Seawolf 发表于 2020-8-8 03:47:10

Leetcode 987. Vertical Order Traversal of a Binary Tree

Given a binary tree, return the vertical order traversal of its nodes values.

For each node at position (X, Y), its left and right children respectively will be at positions (X-1, Y-1) and (X+1, Y-1).

Running a vertical line from X = -infinity to X = +infinity, whenever the vertical line touches some nodes, we report the values of the nodes in order from top to bottom (decreasing Y coordinates).

If two nodes have the same position, then the value of the node that is reported first is the value that is smaller.

Return an list of non-empty reports in order of X coordinate.Every report will have a list of values of nodes.



Example 1:



Input:
Output: [,,,]
Explanation:
Without loss of generality, we can assume the root node is at position (0, 0):
Then, the node with value 9 occurs at position (-1, -1);
The nodes with values 3 and 15 occur at positions (0, 0) and (0, -2);
The node with value 20 occurs at position (1, -1);
The node with value 7 occurs at position (2, -2).
Example 2:



Input:
Output: [,,,,]
Explanation:
The node with value 5 and the node with value 6 have the same position according to the given scheme.
However, in the report "", the node value of 5 comes first since 5 is smaller than 6.


Note:

The tree will have between 1 and 1000 nodes.
Each node's value will be between 0 and 1000.

# Definition for a binary tree node.
# class TreeNode:
#   def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution:
    def verticalTraversal(self, root: TreeNode) -> List]:
      res = []
      if root == None:
            return res
      hashmap = collections.defaultdict(list)
      queue = []
      cols = []
      max_val = 0
      min_val = 0
      level = 0
      queue.append(root)
      cols.append(0)
      
      while queue:
            size = len(queue)
            for i in range(size):
                curt = queue.pop(0)
                col = cols.pop(0)
                hashmap.append((level, curt.val))
                if curt.left != None:
                  min_val = min(min_val, col - 1)
                  queue.append(curt.left)
                  cols.append(col - 1)
                if curt.right != None:
                  max_val = max(max_val, col + 1)
                  queue.append(curt.right)
                  cols.append(col + 1)
            level += 1
      
      for i in range(min_val, max_val + 1):
            res.append()])
      return res
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