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| 1 | +# 1043. Partition Array for Maximum Sum |
| 2 | + |
| 3 | +- Difficulty: Medium. |
| 4 | +- Related Topics: Array, Dynamic Programming. |
| 5 | +- Similar Questions: Subsequence of Size K With the Largest Even Sum. |
| 6 | + |
| 7 | +## Problem |
| 8 | + |
| 9 | +Given an integer array ```arr```, partition the array into (contiguous) subarrays of length **at most** ```k```. After partitioning, each subarray has their values changed to become the maximum value of that subarray. |
| 10 | + |
| 11 | +Return **the largest sum of the given array after partitioning. Test cases are generated so that the answer fits in a **32-bit** integer.** |
| 12 | + |
| 13 | + |
| 14 | +Example 1: |
| 15 | + |
| 16 | +``` |
| 17 | +Input: arr = [1,15,7,9,2,5,10], k = 3 |
| 18 | +Output: 84 |
| 19 | +Explanation: arr becomes [15,15,15,9,10,10,10] |
| 20 | +``` |
| 21 | + |
| 22 | +Example 2: |
| 23 | + |
| 24 | +``` |
| 25 | +Input: arr = [1,4,1,5,7,3,6,1,9,9,3], k = 4 |
| 26 | +Output: 83 |
| 27 | +``` |
| 28 | + |
| 29 | +Example 3: |
| 30 | + |
| 31 | +``` |
| 32 | +Input: arr = [1], k = 1 |
| 33 | +Output: 1 |
| 34 | +``` |
| 35 | + |
| 36 | + |
| 37 | +**Constraints:** |
| 38 | + |
| 39 | + |
| 40 | + |
| 41 | +- ```1 <= arr.length <= 500``` |
| 42 | + |
| 43 | +- ```0 <= arr[i] <= 109``` |
| 44 | + |
| 45 | +- ```1 <= k <= arr.length``` |
| 46 | + |
| 47 | + |
| 48 | + |
| 49 | +## Solution |
| 50 | + |
| 51 | +```javascript |
| 52 | +/** |
| 53 | + * @param {number[]} arr |
| 54 | + * @param {number} k |
| 55 | + * @return {number} |
| 56 | + */ |
| 57 | +var maxSumAfterPartitioning = function(arr, k) { |
| 58 | + var dp = Array(arr.length).fill(0); |
| 59 | + for (var i = 0; i < arr.length; i++) { |
| 60 | + var maxValue = 0; |
| 61 | + for (var j = 1; j <= k && j - 1 <= i; j++) { |
| 62 | + maxValue = Math.max(maxValue, arr[i - j + 1]); |
| 63 | + dp[i] = Math.max(dp[i], ( dp[i - j + 1] + maxValue * j); |
| 64 | + } |
| 65 | + } |
| 66 | + return dp[arr.length]; |
| 67 | +}; |
| 68 | +``` |
| 69 | +
|
| 70 | +**Explain:** |
| 71 | +
|
| 72 | +`dp[i + 1]` represents array `[0 ... i]` 's maxSumAfterPartitioning. (dp[0] = 0 means nothing, it just helps calculate.) |
| 73 | +
|
| 74 | +``` |
| 75 | +dp[i] = max( |
| 76 | + dp[i - 1] + max(arr[i]) * 1, |
| 77 | + dp[i - 2] + max(arr[i], arr[i - 1]) * 2, |
| 78 | + ... |
| 79 | + dp[i - k] + max(arr[i], arr[i - 1], ..., arr[i - k]) * k |
| 80 | +) |
| 81 | +``` |
| 82 | +
|
| 83 | +`dp[arr.length - 1]` would be the answer in the end of the iteration. |
| 84 | +
|
| 85 | +**Complexity:** |
| 86 | +
|
| 87 | +* Time complexity : O(n). |
| 88 | +* Space complexity : O(n). |
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