Minimum Operations to Make Binary Array Elements Equal to One II
Problem Statement​
You are given a binary array nums.
You can perform the following operation any number of times: choose two indices L and R such that 0 <= L, R < nums.length and flip every 0 to 1 and every 1 to 0 in the subarray nums[L...R] (inclusive).
Return the minimum number of operations needed to make nums contain only 1s.
Example 1:
Input: nums = [1,1,0,1]
Output: 1
Explanation: Flip the element at index 2 (0-indexed) to get [1,1,1,1].
Example 2:
Input: nums = [0,1,1,0]
Output: 2
Explanation: Flip the elements at index 0 and 3 (0-indexed) to get [1,1,1,1].
Constraints:
1 <= nums.length <= 10^5nums[i]is either0or1.
Solutions​
Approach​
The goal is to minimize the number of operations required to convert all elements of the array nums to 1. The operations allowed involve flipping subarrays of nums.
Intuition​
To achieve this efficiently:
-
Prefix Sum Calculation: Compute the prefix sums of
numssuch thatprefix[i]represents the number of0s innums[0...i-1]. -
Two Pointers Technique: Use two pointers (
leftandright) to determine the range[L, R]where flipping would be most effective. This involves:- Calculating the total number of
0s innumsinitially. - Iteratively adjusting the range
[L, R]to minimize the number of0s.
- Calculating the total number of
Steps​
-
Initialization: Initialize
leftandrightpointers at the start of the array. Compute the initial count of0s innums. -
Iterative Adjustment: Iterate through possible ranges
[L, R]:- Update the count of
0s by includingnums[right]and excludingnums[left]. - Update the minimum operations required based on the count of
0s.
- Update the count of
-
Edge Cases: Handle arrays where all elements are initially
1.
Complexity​
- Time Complexity:
O(n)wherenis the length ofnums. This is because we iterate through the array with two pointers. - Space Complexity:
O(1)extra space for variables.
Implementation (Java)​
class Solution {
public int minOperations(int[] nums) {
int n = nums.length;
int left = 0, right = 0;
int countZeros = 0;
int minOps = Integer.MAX_VALUE;
for (int num : nums) {
if (num == 0) {
countZeros++;
}
}
int currentOps = countZeros;
while (right < n) {
if (nums[right] == 0) {
countZeros--;
}
right++;
while (countZeros * 2 <= right - left) {
if (nums[left] == 0) {
countZeros++;
}
left++;
}
minOps = Math.min(minOps, currentOps);
}
return minOps == Integer.MAX_VALUE ? 0 : minOps;
}
}
Implementation (Python)​
class Solution:
def minOperations(self, nums):
n = len(nums)
left = 0
right = 0
countZeros = sum(1 for num in nums if num == 0)
minOps = float('inf')
currentOps = countZeros
while right < n:
if nums[right] == 0:
countZeros -= 1
right += 1
while countZeros * 2 <= right - left:
if nums[left] == 0:
countZeros += 1
left += 1
minOps = min(minOps, currentOps)
return minOps if minOps != float('inf') else 0
Conclusion​
This implementation efficiently calculates the minimum operations required to convert the binary array nums into an array containing only 1s using a two-pointer technique. Adjustments can be made according to specific platform requirements or further customization needs.