Problem

You are given the number of rows n_rows and number of columns n_cols of a 2D binary matrix where all values are initially 0. Write a function flip which chooses a 0 value uniformly at random, changes it to 1, and then returns the position [row.id, col.id] of that value. Also, write a function reset which sets all values back to 0. Try to minimize the number of calls to system’s Math.random() and optimize the time and space complexity.

Note:

1 <= n_rows, n_cols <= 10000
0 <= row.id < n_rows and 0 <= col.id < n_cols
flip will not be called when the matrix has no 0 values left.
the total number of calls to flip and reset will not exceed 1000.

Example 1:

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

Example 2:

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

Explanation of Input Syntax:

The input is two lists: the subroutines called and their arguments. Solution‘s constructor has two arguments, n_rows and n_cols. flip and reset have no arguments. Arguments are always wrapped with a list, even if there aren’t any.

Solution 1: Hashtable + Resample

Time complexity: O(|flip|) = O(1000) = O(1)

Space complexity: O(|flip|) = O(1000) = O(1)

// Author: Huahua

// Running time: 12 ms

class Solution {

public:

Solution(int n_rows, int n_cols):

rows_(n_rows), cols_(n_cols), n_(rows_ * cols_) {}

vector<int> flip() {

int index = rand() % n_;

while (m_.count(index))

index = rand() % n_;

m_.insert(index);

return {index / cols_, index % cols_};

}

void reset() {

m_.clear();

n_ = rows_ * cols_;

}

private:

const int rows_;

const int cols_;

int n_;

unordered_set<int> m_;

};

Solution 2: Fisher–Yates shuffle

Generate a random shuffle of 0 to n – 1, one number at a time.

Time complexity: flip: O(1)

Space complexity: O(|flip|) = O(1000) = O(1)

C++

// Author: Huahua

// Running time: 12 ms

class Solution {

public:

Solution(int n_rows, int n_cols):

rows_(n_rows), cols_(n_cols), n_(rows_ * cols_) {}

vector<int> flip() {

int s = rand() % (n_--);

int index = s;

if (m_.count(s))

index = m_[s];

m_[s] = m_.count(n_) ? m_[n_] : n_;

return {index / cols_, index % cols_};

}

void reset() {

m_.clear();

n_ = rows_ * cols_;

}

private:

const int rows_;

const int cols_;

int n_;

unordered_map<int, int> m_;

};

Problem:

Given an array of integers with possible duplicates, randomly output the index of a given target number. You can assume that the given target number must exist in the array.

Note:
The array size can be very large. Solution that uses too much extra space will not pass the judge.

Example:

int[] nums = new int[] {1,2,3,3,3};

Solution solution = new Solution(nums);

// pick(3) should return either index 2, 3, or 4 randomly. Each index should have equal probability of returning.

solution.pick(3);

// pick(1) should return 0. Since in the array only nums[0] is equal to 1.

solution.pick(1);

Solution: Reservoir sampling

Time complexity: O(query * n)

Space complexity: O(1)

C++

// Author: Huahua

// Running time: 92 ms

class Solution {

public:

Solution(vector<int> nums) {

nums_ = std::move(nums);

}

int pick(int target) {

int n = 0;

int index = -1;

for (int i = 0; i < nums_.size(); ++i) {

if (nums_[i] != target) continue;

++n;

if (rand() % n == 0) index = i;

}

return index;

}

private:

vector<int> nums_;

};

Posts tagged as “sample”

花花酱 LeetCode 881. Random Flip Matrix

Problem

Solution 1: Hashtable + Resample

Solution 2: Fisher–Yates shuffle

花花酱 LeetCode 398. Random Pick Index

Problem:

Example:

Solution: Reservoir sampling