Leetcode #2918: Minimum Equal Sum of Two Arrays After Replacing Zeros
In this guide, we solve Leetcode #2918 Minimum Equal Sum of Two Arrays After Replacing Zeros in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
You are given two arrays nums1 and nums2 consisting of positive integers. You have to replace all the 0's in both arrays with strictly positive integers such that the sum of elements of both arrays becomes equal.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Greedy, Array
Intuition
A locally optimal choice leads to a globally optimal result for this structure.
That means we can commit to decisions as we scan without backtracking.
Approach
Sort or preprocess if needed, then repeatedly take the best available local choice.
Maintain the minimal state necessary to validate the greedy decision.
Steps:
- Sort or preprocess as needed.
- Iterate and pick the best local option.
- Track the current solution.
Example
Input: nums1 = [3,2,0,1,0], nums2 = [6,5,0]
Output: 12
Explanation: We can replace 0's in the following way:
- Replace the two 0's in nums1 with the values 2 and 4. The resulting array is nums1 = [3,2,2,1,4].
- Replace the 0 in nums2 with the value 1. The resulting array is nums2 = [6,5,1].
Both arrays have an equal sum of 12. It can be shown that it is the minimum sum we can obtain.
Python Solution
class Solution:
def minSum(self, nums1: List[int], nums2: List[int]) -> int:
s1 = sum(nums1) + nums1.count(0)
s2 = sum(nums2) + nums2.count(0)
if s1 > s2:
return self.minSum(nums2, nums1)
if s1 == s2:
return s1
return -1 if nums1.count(0) == 0 else s2
Complexity
The time complexity is , where and are the lengths of the arrays and , respectively. The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.