Description
Given a 2D grid of size m x n and an integer k. You need to shift the grid k times.
In one shift operation:
Element at grid[i][j] moves to grid[i][j + 1].
Element at grid[i][n - 1] moves to grid[i + 1][0].
Element at grid[m - 1][n - 1] moves to grid[0][0].
Return the 2D grid after applying shift operation k times.
Example 1:
1 | Input: grid = [[1,2,3],[4,5,6],[7,8,9]], k = 1 |
Example 2:
1 | Input: grid = [[3,8,1,9],[19,7,2,5],[4,6,11,10],[12,0,21,13]], k = 4 |
Example 3:
1 | Input: grid = [[1,2,3],[4,5,6],[7,8,9]], k = 9 |
Constraints:
m == grid.length
n == grid[i].length
1 <= m <= 50
1 <= n <= 50
-1000 <= grid[i][j] <= 1000
0 <= k <= 100
Solutions
- Flatten to a one-dimensional list with k step: vector
- Convert to two-dimensional according to the number of rows and columns: metrix
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21# O(nm) time | O(nm) space
class Solution:
def shiftGrid(self, grid: List[List[int]], k: int) -> List[List[int]]:
m, n = len(grid), len(grid[0])
vector = [0] * m*n
cur_idx = 0
for r in range(m):
for c in range(n):
idx = (cur_idx+k)% (m*n)
vector[idx] = grid[r][c]
cur_idx+=1
idx = 0
ans = []
for r in range(m):
level = []
for c in range(n):
level.append(vector[idx])
idx+=1
ans.append(level)
return ans
Optimize space complexity
1 | # O(nm) time | O(1) space |