Description
Given an n x n binary matrix image, flip the image horizontally, then invert it, and return the resulting image.
To flip an image horizontally means that each row of the image is reversed.
- For example, flipping
[1,1,0]horizontally results in[0,1,1].
To invert an image means that each 0 is replaced by 1, and each 1 is replaced by 0.
- For example, inverting
[0,1,1]results in[1,0,0].
Example 1:
Input: image = [[1,1,0],[1,0,1],[0,0,0]] Output: [[1,0,0],[0,1,0],[1,1,1]] Explanation: First reverse each row: [[0,1,1],[1,0,1],[0,0,0]]. Then, invert the image: [[1,0,0],[0,1,0],[1,1,1]]
Example 2:
Input: image = [[1,1,0,0],[1,0,0,1],[0,1,1,1],[1,0,1,0]] Output: [[1,1,0,0],[0,1,1,0],[0,0,0,1],[1,0,1,0]] Explanation: First reverse each row: [[0,0,1,1],[1,0,0,1],[1,1,1,0],[0,1,0,1]]. Then invert the image: [[1,1,0,0],[0,1,1,0],[0,0,0,1],[1,0,1,0]]
Constraints:
n == image.lengthn == image[i].length1 <= n <= 20images[i][j]is either0or1.
Solutions
Solution 1: Two Pointers
We can traverse the matrix, and for each row row, we use two pointers i and j pointing to the first and last elements of the row, respectively. If row[i] = row[j], swapping them will keep their values unchanged, so we only need to XOR invert row[i] and row[j], then move i and j one position towards the center until i ≥ j. If row[i] ≠ row[j], swapping and then inverting their values will also keep them unchanged, so no operation is needed.
Finally, if i = j, we directly invert row[i].
The time complexity is O(n^2), where n is the number of rows or columns in the matrix. The space complexity is O(1).
class Solution: def flipAndInvertImage(self, image: List[List[int]]) -> List[List[int]]: n = len(image) for row in image: i, j = 0, n - 1 while i < j: if row[i] == row[j]: row[i] ^= 1 row[j] ^= 1 i, j = i + 1, j - 1 if i == j: row[i] ^= 1 return image(code-box)
