Maximize Sum of Array After K Negations in Python

Suppose we have an array A of integers, we have to modify the array in the following way −

We can choose an i and replace the A[i] with -A[i], and we will repeat this process K times. We have to return the largest possible sum of the array after changing it in this way.

So, if the array A = [4,2,3], and K = 1, then the output will be 5. So choose indices 1, the array will become [4,-2,3]

To solve this, we will follow these steps −

• Sort the array A

• for i in range 0 to length of A – 1

  • if A[i] <0, then A[i] := - A[i], and decrease k by 1

  • if k = 0, then break from the loop

• if k is even, then

  • sp := A[0]

  • for i := 1 to length of A – 1

    • if A[i] > 0, then sp := minimum of sp and A[i]

  • return sum of the elements of A – (2*sp)

• otherwise, return the sum of the elements of A

Example (Python)

Let us see the following implementation to get a better understanding −

 Live Demo

class Solution(object):
   def largestSumAfterKNegations(self, A, K):
      A.sort()
      for i in range(len(A)):
         if A[i] <0:
            A[i] = -A[i]
            K-=1
         if K==0:
            break
      if K%2:
         smallest_positive = A[0]
         for i in range(1,len(A)):
            if A[i]>=0:
               smallest_positive = min(smallest_positive,A[i]) return sum(A) - (2*smallest_positive)
            else:
               return sum(A)
ob1 = Solution()
print(ob1.largestSumAfterKNegations([3,-1,0,2],3))

Input

[3,-1,0,2]
3

Output

6