1588. Sum of All Odd Length Subarrays
Description
Given an array of positive integers arr
, return the sum of all possible odd-length subarrays of arr
.
A subarray is a contiguous subsequence of the array.
Example 1:
Input: arr = [1,4,2,5,3] Output: 58 Explanation: The odd-length subarrays of arr and their sums are: [1] = 1 [4] = 4 [2] = 2 [5] = 5 [3] = 3 [1,4,2] = 7 [4,2,5] = 11 [2,5,3] = 10 [1,4,2,5,3] = 15 If we add all these together we get 1 + 4 + 2 + 5 + 3 + 7 + 11 + 10 + 15 = 58
Example 2:
Input: arr = [1,2] Output: 3 Explanation: There are only 2 subarrays of odd length, [1] and [2]. Their sum is 3.
Example 3:
Input: arr = [10,11,12] Output: 66
Constraints:
1 <= arr.length <= 100
1 <= arr[i] <= 1000
Follow up:
Could you solve this problem in O(n) time complexity?
Solutions
Solution 1: Dynamic Programming
We define two arrays $f$ and $g$ of length $n$, where $f[i]$ represents the sum of subarrays ending at $\textit{arr}[i]$ with odd lengths, and $g[i]$ represents the sum of subarrays ending at $\textit{arr}[i]$ with even lengths. Initially, $f[0] = \textit{arr}[0]$, and $g[0] = 0$. The answer is $\sum_{i=0}^{n-1} f[i]$.
When $i > 0$, consider how $f[i]$ and $g[i]$ transition:
For the state $f[i]$, the element $\textit{arr}[i]$ can form an odd-length subarray with the previous $g[i-1]$. The number of such subarrays is $(i / 2) + 1$, so $f[i] = g[i-1] + \textit{arr}[i] \times ((i / 2) + 1)$.
For the state $g[i]$, when $i = 0$, there are no even-length subarrays, so $g[0] = 0$. When $i > 0$, the element $\textit{arr}[i]$ can form an even-length subarray with the previous $f[i-1]$. The number of such subarrays is $(i + 1) / 2$, so $g[i] = f[i-1] + \textit{arr}[i] \times ((i + 1) / 2)$.
The final answer is $\sum_{i=0}^{n-1} f[i]$.
The time complexity is $O(n)$, and the space complexity is $O(n)$. Here, $n$ is the length of the array $\textit{arr}$.
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Solution 2: Dynamic Programming (Space Optimization)
We notice that the values of $f[i]$ and $g[i]$ only depend on $f[i - 1]$ and $g[i - 1]$. Therefore, we can use two variables $f$ and $g$ to record the values of $f[i - 1]$ and $g[i - 1]$, respectively, thus optimizing the space complexity.
The time complexity is $O(n)$, and the space complexity is $O(1)$.
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