978. Longest Turbulent Subarray
Description
Given an integer array arr
, return the length of a maximum size turbulent subarray of arr
.
A subarray is turbulent if the comparison sign flips between each adjacent pair of elements in the subarray.
More formally, a subarray [arr[i], arr[i + 1], ..., arr[j]]
of arr
is said to be turbulent if and only if:
- For
i <= k < j
:arr[k] > arr[k + 1]
whenk
is odd, andarr[k] < arr[k + 1]
whenk
is even.
- Or, for
i <= k < j
:arr[k] > arr[k + 1]
whenk
is even, andarr[k] < arr[k + 1]
whenk
is odd.
Example 1:
Input: arr = [9,4,2,10,7,8,8,1,9] Output: 5 Explanation: arr[1] > arr[2] < arr[3] > arr[4] < arr[5]
Example 2:
Input: arr = [4,8,12,16] Output: 2
Example 3:
Input: arr = [100] Output: 1
Constraints:
1 <= arr.length <= 4 * 104
0 <= arr[i] <= 109
Solutions
Solution 1: Dynamic Programming
We define $f[i]$ as the length of the longest turbulent subarray ending at $\textit{nums}[i]$ with an increasing state, and $g[i]$ as the length of the longest turbulent subarray ending at $\textit{nums}[i]$ with a decreasing state. Initially, $f[0] = 1$, $g[0] = 1$. The answer is $\max(f[i], g[i])$.
For $i \gt 0$, if $\textit{nums}[i] \gt \textit{nums}[i - 1]$, then $f[i] = g[i - 1] + 1$, otherwise $f[i] = 1$; if $\textit{nums}[i] \lt \textit{nums}[i - 1]$, then $g[i] = f[i - 1] + 1$, otherwise $g[i] = 1$.
Since $f[i]$ and $g[i]$ are only related to $f[i - 1]$ and $g[i - 1]$, two variables can be used instead of arrays.
The time complexity is $O(n)$, where $n$ is the length of the array. The space complexity is $O(1)$.
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