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FleetCode

519. Random Flip Matrix

Medium46.9% acceptance1 company

There is an m x n binary grid matrix with all the values set 0 initially. Design an algorithm to randomly pick an index (i, j) where matrix[i][j] == 0 and flips it to 1. All the indices (i, j) where matrix[i][j] == 0 should be equally likely to be returned.

Optimize your algorithm to minimize the number of calls made to the built-in random function of your language and optimize the time and space complexity.

Implement the Solution class:

  • Solution(int m, int n) Initializes the object with the size of the binary matrix m and n.
  • int[] flip() Returns a random index [i, j] of the matrix where matrix[i][j] == 0 and flips it to 1.
  • void reset() Resets all the values of the matrix to be 0.

Example 1:

Input
["Solution", "flip", "flip", "flip", "reset", "flip"]
[[3, 1], [], [], [], [], []]
Output
[null, [1, 0], [2, 0], [0, 0], null, [2, 0]]

Explanation
Solution solution = new Solution(3, 1);
solution.flip();  // return [1, 0], [0,0], [1,0], and [2,0] should be equally likely to be returned.
solution.flip();  // return [2, 0], Since [1,0] was returned, [2,0] and [0,0]
solution.flip();  // return [0, 0], Based on the previously returned indices, only [0,0] can be returned.
solution.reset(); // All the values are reset to 0 and can be returned.
solution.flip();  // return [2, 0], [0,0], [1,0], and [2,0] should be equally likely to be returned.

Constraints:

  • 1 <= m, n <= 104
  • There will be at least one free cell for each call to flip.
  • At most 1000 calls will be made to flip and reset.

Asked at 1 company

15:16
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Open solution
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1class Solution:
2
3 def __init__(self, m: int, n: int):
4
5
6 def flip(self) -> List[int]:
7
8
9 def reset(self) -> None:
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11
12
13# Your Solution object will be instantiated and called as such:
14# obj = Solution(m, n)
15# param_1 = obj.flip()
16# obj.reset()
Starter codePython 3Spaces: 4
Examples
Input
["Solution","flip","flip","flip","reset","flip"]
[[3,1],[],[],[],[],[]]
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