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python - `mid = low + (high -low)//2` 比 `(low + high)//2` 有什么好处?

转载 作者:太空宇宙 更新时间:2023-11-04 00:01:16 29 4
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我正在研究树问题 Convert Sorted Array to Binary Search Tree - LeetCode

Given an array where elements are sorted in ascending order, convert it to a height balanced BST.

For this problem, a height-balanced binary tree is defined as a binary tree in which the depth of the two subtrees of every node never differ by more than 1.

Example:

Given the sorted array: [-10,-3,0,5,9],

One possible answer is: [0,-3,9,-10,null,5], which represents the following height balanced BST:

0
/ \
-3 9
/ /
-10 5

一个直观的 D&Q 解决方案是

class Solution:
def sortedArrayToBST(self, nums: List[int]) -> TreeNode:
"""
Runtime: 64 ms, faster than 84.45%
Memory Usage: 15.5 MB, less than 5.70%
"""
if len(nums) == 0: return None
#if len(nums) == 1: return TreeNode(nums[0])
mid = len(nums) // 2
root = TreeNode(nums[mid])
if len(nums) == 1: return root
if len(nums) > 1:
root.left = self.sortedArrayToBST(nums[:mid])
root.right = self.sortedArrayToBST(nums[mid+1:])
return root

mid 设置为 len(nums)//2(low + high)//2

在阅读其他投稿时,我发现

class Solution:
def sortedArrayToBST(self, nums: List[int]) -> TreeNode:
return self.buildBST(nums, 0, len(nums))

def buildBST(self, nums, left, right):
if right <= left:
return None
if right == left + 1:
return TreeNode(nums[left])

mid = left + (right - left) // 2
root = TreeNode(nums[mid])
root.left = self.buildBST(nums, left, mid)
root.right = self.buildBST(nums, mid + 1, right)

return root

mid 设置为 mid = low + (high -low)//2

mid = low + (high -low)//2 相对于 (low + high)//2 有什么好处?

最佳答案

这是一种避免整数溢出的模式;该代码可能是从一种具有固定大小整数的语言移植而来的。当索引可以变得与用于包含它们的类型一样大时,中间 low + high 值的溢出就会成为一个问题,导致未定义的行为、不正确的结果和漏洞。 (当你是 searching something that’s not an array 时,这甚至会发生在像 size_t 这样的大整数类型上。)

... 但是在 Python 中,没有整数溢出,所以你是对的,你可以做 (low + high)//2

关于python - `mid = low + (high -low)//2` 比 `(low + high)//2` 有什么好处?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/55611990/

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