987. Vertical Order Traversal of a Binary Tree
Description
Given the root
of a binary tree, calculate the vertical order traversal of the binary tree.
For each node at position (row, col)
, its left and right children will be at positions (row + 1, col - 1)
and (row + 1, col + 1)
respectively. The root of the tree is at (0, 0)
.
The vertical order traversal of a binary tree is a list of top-to-bottom orderings for each column index starting from the leftmost column and ending on the rightmost column. There may be multiple nodes in the same row and same column. In such a case, sort these nodes by their values.
Return the vertical order traversal of the binary tree.
Example 1:
Input: root = [3,9,20,null,null,15,7] Output: [[9],[3,15],[20],[7]] Explanation: Column -1: Only node 9 is in this column. Column 0: Nodes 3 and 15 are in this column in that order from top to bottom. Column 1: Only node 20 is in this column. Column 2: Only node 7 is in this column.
Example 2:
Input: root = [1,2,3,4,5,6,7] Output: [[4],[2],[1,5,6],[3],[7]] Explanation: Column -2: Only node 4 is in this column. Column -1: Only node 2 is in this column. Column 0: Nodes 1, 5, and 6 are in this column. 1 is at the top, so it comes first. 5 and 6 are at the same position (2, 0), so we order them by their value, 5 before 6. Column 1: Only node 3 is in this column. Column 2: Only node 7 is in this column.
Example 3:
Input: root = [1,2,3,4,6,5,7] Output: [[4],[2],[1,5,6],[3],[7]] Explanation: This case is the exact same as example 2, but with nodes 5 and 6 swapped. Note that the solution remains the same since 5 and 6 are in the same location and should be ordered by their values.
Constraints:
- The number of nodes in the tree is in the range
[1, 1000]
. 0 <= Node.val <= 1000
Solutions
Solution 1: DFS + Sorting
We design a function $dfs(root, i, j)$, where $i$ and $j$ represent the row and column of the current node. We can record the row and column information of the nodes through depth-first search, store it in an array or list $nodes$, and then sort $nodes$ in the order of column, row, and value.
Next, we traverse $nodes$, putting the values of nodes in the same column into the same list, and finally return these lists.
The time complexity is $O(n \times \log n)$, and the space complexity is $O(n)$. Here, $n$ is the number of nodes in the binary tree.
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