Description

Given a binary tree, return the bottom-up level order traversal of its nodes’ values. (ie, from left to right, level by level from leaf to root).

For example: Given binary tree [3,9,20,null,null,15,7],

    3
   / \
  9  20
    /  \
   15   7

return its bottom-up level order traversal as:

[
  [15,7],
  [9,20],
  [3]
]

Solutions

  先用 BFS 遍历,然后反着输出就行。

1. BFS

  使用两个指针的方式判断什么时候换行,效果不是很好:

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.left = None
#         self.right = None

class Solution(object):
    def levelOrderBottom(self, root):
        """
        :type root: TreeNode
        :rtype: List[List[int]]
        """
        if not root:
            return []
        res = []
        queue = [root]
        last = nxt_last = root
        level = []
        while queue:
            node = queue.pop()
            level.append(node.val)
            if node.left:
                queue.insert(0, node.left)
                # level.append(node.left.val)
                nxt_last = node.left
            if node.right:
                queue.insert(0, node.right)
                # level.append(node.right.val)
                nxt_last = node.right
            if node == last:
                last = nxt_last
                res.append(level)
                level = []
            
        return res[::-1]
# Runtime: 32 ms, faster than 7.82% of Python online submissions for Binary Tree Level Order Traversal II.
# Memory Usage: 12.3 MB, less than 56.52% of Python online submissions for Binary Tree Level Order Traversal II.

  这里比较慢的原因是在每一轮都用上了 insert 时间复杂度为 $O(N)$ 的操作,所以总体复杂度是 $O(N)$,那么可以用 python 的容器类来实现 queue 的操作,并采用常用的 BFS 方式:

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.left = None
#         self.right = None

class Solution(object):
    def levelOrderBottom(self, root):
        """
        :type root: TreeNode
        :rtype: List[List[int]]
        """
        if not root:
            return []
        res = []
        queue = collections.deque([(root, 0)])
        
        while queue:
            node, level = queue.popleft()
            if node:
                if level == len(res):
                    res.append([])
                res[level].append(node.val)
                queue.append((node.left, level + 1))
                queue.append((node.right, level + 1))
        return res[::-1]
            
# Runtime: 20 ms, faster than 81.64% of Python online submissions for Binary Tree Level Order Traversal II.
# Memory Usage: 12.2 MB, less than 78.26% of Python online submissions for Binary Tree Level Order Traversal II.

References

  1. 107. Binary Tree Level Order Traversal II
  2. Python solutions (dfs recursively, dfs+stack, bfs+queue).