree
, Depth-First Search
, Graph
There is an undirected connected tree with n
nodes labeled from 0
to n - 1
and n - 1
edges.
You are given the integer n
and the array edges
where edges[i] = [ai, bi]
indicates that there is an edge between nodes ai and bi in the tree.
Return an array answer
of length n
where answer[i]
is the sum of the distances between the ith
node in the tree and all other nodes.
Example 1:
- Input: n = 6, edges = [[0,1],[0,2],[2,3],[2,4],[2,5]]
- Output: [8,12,6,10,10,10]
- Explanation: The tree is shown above. We can see that dist(0,1) + dist(0,2) + dist(0,3) + dist(0,4) + dist(0,5) equals 1 + 1 + 2 + 2 + 2 = 8. Hence, answer[0] = 8, and so on.
Example 2:
- Input: n = 1, edges = []
- Output: [0]
Example 3:
- Input: n = 2, edges = [[1,0]]
- Output: [1,1]
Constraints:
1 <= n <= 3 * 104
edges.length == n - 1
edges[i].length == 2
0 <= ai, bi < n
ai != bi
- The given input represents a valid tree.
Solution:
We use a combination of Depth-First Search (DFS) and dynamic programming techniques. The goal is to efficiently compute the sum of distances for each node in a tree with n
nodes and n-1
edges.
Approach:
- Tree Representation: Represent the tree using an adjacency list. This helps in efficient traversal using DFS.
-
First DFS (
dfs1
):- Calculate the size of each subtree.
- Compute the sum of distances from the root node to all other nodes.
-
Second DFS (
dfs2
):- Use the results from the first DFS to compute the sum of distances for all nodes.
- Adjust the results based on the parent's result.
Detailed Steps:
- Build the Graph: Convert the edge list into an adjacency list for efficient traversal.
-
First DFS:
- Start from the root node (typically node
0
). - Compute the size of each subtree and the total distance from the root node to all other nodes.
- Start from the root node (typically node
-
Second DFS:
- Compute the distance sums for all nodes using the information from the first DFS.
- Adjust the distance sum based on the parent node’s result.
Let's implement this solution in PHP: 834. Sum of Distances in Tree
<?php
/**
* @param Integer $n
* @param Integer[][] $edges
* @return Integer[]
*/
function sumOfDistancesInTree($n, $edges) {
...
...
...
/**
* go to ./solution.php
*/
}
// Example usage
$n1 = 6;
$edges1 = [[0,1],[0,2],[2,3],[2,4],[2,5]];
print_r(sumOfDistancesInTree($n1, $edges1)); // Output: [8,12,6,10,10,10]
$n2 = 1;
$edges2 = [];
print_r(sumOfDistancesInTree($n2, $edges2)); // Output: [0]
$n3 = 2;
$edges3 = [[1,0]];
print_r(sumOfDistancesInTree($n3, $edges3)); // Output: [1,1]
?>
Explanation:
-
Graph Construction:
array_fill
initializes the adjacency list,ans
, andsize
arrays. -
dfs1
Function: Calculates the total distance from the root and subtree sizes. -
dfs2
Function: Adjusts distances for all nodes based on the result fromdfs1
.
This approach efficiently computes the required distances using two DFS traversals, achieving a time complexity of O(n)
, which is suitable for large trees as specified in the problem constraints.
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