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2460. Apply Operations to an Array
Description
You are given a 0-indexed array nums
of size n
consisting of non-negative integers.
You need to apply n - 1
operations to this array where, in the ith
operation (0-indexed), you will apply the following on the ith
element of nums
:
- If
nums[i] == nums[i + 1]
, then multiplynums[i]
by2
and setnums[i + 1]
to0
. Otherwise, you skip this operation.
After performing all the operations, shift all the 0
's to the end of the array.
- For example, the array
[1,0,2,0,0,1]
after shifting all its0
's to the end, is[1,2,1,0,0,0]
.
Return the resulting array.
Note that the operations are applied sequentially, not all at once.
Example 1:
Input: nums = [1,2,2,1,1,0] Output: [1,4,2,0,0,0] Explanation: We do the following operations: - i = 0: nums[0] and nums[1] are not equal, so we skip this operation. - i = 1: nums[1] and nums[2] are equal, we multiply nums[1] by 2 and change nums[2] to 0. The array becomes [1,4,0,1,1,0]. - i = 2: nums[2] and nums[3] are not equal, so we skip this operation. - i = 3: nums[3] and nums[4] are equal, we multiply nums[3] by 2 and change nums[4] to 0. The array becomes [1,4,0,2,0,0]. - i = 4: nums[4] and nums[5] are equal, we multiply nums[4] by 2 and change nums[5] to 0. The array becomes [1,4,0,2,0,0]. After that, we shift the 0's to the end, which gives the array [1,4,2,0,0,0].
Example 2:
Input: nums = [0,1] Output: [1,0] Explanation: No operation can be applied, we just shift the 0 to the end.
Constraints:
2 <= nums.length <= 2000
0 <= nums[i] <= 1000
Solutions
Solution 1: Simulation
We can directly simulate according to the problem description.
First, we traverse the array $nums$. For any two adjacent elements $nums[i]$ and $nums[i+1]$, if $nums[i] = nums[i+1]$, then we double the value of $nums[i]$ and change the value of $nums[i+1]$ to $0$.
Then, we create an answer array $ans$ of length $n$, and put all non-zero elements of $nums$ into $ans$ in order.
Finally, we return the answer array $ans$.
The time complexity is $O(n)$, where $n$ is the length of the array $nums$. Ignoring the space consumption of the answer, the space complexity is $O(1)$.
-
class Solution { public int[] applyOperations(int[] nums) { int n = nums.length; for (int i = 0; i < n - 1; ++i) { if (nums[i] == nums[i + 1]) { nums[i] <<= 1; nums[i + 1] = 0; } } int[] ans = new int[n]; int i = 0; for (int x : nums) { if (x > 0) { ans[i++] = x; } } return ans; } }
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class Solution { public: vector<int> applyOperations(vector<int>& nums) { int n = nums.size(); for (int i = 0; i < n - 1; ++i) { if (nums[i] == nums[i + 1]) { nums[i] <<= 1; nums[i + 1] = 0; } } vector<int> ans(n); int i = 0; for (int& x : nums) { if (x) { ans[i++] = x; } } return ans; } };
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class Solution: def applyOperations(self, nums: List[int]) -> List[int]: n = len(nums) for i in range(n - 1): if nums[i] == nums[i + 1]: nums[i] <<= 1 nums[i + 1] = 0 ans = [0] * n i = 0 for x in nums: if x: ans[i] = x i += 1 return ans
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func applyOperations(nums []int) []int { n := len(nums) for i := 0; i < n-1; i++ { if nums[i] == nums[i+1] { nums[i] <<= 1 nums[i+1] = 0 } } ans := make([]int, n) i := 0 for _, x := range nums { if x > 0 { ans[i] = x i++ } } return ans }
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function applyOperations(nums: number[]): number[] { const n = nums.length; for (let i = 0; i < n - 1; ++i) { if (nums[i] === nums[i + 1]) { nums[i] <<= 1; nums[i + 1] = 0; } } const ans: number[] = Array(n).fill(0); let i = 0; for (const x of nums) { if (x !== 0) { ans[i++] = x; } } return ans; }
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impl Solution { pub fn apply_operations(nums: Vec<i32>) -> Vec<i32> { let mut nums = nums; for i in 0..nums.len() - 1 { if nums[i] == nums[i + 1] { nums[i] <<= 1; nums[i + 1] = 0; } } let mut cur = 0; for i in 0..nums.len() { if nums[i] != 0 { nums.swap(i, cur); cur += 1; } } nums } }