Given an array, write a program to generate a random permutation of array elements. This question is also asked as “shuffle a deck of cards” or “randomize a given array”.
Let the given array be arr[]. A simple solution is to create an auxiliary array temp[] which is initially a copy of arr[]. Randomly select an element from temp[], copy the randomly selected element to arr[0] and remove the selected element from temp[]. Repeat the same process n times and keep copying elements to arr[1], arr[2], … . The time complexity of this solution will be O(n^2).
Fisher–Yates shuffle Algorithm works in O(n) time complexity. The assumption here is, we are given a function rand() that generates random number in O(1) time.
The idea is to start from the last element, swap it with a randomly selected element from the whole array (including last). Now consider the array from 0 to n-2 (size reduced by 1), and repeat the process till we hit the first element.
The idea is to start from the last element, swap it with a randomly selected element from the whole array (including last). Now consider the array from 0 to n-2 (size reduced by 1), and repeat the process till we hit the first element.
Following is the detailed algorithm
To shuffle an array a of n elements (indices 0..n-1): for i from n - 1 downto 1 do j = random integer with 0 <= j <= i exchange a[j] and a[i]
Following is C++ implementation of this algorithm.
// C Program to shuffle a given array #include <stdio.h> #include <stdlib.h> #include <time.h> // A utility function to swap to integers void swap ( int *a, int *b) { int temp = *a; *a = *b; *b = temp; } // A utility function to print an array void printArray ( int arr[], int n) { for ( int i = 0; i < n; i++) printf ( "%d " , arr[i]); printf ( "\n" ); } // A function to generate a random permutation of arr[] void randomize ( int arr[], int n ) { // Use a different seed value so that we don't get same // result each time we run this program srand ( time (NULL) ); // Start from the last element and swap one by one. We don't // need to run for the first element that's why i > 0 for ( int i = n-1; i > 0; i--) { // Pick a random index from 0 to i int j = rand () % (i+1); // Swap arr[i] with the element at random index swap(&arr[i], &arr[j]); } } // Driver program to test above function. int main() { int arr[] = {1, 2, 3, 4, 5, 6, 7, 8}; int n = sizeof (arr)/ sizeof (arr[0]); randomize (arr, n); printArray(arr, n); return 0; } |
Output:
7 8 4 6 3 1 2 5
The above function assumes that rand() generates a random number.
Time Complexity: O(n), assuming that the function rand() takes O(1) time.
How does this work?
The probability that ith element (including the last one) goes to last position is 1/n, because we randomly pick an element in first iteration.
The probability that ith element (including the last one) goes to last position is 1/n, because we randomly pick an element in first iteration.
The probability that ith element goes to second last position can be proved to be 1/n by dividing it in two cases.
Case 1: i = n-1 (index of last element):
The probability of last element going to second last position is = (probability that last element doesn't stay at its original position) x (probability that the index picked in previous step is picked again so that the last element is swapped)
So the probability = ((n-1)/n) x (1/(n-1)) = 1/n
Case 2: 0 < i < n-1 (index of non-last):
The probability of ith element going to second position = (probability that ith element is not picked in previous iteration) x (probability that ith element is picked in this iteration)
So the probability = ((n-1)/n) x (1/(n-1)) = 1/n
Case 1: i = n-1 (index of last element):
The probability of last element going to second last position is = (probability that last element doesn't stay at its original position) x (probability that the index picked in previous step is picked again so that the last element is swapped)
So the probability = ((n-1)/n) x (1/(n-1)) = 1/n
Case 2: 0 < i < n-1 (index of non-last):
The probability of ith element going to second position = (probability that ith element is not picked in previous iteration) x (probability that ith element is picked in this iteration)
So the probability = ((n-1)/n) x (1/(n-1)) = 1/n
We can easily generalize above proof for any other position.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
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