📜  最大和连续递增子数组

📅  最后修改于: 2022-05-13 01:57:50.636000             🧑  作者: Mango

最大和连续递增子数组

给定一个由 n 个不同正整数组成的数组。问题是在 O(n) 时间复杂度中找到连续递增子数组的最大和。
例子 :

Input : arr[] = {2, 1, 4, 7, 3, 6}
Output : 12
Contiguous Increasing subarray {1, 4, 7} = 12

Input : arr[] = {38, 7, 8, 10, 12}
Output : 38

一个简单的解决方案是生成所有子数组并计算它们的总和。最后返回总和最大的子数组。该解决方案的时间复杂度为 O(n 2 )。
一个有效的解决方案是基于所有元素都是积极的这一事实。所以我们考虑最长递增子数组并比较它们的总和。增加子数组不能重叠,所以我们的时间复杂度变成O(n)。
算法:

Let arr be the array of size n
Let result be the required sum

int largestSum(arr, n) 
    result = INT_MIN  // Initialize result

    i = 0
    while i < n

        // Find sum of longest increasing subarray
        // starting with i
        curr_sum = arr[i];
    while i+1 < n && arr[i] < arr[i+1]
              curr_sum += arr[i+1];
          i++; 

        // If current sum is greater than current
        // result.
        if result < curr_sum
            result = curr_sum; 

        i++;
    return result

下面是上述算法的实现。

C++
// C++ implementation of largest sum
// contiguous increasing subarray
#include 
using namespace std;
 
// Returns sum of longest
// increasing subarray.
int largestSum(int arr[], int n)
{
    // Initialize result
    int result = INT_MIN;
 
    // Note that i is incremented
    // by inner loop also, so overall
    // time complexity is O(n)
    for (int i = 0; i < n; i++)
    {
        // Find sum of longest
        // increasing subarray
        // starting from arr[i]
        int curr_sum = arr[i];
        while (i + 1 < n &&
               arr[i + 1] > arr[i])
        {
            curr_sum += arr[i + 1];
            i++;
        }
 
        // Update result if required
        if (curr_sum > result)
            result = curr_sum;
    }
 
    // required largest sum
    return result;
}
 
// Driver Code
int main()
{
    int arr[] = {1, 1, 4, 7, 3, 6};
    int n = sizeof(arr) / sizeof(arr[0]);
    cout << "Largest sum = "
         << largestSum(arr, n);
    return 0;
}


Java
// Java implementation of largest sum
// contiguous increasing subarray
 
class GFG
{
    // Returns sum of longest
    // increasing subarray.
    static int largestSum(int arr[], int n)
    {
        // Initialize result
        int result = -9999999;
     
        // Note that i is incremented
        // by inner loop also, so overall
        // time complexity is O(n)
        for (int i = 0; i < n; i++)
        {
            // Find sum of longest
            // increasing subarray
            // starting from arr[i]
            int curr_sum = arr[i];
            while (i + 1 < n &&
                   arr[i + 1] > arr[i])
            {
                curr_sum += arr[i + 1];
                i++;
            }
     
            // Update result if required
            if (curr_sum > result)
                result = curr_sum;
        }
     
        // required largest sum
        return result;
    }
     
    // Driver Code
    public static void main (String[] args)
    {
        int arr[] = {1, 1, 4, 7, 3, 6};
        int n = arr.length;
        System.out.println("Largest sum = " +
                         largestSum(arr, n));
    }
}


Python3
# Python3 implementation of largest
# sum contiguous increasing subarray
 
# Returns sum of longest
# increasing subarray.
def largestSum(arr, n):
     
    # Initialize result
    result = -2147483648
 
    # Note that i is incremented
    # by inner loop also, so overall
    # time complexity is O(n)
    for i in range(n):
     
        # Find sum of longest increasing
        # subarray starting from arr[i]
        curr_sum = arr[i]
        while (i + 1 < n and
               arr[i + 1] > arr[i]):
         
            curr_sum += arr[i + 1]
            i += 1
         
        # Update result if required
        if (curr_sum > result):
            result = curr_sum
     
    # required largest sum
    return result
 
# Driver Code
arr = [1, 1, 4, 7, 3, 6]
n = len(arr)
print("Largest sum = ", largestSum(arr, n))
 
# This code is contributed by Anant Agarwal.


C#
// C# implementation of largest sum
// contiguous increasing subarray
using System;
 
class GFG
{
     
    // Returns sum of longest
    // increasing subarray.
    static int largestSum(int []arr,
                          int n)
    {
         
        // Initialize result
        int result = -9999999;
         
        // Note that i is incremented by
        // inner loop also, so overall
        // time complexity is O(n)
        for (int i = 0; i < n; i++)
        {
             
            // Find sum of longest increasing
            // subarray starting from arr[i]
            int curr_sum = arr[i];
            while (i + 1 < n &&
                   arr[i + 1] > arr[i])
            {
                curr_sum += arr[i + 1];
                i++;
            }
     
            // Update result if required
            if (curr_sum > result)
                result = curr_sum;
        }
     
        // required largest sum
        return result;
    }
     
    // Driver code
    public static void Main ()
    {
        int []arr = {1, 1, 4, 7, 3, 6};
        int n = arr.Length;
        Console.Write("Largest sum = " +
                    largestSum(arr, n));
    }
}
 
// This code is contributed
// by Nitin Mittal.


PHP
 $arr[$i])
        {
            $curr_sum += $arr[$i + 1];
            $i++;
        }
 
        // Update result if required
        if ($curr_sum > $result)
            $result = $curr_sum;
    }
 
    // required largest sum
    return $result;
}
 
// Driver Code
{
    $arr = array(1, 1, 4, 7, 3, 6);
    $n = sizeof($arr) / sizeof($arr[0]);
    echo "Largest sum = " ,
          largestSum($arr, $n);
    return 0;
}
 
// This code is contributed by nitin mittal.
?>


Javascript


输出 :

Largest sum = 12