2340. Minimum Adjacent Swaps to Make a Valid Array π ο
Descriptionο
You are given a 0-indexed integer array nums
.
Swaps of adjacent elements are able to be performed on nums
.
A valid array meets the following conditions:
- The largest element (any of the largest elements if there are multiple) is at the rightmost position in the array.
- The smallest element (any of the smallest elements if there are multiple) is at the leftmost position in the array.
Return the minimum swaps required to make nums
a valid array.
Example 1:
Input: nums = [3,4,5,5,3,1] Output: 6 Explanation: Perform the following swaps: - Swap 1: Swap the 3rd and 4th elements, nums is then [3,4,5,3,5,1]. - Swap 2: Swap the 4th and 5th elements, nums is then [3,4,5,3,1,5]. - Swap 3: Swap the 3rd and 4th elements, nums is then [3,4,5,1,3,5]. - Swap 4: Swap the 2nd and 3rd elements, nums is then [3,4,1,5,3,5]. - Swap 5: Swap the 1st and 2nd elements, nums is then [3,1,4,5,3,5]. - Swap 6: Swap the 0th and 1st elements, nums is then [1,3,4,5,3,5]. It can be shown that 6 swaps is the minimum swaps required to make a valid array.
Example 2:
Input: nums = [9] Output: 0 Explanation: The array is already valid, so we return 0.
Constraints:
1 <= nums.length <= 105
1 <= nums[i] <= 105
Solutionsο
Solution 1: Maintain Index of Extremes + Case Analysisο
We can use indices $i$ and $j$ to record the index of the first minimum value and the last maximum value in the array $\textit{nums}$, respectively. Traverse the array $\textit{nums}$ to update the values of $i$ and $j$.
Next, we need to consider the number of swaps.
If $i = j$, it means the array $\textit{nums}$ is already a valid array, and no swaps are needed. Return $0$.
If $i < j$, it means the minimum value in the array $\textit{nums}$ is to the left of the maximum value. The number of swaps needed is $i + n - 1 - j$, where $n$ is the length of the array $\textit{nums}$.
If $i > j$, it means the minimum value in the array $\textit{nums}$ is to the right of the maximum value. The number of swaps needed is $i + n - 1 - j - 1$.
The time complexity is $O(n)$, where $n$ is the length of the array $\textit{nums}$. The space complexity is $O(1)$.
Python3ο
class Solution:
def minimumSwaps(self, nums: List[int]) -> int:
i = j = 0
for k, v in enumerate(nums):
if v < nums[i] or (v == nums[i] and k < i):
i = k
if v >= nums[j] or (v == nums[j] and k > j):
j = k
return 0 if i == j else i + len(nums) - 1 - j - (i > j)
Javaο
class Solution {
public int minimumSwaps(int[] nums) {
int n = nums.length;
int i = 0, j = 0;
for (int k = 0; k < n; ++k) {
if (nums[k] < nums[i] || (nums[k] == nums[i] && k < i)) {
i = k;
}
if (nums[k] > nums[j] || (nums[k] == nums[j] && k > j)) {
j = k;
}
}
if (i == j) {
return 0;
}
return i + n - 1 - j - (i > j ? 1 : 0);
}
}
C++ο
class Solution {
public:
int minimumSwaps(vector<int>& nums) {
int n = nums.size();
int i = 0, j = 0;
for (int k = 0; k < n; ++k) {
if (nums[k] < nums[i] || (nums[k] == nums[i] && k < i)) {
i = k;
}
if (nums[k] > nums[j] || (nums[k] == nums[j] && k > j)) {
j = k;
}
}
if (i == j) {
return 0;
}
return i + n - 1 - j - (i > j);
}
};
Goο
func minimumSwaps(nums []int) int {
var i, j int
for k, v := range nums {
if v < nums[i] || (v == nums[i] && k < i) {
i = k
}
if v > nums[j] || (v == nums[j] && k > j) {
j = k
}
}
if i == j {
return 0
}
if i < j {
return i + len(nums) - 1 - j
}
return i + len(nums) - 2 - j
}
TypeScriptο
function minimumSwaps(nums: number[]): number {
let i = 0;
let j = 0;
const n = nums.length;
for (let k = 0; k < n; ++k) {
if (nums[k] < nums[i] || (nums[k] == nums[i] && k < i)) {
i = k;
}
if (nums[k] > nums[j] || (nums[k] == nums[j] && k > j)) {
j = k;
}
}
return i == j ? 0 : i + n - 1 - j - (i > j ? 1 : 0);
}