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Program to find simple moving average | Set-2

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  • Difficulty Level : Hard
  • Last Updated : 11 Jan, 2022

Simple Moving Average is the average obtained from the data for some t period of time . In normal mean, its value get changed with the changing data but in this type of mean it also changes with the time interval. We get the mean for some period t and then we remove some previous data. Again we get new mean and this process continues. This is why it is moving average. This has a great application in the financial market. OR this can be simply visualized as follows.

Given an arr[] of size N, containing only positive integers and an integer K. The task is to compute the simple moving average of previous K elements. 

Examples:

Input: { 1, 3, 5, 6, 8 }, K = 3
Output: 0.33 1.33 3.00 4.67 6.33
Explanation: New number added is 1.0, SMA = 0.33
New number added is 3.0, SMA = 1.33
New number added is 5.0, SMA = 3.0
New number added is 6.0, SMA = 4.67
New number added is 8.0, SMA = 6.33        

Input: Array[]= {2, 5, 7, 3, 11, 9, 13, 12}, K = 2
Output: 1.0 3.5 6 5 7 10 11 12.5

 

Naive Approach: This uses two nested loops. Outer loop traverses the array from left to right. Inner loop computes the average of K previous elements including itself for each index. Finally, the moving average values are printed. The outer loop starts traversal from index K itself. Instead of storing the result, we can directly display the output to avoid using extra spaces.

Time complexity: O(N*K)
Space complexity: O(1)

Efficient Approach: The efficient approach is discussed in the Set-1 of this problem.

Space Optimized approach: This uses sliding window for better time efficiency and space optimization. A window of size K starts from index K and the moving average is printed for each index thereafter. 

Below is the implementation of the above approach. 

C++




// C++ code to find the simple moving average
#include <bits/stdc++.h>
#include <iomanip>
using namespace std;
 
// Function to compute moving average
// of previous K elements
void ComputeMovingAverage(int arr[], int N,
                          int K)
{
    int i;
    float sum = 0;
 
    // Initial sum of K elements.
    for (i = 0; i < K; i++) {
        sum += arr[i];
        cout << setprecision(2) << std::fixed;
        cout << sum / K << " ";
    }
 
    // Compute MA from index K
    float avg;
    for (i = K; i < N; i++) {
        sum -= arr[i - K];
        sum += arr[i];
        avg = sum / K;
        cout << setprecision(2) << std::fixed;
        cout << avg << " ";
    }
}
 
// Driver code
int main()
{
    int arr[] = { 1, 3, 5, 6, 8 };
    int N = sizeof(arr) / sizeof(arr[0]);
    int K = 3;
    ComputeMovingAverage(arr, N, K);
    return 0;
}


Java




// Java code to find the simple moving average
import java.util.*;
class GFG{
 
  // Function to compute moving average
  // of previous K elements
  static void ComputeMovingAverage(int arr[], int N,
                                   int K)
  {
    int i;
    float sum = 0;
 
    // Initial sum of K elements.
    for (i = 0; i < K; i++) {
      sum += arr[i];
      System.out.printf("%.2f ",sum / K);
    }
 
    // Compute MA from index K
    for (i = K; i < N; i++) {
      sum -= arr[i - K];
      sum += arr[i];
      System.out.printf("%.2f ",sum / K);
    }
  }
 
  // Driver code
  public static void main(String[] args)
  {
    int arr[] = { 1, 3, 5, 6, 8 };
    int N = arr.length;
    int K = 3;
    ComputeMovingAverage(arr, N, K);
  }
}
 
// This code is contributed by Rajput-Ji


Python3




# Python code for the above approach
 
# Function to compute moving average
# of previous K elements
def ComputeMovingAverage(arr, N, K):
    i = None
    sum = 0
 
    # Initial sum of K elements.
    for i in range(K):
        sum += arr[i]
        print("%.2f"%(sum / K), end= " ")
 
    # Compute MA from index K
    for i in range(K, N):
        sum -= arr[i - K]
        sum += arr[i]
        avg = sum / K
        print("%.2f"%(avg), end =" ")
 
# Driver code
arr = [1, 3, 5, 6, 8]
N = len(arr)
K = 3
ComputeMovingAverage(arr, N, K)
 
# This code is contributed by Saurabh Jaiswal


C#




// C# code to find the simple moving average
using System;
 
class GFG {
 
  // Function to compute moving average
  // of previous K elements
  static void ComputeMovingAverage(int[] arr, int N,
                                   int K)
  {
    int i;
    float sum = 0;
 
    // Initial sum of K elements.
    for (i = 0; i < K; i++) {
      sum += arr[i];
      Console.Write(Math.Round((sum / K),2) + " ");
    }
 
    // Compute MA from index K
    for (i = K; i < N; i++) {
      sum -= arr[i - K];
      sum += arr[i];
      Console.Write(Math.Round(sum / K, 2) + " ");
    }
  }
 
  // Driver code
  public static void Main(string[] args)
  {
    int[] arr = { 1, 3, 5, 6, 8 };
    int N = arr.Length;
    int K = 3;
    ComputeMovingAverage(arr, N, K);
  }
}
 
// This code is contributed by ukasp.


Javascript




<script>
       // JavaScript code for the above approach
 
 
       // Function to compute moving average
       // of previous K elements
       function ComputeMovingAverage(arr, N,
           K) {
           let i;
           let sum = 0;
 
           // Initial sum of K elements.
           for (i = 0; i < K; i++) {
               sum += arr[i];
               document.write((sum / K).toFixed(2) + " ");
           }
 
           // Compute MA from index K
           for (i = K; i < N; i++) {
               sum -= arr[i - K];
               sum += arr[i];
               avg = sum / K;
               document.write((avg).toFixed(2) + " ");
           }
       }
 
       // Driver code
 
       let arr = [1, 3, 5, 6, 8];
       let N = arr.length;
       let K = 3;
       ComputeMovingAverage(arr, N, K);
 
 // This code is contributed by Potta Lokesh
   </script>


 
 

Output

0.33 1.33 3.00 4.67 6.33 

Time complexity: O(N)
Space complexity: O(1) 


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