2134. Minimum Swaps to Group All 1's Together II

Description

A swap is defined as taking two distinct positions in an array and swapping the values in them.

A circular array is defined as an array where we consider the first element and the last element to be adjacent.

Given a binary circular array nums, return the minimum number of swaps required to group all 1's present in the array together at any location.

 

Example 1:

Input: nums = [0,1,0,1,1,0,0]
Output: 1
Explanation: Here are a few of the ways to group all the 1's together:
[0,0,1,1,1,0,0] using 1 swap.
[0,1,1,1,0,0,0] using 1 swap.
[1,1,0,0,0,0,1] using 2 swaps (using the circular property of the array).
There is no way to group all 1's together with 0 swaps.
Thus, the minimum number of swaps required is 1.

Example 2:

Input: nums = [0,1,1,1,0,0,1,1,0]
Output: 2
Explanation: Here are a few of the ways to group all the 1's together:
[1,1,1,0,0,0,0,1,1] using 2 swaps (using the circular property of the array).
[1,1,1,1,1,0,0,0,0] using 2 swaps.
There is no way to group all 1's together with 0 or 1 swaps.
Thus, the minimum number of swaps required is 2.

Example 3:

Input: nums = [1,1,0,0,1]
Output: 0
Explanation: All the 1's are already grouped together due to the circular property of the array.
Thus, the minimum number of swaps required is 0.

 

Constraints:

• 1 <= nums.length <= 105
• nums[i] is either 0 or 1.

Solutions

Solution 1: Sliding Window

First, we count the number of $1$s in the array, denoted as $k$. The problem is actually asking for a circular subarray of length $k$ that contains the maximum number of $1$s. Therefore, the minimum number of swaps is $k$ minus the maximum number of $1$s in that subarray.

We can solve this problem using a sliding window. First, we count the number of $1$s in the first $k$ elements of the array, denoted as $cnt$. Then, we maintain a sliding window of length $k$. Each time we move the window one position to the right, we update $cnt$ and simultaneously update the maximum $cnt$ value, i.e., $mx = \max(mx, cnt)$. Finally, the answer is $k - mx$.

The time complexity is $O(n)$, where $n$ is the length of the array $nums$. The space complexity is $O(1)$.

Python3JavaC++GoTypeScriptRustC#

class Solution:
    def minSwaps(self, nums: List[int]) -> int:
        k = nums.count(1)
        mx = cnt = sum(nums[:k])
        n = len(nums)
        for i in range(k, n + k):
            cnt += nums[i % n]
            cnt -= nums[(i - k + n) % n]
            mx = max(mx, cnt)
        return k - mx

class Solution {
    public int minSwaps(int[] nums) {
        int k = Arrays.stream(nums).sum();
        int n = nums.length;
        int cnt = 0;
        for (int i = 0; i < k; ++i) {
            cnt += nums[i];
        }
        int mx = cnt;
        for (int i = k; i < n + k; ++i) {
            cnt += nums[i % n] - nums[(i - k + n) % n];
            mx = Math.max(mx, cnt);
        }
        return k - mx;
    }
}

class Solution {
public:
    int minSwaps(vector<int>& nums) {
        int k = accumulate(nums.begin(), nums.end(), 0);
        int n = nums.size();
        int cnt = accumulate(nums.begin(), nums.begin() + k, 0);
        int mx = cnt;
        for (int i = k; i < n + k; ++i) {
            cnt += nums[i % n] - nums[(i - k + n) % n];
            mx = max(mx, cnt);
        }
        return k - mx;
    }
};

func minSwaps(nums []int) int {
    k := 0
    for _, x := range nums {
        k += x
    }
    cnt := 0
    for i := 0; i < k; i++ {
        cnt += nums[i]
    }
    mx := cnt
    n := len(nums)
    for i := k; i < n+k; i++ {
        cnt += nums[i%n] - nums[(i-k+n)%n]
        mx = max(mx, cnt)
    }
    return k - mx
}

function minSwaps(nums: number[]): number {
    const k = nums.reduce((a, b) => a + b, 0);
    let cnt = nums.slice(0, k).reduce((a, b) => a + b, 0);
    let mx = cnt;
    const n = nums.length;
    for (let i = k; i < n + k; ++i) {
        cnt += nums[i % n] - nums[(i - k + n) % n];
        mx = Math.max(mx, cnt);
    }
    return k - mx;
}

impl Solution {
    pub fn min_swaps(nums: Vec<i32>) -> i32 {
        let k: i32 = nums.iter().sum();
        let n: usize = nums.len();
        let mut cnt: i32 = 0;
        for i in 0..k {
            cnt += nums[i as usize];
        }
        let mut mx: i32 = cnt;
        for i in k..(n as i32) + k {
            cnt +=
                nums[(i % (n as i32)) as usize] -
                nums[((i - k + (n as i32)) % (n as i32)) as usize];
            mx = mx.max(cnt);
        }
        return k - mx;
    }
}

public class Solution {
    public int MinSwaps(int[] nums) {
        int k = nums.Sum();
        int n = nums.Length;
        int cnt = 0;
        for (int i = 0; i < k; ++i) {
            cnt += nums[i];
        }
        int mx = cnt;
        for (int i = k; i < n + k; ++i) {
            cnt += nums[i % n] - nums[(i - k + n) % n];
            mx = Math.Max(mx, cnt);
        }
        return k - mx;
    }
}

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