384. Shuffle an Array

Problem Description

Given an integer array nums, design an algorithm to randomly shuffle the array. All permutations of the array should be equally likely as a result of the shuffling.

Implement the Solution class:

• Solution(int[] nums) Initializes the object with the integer array nums.
• int[] reset() Resets the array to its original configuration and returns it.
• int[] shuffle() Returns a random shuffling of the array.

Example 1:

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

Explanation
Solution solution = new Solution([1, 2, 3]);
solution.shuffle();    // Shuffle the array [1,2,3] and return its result.
                       // Any permutation of [1,2,3] must be equally likely to be returned.
                       // Example: return [3, 1, 2]
solution.reset();      // Resets the array back to its original configuration [1,2,3]. Return [1, 2, 3]
solution.shuffle();    // Returns the random shuffling of array [1,2,3]. Example: return [1, 3, 2]

Constraints:

1 <= nums.length <= 200
-106 <= nums[i] <= 106
All the elements of nums are unique.
At most 5 * 104 calls in total will be made to reset and shuffle.

Solution

Hoestly I dont see any points of this question, but here is some resources to check

This leetcode discussion explain the implementation of the Fisher-Yates Algorithm

Java

class Solution {

    private int [] nums;
    private Random random;

    public Solution(int[] nums) {
        this.nums = nums;
        this.random = new Random();
    }

    /** Resets the array to its original configuration and return it. */
    public int[] reset() {
        return nums;
    }

    /** Returns a random shuffling of the array. */
    public int[] shuffle() {
        // keep generating random index, and keep swapping,
        // since random idx->[0,i] so iterate arr from end so that randomindex lies where the index decision has not been taken
        int [] copyarr = nums.clone();
        
        for (int i = nums.length - 1; i > 0; i--) {
            int ridx = random.nextInt(i + 1); // i+1 bcoz indexing is from 1-n and not 0-n-1
            // swap elements at ridx and i
            int temp = copyarr[i];
            copyarr[i] = copyarr[ridx];
            copyarr[ridx] = temp;
        }
        return copyarr;
    }
}


/**
 * Your Solution object will be instantiated and called as such:
 * Solution obj = new Solution(nums);
 * int[] param_1 = obj.reset();
 * int[] param_2 = obj.shuffle();
 */

Python

import random

class Solution:

    def __init__(self, nums: List[int]):
        self.original = nums[:]


    def reset(self) -> List[int]:
        """
        Resets the array to its original configuration and return it.
        """
        return self.original
        

    def shuffle(self) -> List[int]:
        """
        Returns a random shuffling of the array.
        """
        nums = self.original[:]
        random_nums = random.shuffle(nums)
        return nums
        


# Your Solution object will be instantiated and called as such:
# obj = Solution(nums)
# param_1 = obj.reset()
# param_2 = obj.shuffle()

Complexity Analysis

• Time Complexity
  • reset(): O(1)
  • shuffle(): O(n)
• Space Complexity
  • O(n)