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Sum of subsets of all the subsets of an array | O(N)

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Given an array arr[] of length N, the task is to find the overall sum of subsets of all the subsets of the array.
Examples: 
 

Input: arr[] = {1, 1} 
Output:
All possible subsets: 
a) {} : 0 
All the possible subsets of this subset 
will be {}, Sum = 0 
b) {1} : 1 
All the possible subsets of this subset 
will be {} and {1}, Sum = 0 + 1 = 1 
c) {1} : 1 
All the possible subsets of this subset 
will be {} and {1}, Sum = 0 + 1 = 1 
d) {1, 1} : 4 
All the possible subsets of this subset 
will be {}, {1}, {1} and {1, 1}, Sum = 0 + 1 + 1 + 2 = 4 
Thus, ans = 0 + 1 + 1 + 4 = 6
Input: arr[] = {1, 4, 2, 12} 
Output: 513 
 

 

Approach: In this article, an approach with O(N) time complexity to solve the given problem will be discussed. 
The key is observing the number of times an element will repeat in all the subsets.
Let’s magnify the view. It is known that every element will appear 2(N – 1) times in the sum of subsets. Now, let’s magnify the view even further and see how the count varies with the subset size.
There are N – 1CK – 1 subsets of size K for every index that include it. 
Contribution of an element for a subset of size K will be equal to 2(K – 1) times its value. Thus, total contribution of an element for all the subsets of length K will be equal to N – 1CK – 1 * 2(K – 1) 
Total contribution among all the subsets will be equal to: 
 

N – 1CN – 1 * 2(N – 1) + N – 1CN – 2 * 2(N – 2 + N – 1CN – 3 * 2(N – 3) + … + N – 1C0 * 20
 

Now, the contribution of each element in the final answer is known. So, multiply it to the sum of all the elements of the array which will give the required answer.
Below is the implementation of the above approach: 
 

C++




// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
#define maxN 10
 
// To store factorial values
int fact[maxN];
 
// Function to return ncr
int ncr(int n, int r)
{
    return (fact[n] / fact[r]) / fact[n - r];
}
 
// Function to return the required sum
int findSum(int* arr, int n)
{
    // Initialising factorial
    fact[0] = 1;
    for (int i = 1; i < n; i++)
        fact[i] = i * fact[i - 1];
 
    // Multiplier
    int mul = 0;
 
    // Finding the value of multiplier
    // according to the formula
    for (int i = 0; i <= n - 1; i++)
        mul += (int)pow(2, i) * ncr(n - 1, i);
 
    // To store the final answer
    int ans = 0;
 
    // Calculate the final answer
    for (int i = 0; i < n; i++)
        ans += mul * arr[i];
 
    return ans;
}
 
// Driver code
int main()
{
    int arr[] = { 1, 1 };
    int n = sizeof(arr) / sizeof(int);
 
    cout << findSum(arr, n);
 
    return 0;
}


Java




// Java implementation of the approach
class GFG
{
static int maxN = 10;
 
// To store factorial values
static int []fact = new int[maxN];
 
// Function to return ncr
static int ncr(int n, int r)
{
    return (fact[n] / fact[r]) / fact[n - r];
}
 
// Function to return the required sum
static int findSum(int[] arr, int n)
{
    // Initialising factorial
    fact[0] = 1;
    for (int i = 1; i < n; i++)
        fact[i] = i * fact[i - 1];
 
    // Multiplier
    int mul = 0;
 
    // Finding the value of multiplier
    // according to the formula
    for (int i = 0; i <= n - 1; i++)
        mul += (int)Math.pow(2, i) * ncr(n - 1, i);
 
    // To store the final answer
    int ans = 0;
 
    // Calculate the final answer
    for (int i = 0; i < n; i++)
        ans += mul * arr[i];
 
    return ans;
}
 
// Driver code
public static void main(String []args)
{
    int arr[] = { 1, 1 };
    int n = arr.length;
 
    System.out.println(findSum(arr, n));
}
}
 
// This code is contributed by Rajput-Ji


Python3




# Python3 implementation of the approach
maxN = 10
 
# To store factorial values
fact = [0]*maxN;
 
# Function to return ncr
def ncr(n, r) :
 
    return (fact[n] // fact[r]) // fact[n - r];
 
# Function to return the required sum
def findSum(arr, n) :
 
    # Initialising factorial
    fact[0] = 1;
    for i in range(1, n) :
        fact[i] = i * fact[i - 1];
 
    # Multiplier
    mul = 0;
 
    # Finding the value of multiplier
    # according to the formula
    for i in range(n) :
        mul += (2 ** i) * ncr(n - 1, i);
 
    # To store the final answer
    ans = 0;
 
    # Calculate the final answer
    for i in range(n) :
        ans += mul * arr[i];
 
    return ans;
 
# Driver code
if __name__ == "__main__" :
 
    arr = [ 1, 1 ];
    n = len(arr);
 
    print(findSum(arr, n));
 
# This code is contributed by AnkitRai01


C#




// C# implementation of the approach
using System;
     
class GFG
{
static int maxN = 10;
 
// To store factorial values
static int []fact = new int[maxN];
 
// Function to return ncr
static int ncr(int n, int r)
{
    return (fact[n] / fact[r]) / fact[n - r];
}
 
// Function to return the required sum
static int findSum(int[] arr, int n)
{
    // Initialising factorial
    fact[0] = 1;
    for (int i = 1; i < n; i++)
        fact[i] = i * fact[i - 1];
 
    // Multiplier
    int mul = 0;
 
    // Finding the value of multiplier
    // according to the formula
    for (int i = 0; i <= n - 1; i++)
        mul += (int)Math.Pow(2, i) * ncr(n - 1, i);
 
    // To store the final answer
    int ans = 0;
 
    // Calculate the final answer
    for (int i = 0; i < n; i++)
        ans += mul * arr[i];
 
    return ans;
}
 
// Driver code
public static void Main(String []args)
{
    int []arr = { 1, 1 };
    int n = arr.Length;
 
    Console.WriteLine(findSum(arr, n));
}
}
 
// This code is contributed by 29AjayKumar


Javascript




<script>
 
// JavaScript implementation of the approach
 
// To store factorial values
let fact = new Array(10);
 
// Function to return ncr
function ncr(n, r)
{
    return (fact[n] / fact[r]) / fact[n - r];
}
 
// Function to return the required sum
function findSum(arr, n)
{
    // Initialising factorial
    fact[0] = 1;
    for (let i = 1; i < n; i++)
        fact[i] = i * fact[i - 1];
 
    // Multiplier
    let mul = 0;
 
    // Finding the value of multiplier
    // according to the formula
    for (let i = 0; i <= n - 1; i++)
        mul += Math.pow(2, i) * ncr(n - 1, i);
 
    // To store the final answer
    let ans = 0;
 
    // Calculate the final answer
    for (let i = 0; i < n; i++)
        ans += mul * arr[i];
 
    return ans;
}
 
// Driver code
 
    let arr = [ 1, 1 ];
    let n = arr.length;
 
    document.write(findSum(arr, n));
 
 
// This code is contributed by Mayank Tyagi
 
</script>


Output: 

6

 

Time Complexity : O(Nlogn) ,where N is the number of elements in an array.

Space Complexity : O(N) ,to store the factorial of numbers from 1 to N



Last Updated : 25 Apr, 2023
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