好比對於數組[1,-2,3,5,-1,2] 最大子數組和是sum[3,5,-1,2] = 9, 咱們要求函數輸出子數組和的最大值,而且返回子數組的左右邊界(下面函數的left和right參數).php
本文咱們規定當數組中全部數都小於0時,返回數組中最大的數(也能夠規定返回0,只要讓如下代碼中maxsum初始化爲0便可,此時咱們要注意-1 0 0 0 -2這種情形,特別是若是要求輸出子數組的起始位置時,若是是面試就要和麪試官問清楚)html
如下代碼咱們在PAT 1007. Maximum Subsequence Sum測試經過,測試main函數以下面試
int main() { int n; scanf("%d", &n); vector<int>vec(n); for(int i = 0; i < n; i++) scanf("%d", &vec[i]); int left, right; int maxsum = maxSum1(vec, left, right);//測試時替換函數名稱 if(maxsum >= 0) printf("%d %d %d", maxsum, vec[left], vec[right]); else printf("0 %d %d", vec[0], vec[n-1]); }
參考:編程之美2.14 求數組的子數組之和的最大值算法
算法1:最簡單的就是窮舉全部的子數組,而後求和,複雜度是O(n^3)編程
int maxSum1(vector<int>&vec, int &left, int &right) { int maxsum = INT_MIN, sum = 0; for(int i = 0; i < vec.size(); i++) for(int k = i; k < vec.size(); k++) { sum = 0; for(int j = i; j <= k; j++) sum += vec[j]; if(sum > maxsum) { maxsum = sum; left = i; right = k; } } return maxsum; }
算法2: 上面代碼第三重循環作了不少的重複工做,稍稍改進以下,複雜度爲O(n^2)數組
int maxSum2(vector<int>&vec, int &left, int &right) { int maxsum = INT_MIN, sum = 0; for(int i = 0; i < vec.size(); i++) { sum = 0; for(int k = i; k < vec.size(); k++) { sum += vec[k]; if(sum > maxsum) { maxsum = sum; left = i; right = k; } } } return maxsum; }
算法3: 分治法, 下面貼上編程之美的解釋, 複雜度爲O(nlogn)函數
//求數組vec【start,end】的最大子數組和,最大子數組邊界爲[left,right] int maxSum3(vector<int>&vec, const int start, const int end, int &left, int &right) { if(start == end) { left = start; right = left; return vec[start]; } int middle = start + ((end - start)>>1); int lleft, lright, rleft, rright; int maxLeft = maxSum3(vec, start, middle, lleft, lright);//左半部分最大和 int maxRight = maxSum3(vec, middle+1, end, rleft, rright);//右半部分最大和 int maxLeftBoeder = vec[middle], maxRightBorder = vec[middle+1], mleft = middle, mright = middle+1; int tmp = vec[middle]; for(int i = middle-1; i >= start; i--) { tmp += vec[i]; if(tmp > maxLeftBoeder) { maxLeftBoeder = tmp; mleft = i; } } tmp = vec[middle+1]; for(int i = middle+2; i <= end; i++) { tmp += vec[i]; if(tmp > maxRightBorder) { maxRightBorder = tmp; mright = i; } } int res = max(max(maxLeft, maxRight), maxLeftBoeder+maxRightBorder); if(res == maxLeft) { left = lleft; right = lright; } else if(res == maxLeftBoeder+maxRightBorder) { left = mleft; right = mright; } else { left = rleft; right = rright; } return res; }
算法4: 動態規劃, 數組爲vec[],設dp[i] 是以vec[i]結尾的子數組的最大和,對於元素vec[i+1], 它有兩種選擇:a、vec[i+1]接着前面的子數組構成最大和,b、vec[i+1]本身單獨構成子數組。則dp[i+1] = max{dp[i]+vec[i+1], vec[i+1]}測試
若是不考慮記錄最大子數組的位置,因而有如下代碼: 本文地址3d
int maxSum_(vector<int>&vec) { int maxsum = INT_MIN, sum = 0; for(int i = 0; i < vec.size(); i++) { sum = max(sum + vec[i], vec[i]); maxsum = max(maxsum, sum); } return maxsum; }
對以上代碼換個寫法,並記錄最大子數組的位置htm
int maxSum4(vector<int>&vec, int &left, int&right) { int maxsum = INT_MIN, sum = 0; int begin = 0; for(int i = 0; i < vec.size(); i++) { if(sum >= 0) { sum += vec[i]; } else { sum = vec[i]; begin = i; } if(maxsum < sum) { maxsum = sum; left = begin; right = i; } } return maxsum; }
若是數組是循環的,該如何呢
這時分兩種情形(圖中紅色方框表示求得的最大子數組,left、right分別是子數組的開始和結尾):
(1)以下圖最大的子數組沒有跨過vec[n-1]到vec[0], 這就是每循環的狀況
(2)以下圖,最大的子數組跨過vec[n-1]到vec[0]
對於第二種情形,至關於從原數組中挖掉了一塊(vec[right+1], …, vec[left-1]) ,那麼咱們只要使挖掉的和最小便可,求最小子數組和最大子數組相似,代碼以下,如下代碼在九度oj1572首尾相連數組的最大子數組和經過測試(測試須要,如下代碼當數組全是負數時,輸出0):
int maxSumCycle(vector<int>&vec, int &left, int&right) { int maxsum = INT_MIN, curMaxSum = 0; int minsum = INT_MAX, curMinSum = 0; int sum = 0; int begin_max = 0, begin_min = 0; int minLeft, minRight; for(int i = 0; i < vec.size(); i++) { sum += vec[i]; if(curMaxSum >= 0) { curMaxSum += vec[i]; } else { curMaxSum = vec[i]; begin_max = i; } if(maxsum < curMaxSum) { maxsum = curMaxSum; left = begin_max; right = i; } ///////////////求和最小的子數組 if(curMinSum <= 0) { curMinSum += vec[i]; } else { curMinSum = vec[i]; begin_min = i; } if(minsum > curMinSum) { minsum = curMinSum; minLeft = begin_min; minRight = i; } } if(maxsum >= sum - minsum) return maxsum; else { left = minRight+1; right = minLeft-1; return sum - minsum; } }
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