376. Wiggle Subsequence 摆动序列
【LeetCode】376. Wiggle Subsequence 解题报告(Python)
Section titled “【LeetCode】376. Wiggle Subsequence 解题报告(Python)”作者: 负雪明烛 id: fuxuemingzhu 个人博客: https://fuxuemingzhu.cn/
题目地址: https://leetcode.com/problems/wiggle-subsequence/description/
A sequence of numbers is called a wiggle sequence if the differences between successive numbers strictly alternate between positive and negative. The first difference (if one exists) may be either positive or negative. A sequence with fewer than two elements is trivially a wiggle sequence.
For example, [1,7,4,9,2,5] is a wiggle sequence because the differences (6,-3,5,-7,3) are alternately positive and negative. In contrast, [1,4,7,2,5] and [1,7,4,5,5] are not wiggle sequences, the first because its first two differences are positive and the second because its last difference is zero.
Given a sequence of integers, return the length of the longest subsequence that is a wiggle sequence. A subsequence is obtained by deleting some number of elements (eventually, also zero) from the original sequence, leaving the remaining elements in their original order.
Example 1:
Input: [1,7,4,9,2,5]Output: 6Explanation: The entire sequence is a wiggle sequence.Example 2:
Input: [1,17,5,10,13,15,10,5,16,8]Output: 7Explanation: There are several subsequences that achieve this length. One is [1,17,10,13,10,16,8].Example 3:
Input: [1,2,3,4,5,6,7,8,9]Output: 2Follow up:
Can you do it in O(n) time?
如果一个数组里面,相邻的两个数字的差是正负交替的,那么认为这个是波动序列。求输入的数组里面最长的波动序列长度。
明显的DP问题,本来的想法是用个二维DP,可是提交了几遍只通过了部分测试用例。才去看的别人的两个DP数组的解法。
定义了一个记录递增的DP数组inc,一个记录递减的DP数组dec,这两个DP数组分别保存的是开头元素是递增、递减的最长波动序列长度。对于每个位置,从头遍历,如果当前的元素比前面的元素大,应该更新递增数组,否则,如果比前面的数字小,那么应该更新递减数组。
时间复杂度是O(N^2),空间复杂度是O(N).
class Solution(object): def wiggleMaxLength(self, nums): """ :type nums: List[int] :rtype: int """ n = len(nums) if n <= 1: return n inc, dec = [1] * n, [1] * n for x in range(n): for y in range(x): if nums[x] > nums[y]: inc[x] = max(inc[x], dec[y] + 1) elif nums[x] < nums[y]: dec[x] = max(dec[x], inc[y] + 1) return max(inc[-1], dec[-1])其实不需要从头遍历,只需要知道前面元素对应的最长递增和递减数组即可。
时间复杂度是O(N),空间复杂度是O(N).
class Solution(object): def wiggleMaxLength(self, nums): """ :type nums: List[int] :rtype: int """ n = len(nums) if n <= 1: return n inc, dec = [1] * n, [1] * n for x in range(1, n): if nums[x] > nums[x - 1]: inc[x] = dec[x - 1] + 1 dec[x] = dec[x - 1] elif nums[x] < nums[x - 1]: inc[x] = inc[x - 1] dec[x] = inc[x - 1] + 1 else: inc[x] = inc[x - 1] dec[x] = dec[x - 1] return max(inc[-1], dec[-1])简单分析代码就可以看出,每个元素都只和它之前的元素相关,因此,只需要使用两个变量即可。
时间复杂度是O(N),空间复杂度是O(1).
class Solution(object): def wiggleMaxLength(self, nums): """ :type nums: List[int] :rtype: int """ n = len(nums) if n <= 1: return n inc, dec = 1, 1 for x in range(1, n): if nums[x] > nums[x - 1]: inc = dec + 1 elif nums[x] < nums[x - 1]: dec = inc + 1 return max(inc, dec)参考资料:
https://leetcode.com/articles/wiggle-subsequence/ http://www.cnblogs.com/grandyang/p/5697621.html http://bookshadow.com/weblog/2016/07/21/leetcode-wiggle-subsequence/
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