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Count subsequences having average of its elements equal to K
  • Difficulty Level : Hard
  • Last Updated : 03 Feb, 2021

Given an array arr[] consisting of N integers and an integer K, the task is to count the number of subsequences of the given array with average K.

Examples:

Input: arr[] = {9, 7, 8, 9}, K = 8
Output: 5
Explanation: The subsequences having average 8 are {8}, {9, 7}, {7, 9}, {9, 7, 8}, {7, 8, 9}.

Input: arr[] = {5, 5, 1}, K = 4
Output: 0
Explanation: No such subsequence can be obtaiend.

Naive Approach: The simplest approach to solve the problem is to use recursion. Follow the steps below to solve the problem:



  1. Two options are possible for each array element, i.e. either to include the current element in the sum or to exclude the current element in the sum and increase the current index for each recursive call.
  2. For both the above possibilities, return the number of subsequences with average K.
  3. The base case is to check if the last index has been reached or not. The average in the base case can be calculated by dividing the sum of array elements included in that subsequence.
  4. If the average is equal to K, then return 1. Otherwise, return 0.

Time Complexity: O(2N)
Auxiliary Space: O(N)

Efficient Approach: The above approach can be optimized using Dynamic Programming. Follow the steps below to solve the problem:

  • Initialize a 3D array, say dp[][][], where dp[i][k][s] is the number of ways to select k integers from the first i integers such that the sum of the selected integers is s.
  • Traverse the array.
  • Two possible options are available for each element, i.e. either to include it or exclude it.
  • If the current element at index i is included, then the next index state will be i + 1 and the count of selected elements will increase from k to k + 1 and the sum s will increase to s + arr[i].
  • If the current element at index i is excluded, only index i will increase to i+1 and all the other states will remain the same.
  • Below is the dp transition state for this problem:

If ith element is included, then dp[i + 1][k + 1][s + arr[i]] += dp[i][k][s]
If ith element is excluded, then dp[i + 1][k][s] += dp[i][k][s]

  • Finally, the answer will be the summation of dp[N][j][K*j] for all j ( 1 ≤ j ≤ N.

Below is the implementation of the above approach:

C++14




// C++ program for the above approach
 
#include <bits/stdc++.h>
using namespace std;
 
// Stores the dp states
int dp[101][101][1001];
 
// Function to find the count of
// subsequences having average K
int countAverage(int n, int K, int* arr)
{
 
    // Base condition
    dp[0][0][0] = 1;
 
    // Three loops for three states
    for (int i = 0; i < n; i++) {
        for (int k = 0; k < n; k++) {
            for (int s = 0; s <= 1000; s++) {
 
                // Recurrence relation
                dp[i + 1][k + 1][s + arr[i]]
                    += dp[i][k][s];
                dp[i + 1][k][s] += dp[i][k][s];
            }
        }
    }
 
    // Stores the sum of dp[n][j][K*j]
    // all possible values of j with
    // average K and sum K * j
    int cnt = 0;
 
    // Iterate over the range [1, N]
    for (int j = 1; j <= n; j++) {
        cnt += dp[n][j][K * j];
    }
 
    // Return the final count
    return cnt;
}
 
// Driver Code
int main()
{
    int arr[] = { 9, 7, 8, 9 };
    int K = 8;
    int N = sizeof(arr) / sizeof(arr[0]);
    cout << countAverage(N, K, arr);
 
    return 0;
}

Java




// Java program for the above approach
import java.util.*;
class GFG
{
 
// Stores the dp states
static int [][][]dp = new int[101][101][1001];
 
// Function to find the count of
// subsequences having average K
static int countAverage(int n, int K, int[] arr)
{
 
    // Base condition
    dp[0][0][0] = 1;
 
    // Three loops for three states
    for (int i = 0; i < n; i++)
    {
        for (int k = 0; k < n; k++)
        {
            for (int s = 0; s <= 100; s++)
            {
 
                // Recurrence relation
                dp[i + 1][k + 1][s + arr[i]]
                    += dp[i][k][s];
                dp[i + 1][k][s] += dp[i][k][s];
            }
        }
    }
 
    // Stores the sum of dp[n][j][K*j]
    // all possible values of j with
    // average K and sum K * j
    int cnt = 0;
 
    // Iterate over the range [1, N]
    for (int j = 1; j <= n; j++)
    {
        cnt += dp[n][j][K * j];
    }
 
    // Return the final count
    return cnt;
}
 
// Driver Code
public static void main(String[] args)
{
    int arr[] = { 9, 7, 8, 9 };
    int K = 8;
    int N = arr.length;
    System.out.print(countAverage(N, K, arr));
}
}
 
// This code is contributed by shikhasingrajput

Python3




# Python3 program for the above approach
 
# Stores the dp states
dp = [[[0 for i in range(1001)] for i in range(101)] for i in range(101)]
 
# Function to find the count of
# subsequences having average K
def countAverage(n, K, arr):
    global dp
    dp[0][0][0] = 1
 
    # Three loops for three states
    for i in range(n):
        for k in range(n):
            for s in range(100):
 
                # Recurrence relation
                dp[i + 1][k + 1][s + arr[i]] += dp[i][k][s]
                dp[i + 1][k][s] += dp[i][k][s]
 
    # Stores the sum of dp[n][j][K*j]
    # all possible values of j with
    # average K and sum K * j
    cnt = 0
 
    # Iterate over the range [1, N]
    for j in range(1, n + 1):
        cnt += dp[n][j][K * j]
 
    # Return the final count
    return cnt
 
# Driver Code
if __name__ == '__main__':
    arr= [9, 7, 8, 9]
    K = 8
    N = len(arr)
 
    print(countAverage(N, K, arr))
 
    # This code is contributed by mohit kumar 29.

C#




// C# program for the above approach
using System;
public class GFG
{
 
// Stores the dp states
static int [,,]dp = new int[101, 101, 1001];
 
// Function to find the count of
// subsequences having average K
static int countAverage(int n, int K, int[] arr)
{
 
    // Base condition
    dp[0, 0, 0] = 1;
 
    // Three loops for three states
    for (int i = 0; i < n; i++)
    {
        for (int k = 0; k < n; k++)
        {
            for (int s = 0; s <= 100; s++)
            {
 
                // Recurrence relation
                dp[i + 1, k + 1, s + arr[i]]
                    += dp[i, k, s];
                dp[i + 1, k, s] += dp[i, k, s];
            }
        }
    }
 
    // Stores the sum of dp[n,j,K*j]
    // all possible values of j with
    // average K and sum K * j
    int cnt = 0;
 
    // Iterate over the range [1, N]
    for (int j = 1; j <= n; j++)
    {
        cnt += dp[n, j, K * j];
    }
 
    // Return the readonly count
    return cnt;
}
 
// Driver Code
public static void Main(String[] args)
{
    int []arr = { 9, 7, 8, 9 };
    int K = 8;
    int N = arr.Length;
    Console.Write(countAverage(N, K, arr));
}
}
 
// This code is contributed by 29AjayKumar

 
 

Output: 
5

 

Time Complexity: O(S*N2) where S is the sum of the array.
Auxiliary Space: O(S*N2) 

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