LeetCode 519. Random Flip Matrix 哈希Map

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.

class Solution:

    def __init__(self, m: int, n: int):
        self.row = m
        self.col = n
        self.start = 0
        self.end = m * n
        self.pos_map = {}
        

    def flip(self) -> List[int]:
        idx = random.randrange(self.start, self.end)
        res = self.pos_map.get(idx, idx)
        self.pos_map[idx] = self.pos_map.get(self.start, self.start)
        self.start += 1
        return (res // self.col, res % self.col)


    def reset(self) -> None:
        self.start = 0
        self.pos_map = {}
        


# Your Solution object will be instantiated and called as such:
# obj = Solution(m, n)
# param_1 = obj.flip()
# obj.reset()