牛客NC166 连续子数组的最大和(二)【中等前缀和数组+动态规划 Java/Go/PHP/C++】

题目

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题目链接：
https://www.nowcoder.com/practice/11662ff51a714bbd8de809a89c481e21

思路

前缀和数组+动态规划

Java代码

import java.util.*;public class Solution {/*** 代码中的类名、方法名、参数名已经指定，请勿修改，直接返回方法规定的值即可*** @param array int整型一维数组* @return int整型一维数组*/public int[] FindGreatestSumOfSubArray (int[] array) {//前缀和+动态规划int n = array.length;if (n <= 1) return array;int[] presum = new int[n + 1]; //前缀和for (int i = 0; i < n; i++) {presum[i + 1] = presum[i] + array[i];}int[] dp = new int[n];dp[0] = array[0];int pre = array[0];int maxSum = array[0];int maxSumEnd = 0;//存放最的子数组和的子数组下标列表List<Integer> maxsumll = new ArrayList<>();for (int i = 1; i < n ; i++) {int p1 = array[i];int p2 = array[i] + pre;int cur = Math.max(p1, p2);//maxSum=Math.max(maxSum,cur);if (maxSum <= cur) {if (maxSum < cur) {maxsumll.clear();}maxsumll.add(i);maxSum = cur;maxSumEnd = i;}pre = cur;}//System.out.println(maxSum+", "+maxSumEnd);//System.out.println(sumIdx);int maxSize = 0;int maxSizeIdx = 0;for (Integer idx : maxsumll) {//for (int i = idx; i <=idx ; i++) {for (int j = 0; j <= idx ; j++) {if (presum[idx + 1] - presum[j] == maxSum) {//size=Math.max(size,idx+1-j);if (maxSize < idx + 1 - j) {maxSize = idx + 1 - j;maxSizeIdx = idx;}break;}//  }}}// System.out.println("size:"+ maxSize+" maxSizeidx:"+ maxSizeIdx);int[] ans = new int[maxSize];for (int i = 0; i < maxSize ; i++) {ans[i] = array[maxSizeIdx - maxSize + 1 + i];}return ans;}
}

Go代码

package main/*** 代码中的类名、方法名、参数名已经指定，请勿修改，直接返回方法规定的值即可*** @param array int整型一维数组* @return int整型一维数组*/
func FindGreatestSumOfSubArray(array []int) []int {//前缀和+动态规划n := len(array)if n <= 1 {return array}presum := make([]int, n+1)for i := 0; i < n; i++ {presum[i+1] = presum[i] + array[i]}pre := array[0]maxSum := array[0]maxSumll := []int{} //存放最的子数组和的子数组下标列表for i := 1; i < n; i++ {p1 := array[i]p2 := array[i] + precur := p1if cur < p2 {cur = p2}if maxSum <= cur {if maxSum < cur {maxSumll = []int{}}maxSum = curmaxSumll = append(maxSumll, i)}pre = cur}maxSize := 0maxSizeIdx := 0for _, idx := range maxSumll {for j := 0; j <= idx; j++ {if presum[idx+1]-presum[j] == maxSum {if maxSize < idx+1-j {maxSize = idx + 1 - jmaxSizeIdx = idx}break}}}ans := make([]int, maxSize)for i := 0; i < maxSize; i++ {ans[i] = array[maxSizeIdx+1-maxSize+i]}return ans
}

PHP代码

<?php/*** 代码中的类名、方法名、参数名已经指定，请勿修改，直接返回方法规定的值即可** * @param array int整型一维数组 * @return int整型一维数组*/
function FindGreatestSumOfSubArray( $array )
{//前缀和+动态规划$n= count($array);if($n <=1){return $array;}$presum = [0=>0];for($i=0;$i<$n;$i++){$presum[$i+1] = $presum[$i]+$array[$i];}$pre = $array[0];$max = $array[0];$list = array(); //存放$max对应的子数组的结束下标for($i=1;$i<$n;$i++){$cur = $array[$i];$p2 = $array[$i]+$pre;if($cur < $p2){$cur = $p2;}if($max<=$cur){if($max<$cur) {$list = array();}$list[count($list)] = $i;$max = $cur;}$pre=$cur;}$maxLen =0;$maxLenIdx =0;foreach ($list as $idx){for($j=0;$j<=$idx;$j++){if($presum[$idx+1] -$presum[$j] ==$max){if($maxLen < $idx+1-$j){$maxLen = $idx+1-$j;$maxLenIdx = $idx;}break;}}}$ans=[];for($i=0;$i<$maxLen;$i++){$ans[$i] = $array[$maxLenIdx-$maxLen+1+$i];}return $ans;
}

C++代码

class Solution {public:/*** 代码中的类名、方法名、参数名已经指定，请勿修改，直接返回方法规定的值即可*** @param array int整型vector* @return int整型vector*/vector<int> FindGreatestSumOfSubArray(vector<int>& array) {//前缀和+动态规划int n = array.size();if (n <= 1)return array;//前缀和vector<int> presum(n + 1, 0);for (int i = 0; i < n; i++) {presum[i + 1] = presum[i] + array[i];}int pre = array[0];int max = array[0]; //最大的子数组和vector<int> list; //存放max对应的子数组的下标列表for (int i = 1; i < n; i++) {int p1 = array[i];int p2 = array[i] + pre;int cur = p1;if (cur < p2) {cur = p2;}if (max <= cur) {if (max < cur) {list.clear();}max = cur;list.push_back(i);}pre = cur;}int maxLen = 0;int maxLenIdx = 0;for (int i = 0; i < list.size(); i++) {int idx = list[i];for (int j = 0; j <= idx; j++) {if (presum[idx + 1] - presum[j] == max) {if (maxLen < idx + 1 - j) {maxLen = idx + 1 - j;maxLenIdx = idx;}break;}}}vector<int> ans(maxLen);for (int i = 0; i < maxLen; i++) {ans[i] = array[maxLenIdx - maxLen + 1 + i];}return ans;}
};