1031. Maximum Sum of Two Non-Overlapping Subarrays

package LeetCode_1031

/**
 * 1031. Maximum Sum of Two Non-Overlapping Subarrays
 * https://leetcode.com/problems/maximum-sum-of-two-non-overlapping-subarrays/
 * Given an array A of non-negative integers, return the maximum sum of elements in two non-overlapping (contiguous) subarrays,
 * which have lengths L and M.
 * (For clarification, the L-length subarray could occur before or after the M-length subarray.)
Formally, return the largest V for which V = (A[i] + A[i+1] + ... + A[i+L-1]) + (A[j] + A[j+1] + ... + A[j+M-1]) and either:
0 <= i < i + L - 1 < j < j + M - 1 < A.length,
or
0 <= j < j + M - 1 < i < i + L - 1 < A.length.

Example 1:
Input: A = [0,6,5,2,2,5,1,9,4], L = 1, M = 2
Output: 20
Explanation: One choice of subarrays is [9] with length 1, and [6,5] with length 2.

Example 2:
Input: A = [3,8,1,3,2,1,8,9,0], L = 3, M = 2
Output: 29
Explanation: One choice of subarrays is [3,8,1] with length 3, and [8,9] with length 2.

Example 3:
Input: A = [2,1,5,6,0,9,5,0,3,8], L = 4, M = 3
Output: 31
Explanation: One choice of subarrays is [5,6,0,9] with length 4, and [3,8] with length 3.

Note:
1. L >= 1
2. M >= 1
3. L + M <= A.length <= 1000
5. 0 <= A[i] <= 1000
 * */
class Solution {
    /*
    * solution: prefix sum, keep tracking left range and right range for L,M and M,L,
    * Time:O(n), Space:O(n)
    * */
    fun maxSumTwoNoOverlap(A: IntArray, L: Int, M: Int): Int {
        if (A.isEmpty()) {
            return 0
        }
        val n = A.size
        val prefixSumArray = IntArray(n)
        prefixSumArray[0] = A[0]
        for (i in 1 until n) {
            prefixSumArray[i] += prefixSumArray[i - 1] + A[i]
        }
        //the L-length sub-array could occur before or after the M-length sub-array
        val maxLM = getMaxValue(prefixSumArray, L, M)
        val maxML = getMaxValue(prefixSumArray, M, L)
        return Math.max(maxLM, maxML)
    }

    private fun getMaxValue(nums: IntArray, leftSize: Int, rightSize: Int): Int {
        val totalSize = leftSize + rightSize
        var maxLeft = 0
        var rightValue = 0
        var maxValue = 0
        /*
        * calculate sum by L,M, for example: [3,8,1,3,2,1,8,9,0], L = 3, M = 2,
        * size of array is 9, handle get sum from L before M processing:
        * left range: 0-2, right range:3-4,
        * left range: 1-3, right range:4-5,
        * left range: 2-4, right range:5-6,
        * left range: 3-5, right range:6-7,
        * left range: 4-6, right range:7-8,
        * */
        for (i in totalSize - 1 until nums.size) {
            //keep tracking left max value
            maxLeft = Math.max(maxLeft, getRangeSum(nums, i - (totalSize - 1), i - rightSize))
            /*
           current right sum, no need to keeping the maximum right, because here is scan left to right,
           would renew the rightValue, for example:[2,1,5,6,0,9,5,0,3,8], L = 4, M = 3,
           will occur: [6,0,9,5], [0,3,8], [0,9,5], then [0,3,8] should be the right answer
           */
            rightValue = getRangeSum(nums, i - (rightSize - 1), i)
            maxValue = Math.max(maxValue, maxLeft + rightValue)
        }
        return maxValue
    }

    private fun getRangeSum(prefixSumArray: IntArray, start: Int, end: Int): Int {
        if (start == 0) {
            return prefixSumArray[end]
        }
        return prefixSumArray[end] - prefixSumArray[start - 1]
    }
}
原文地址:https://www.cnblogs.com/johnnyzhao/p/14284563.html