通过删除子数组

时间:2018-12-23 01:52:47

标签: c arrays optimization big-o sub-array

C程序,查找要删除的子数组的起始索引和结尾索引,以使给定数组的左侧和右侧的总和相等。如果无法打印-1。我需要它可用于任何阵列,这仅用于测试。这是找到平衡的代码。

#include <stdio.h> 

int equilibrium(int arr[], int n) 
{ 
int i, j; 
int leftsum, rightsum; 

/* Check for indexes one by one until 
an equilibrium index is found */
for (i = 0; i < n; ++i) {    

    /* get left sum */
    leftsum = 0; 
    for (j = 0; j < i; j++) 
        leftsum += arr[j]; 

    /* get right sum */
    rightsum = 0; 
    for (j = i + 1; j < n; j++) 
        rightsum += arr[j]; 

    /* if leftsum and rightsum are same, 
    then we are done */
    if (leftsum == rightsum) 
        return i; 
} 

/* return -1 if no equilibrium index is found */
return -1; 
} 

// Driver code 
int main() 
{ 
int arr[] = { -7, 1, 5, 2, -4, 3, 0 }; 
int arr_size = sizeof(arr) / sizeof(arr[0]); 
printf("%d", equilibrium(arr, arr_size)); 

getchar(); 
return 0; 
}

1 个答案:

答案 0 :(得分:1)

您可以在O(NlogN)O(N)(通常情况下)中解决此问题。

首先,您需要进行预处理,将所有总和从右到左保存在数据结构中,尤其是平衡的二进制搜索树(例如Red Black tree,AVL树,Splay树等,如果您可以使用stdlib,只需使用std::multiset)或HashTable(在stdlib中是std::unordered_multiset):

void preProcessing(dataStructure & ds, int * arr, int n){
    int sum = 0;
    int * toDelete = (int) malloc(n)
    for(int i = n-1; i >= 0; --i){
        sum += arr[i];
        toDelete[i] = sum; // Save items to delete later.
        tree.insert(sum);
    }

因此,要解决问题,您只需遍历数组一次:

// It considers that the deleted subarray could be empty
bool Solve(dataStructure & ds, int * arr, int n, int * toDelete){
    int sum = 0;
    bool solved = false; // true if a solution is found
    for(int i = 0 ; i < n; ++i){ 
        ds.erase(toDelete[i]); // deletes the actual sum up to i-th element from data structure, as it couldn't be part of the solution.
                               // It costs O(logN)(BBST) or O(1)(Hashtable)
        sum += arr[i];
        if(ds.find(sum)){// If sum is in ds, then there's a leftsum == rightsum
                         // It costs O(logN)(BBST) or O(1)(HashTable)
            solved = true;
            break;
        }
    }
    return solved;
}

然后,如果您使用BBST(平衡二进制搜索树),则您的解决方案将为O(NlogN),但是,如果您使用HashTable,则您的解决方案将平均为O(N)。我不会实现它,所以也许有一个错误,但是我尝试解释主要思想。