Find optimal weights which can be used to weigh all the weights in the range [1, X]
Given an integer X, the task is to find an optimal set of weights {w1, w2, w3, …, wn} such that we can weigh/determine all the weights from 1 to X using a two-sided weighing balance pan. Note that all the weights must be unique and n should be as minimum as possible.
Examples:
Input: X = 7
Output: 1 3 9
Weights Left Side Right Side 1 1 1 2 2 + 1 3 3 3 3 4 4 1 + 3 5 5 + 1 + 3 9 6 6 + 3 9 7 7 + 3 1 + 9 Input: X = 20
Output: 1 3 9 27
Approach:
- One optimal approach is to use weights which are powers of 3 i.e. {1, 3, 9, 27, 81, 243, …}
- It can be proved through induction that using {1, 3, 9, 27, 81, …, pow(3, n)}, we can balance all the weights from 1 to (pow(3, n + 1) – 1) / 2.
- So, find the values of n such that all the values from 1 to X can be balanced and print the results.
Below is the implementation of the above approach:
C++
// C++ implementation of the approach #include <bits/stdc++.h> using namespace std; // Function to find the optimal weights void findWeights( int X) { int sum = 0; // Number of weights required int power = 0; // Finding the value of required powers of 3 while (sum < X) { sum = pow (3, power + 1) - 1; sum /= 2; power++; } // Optimal Weights are powers of 3 int ans = 1; for ( int i = 1; i <= power; i++) { cout << ans << " " ; ans = ans * 3; } } // Driver code int main() { int X = 2; findWeights(X); return 0; } |
Java
// Java implementation of the approach import java.util.*; public class GFG { // Function to find the optimal weights static void findWeights( int X) { int sum = 0 ; // Number of weights required int power = 0 ; int number = 3 ; // Finding the value of required powers of 3 while (sum < X) { sum = number - 1 ; sum /= 2 ; power++; number *= 3 ; } // Optimal Weights are powers of 3 int ans = 1 ; for ( int i = 1 ; i <= power; i++) { System.out.print(ans + " " ); ans = ans * 3 ; } } // Driver code public static void main (String[] args) { int X = 2 ; findWeights(X); } } // This code is contributed by Sam007. |
Python3
# Python3 implementation of the approach # Function to find the optimal weights def findWeights(X): sum = 0 # Number of weights required power = 0 # Finding the value of required powers of 3 while ( sum < X): sum = pow ( 3 , power + 1 ) - 1 sum / / = 2 power + = 1 # Optimal Weights are powers of 3 ans = 1 for i in range ( 1 , power + 1 ): print (ans, end = " " ) ans = ans * 3 # Driver code X = 2 findWeights(X) # This code is contributed by Mohit Kumar |
C#
// C# implementation of the approach using System; class GFG { // Function to find the optimal weights static void findWeights( int X) { int sum = 0; // Number of weights required int power = 0; int number = 3; // Finding the value of required powers of 3 while (sum < X) { sum = number - 1; sum /= 2; power++; number *= 3; } // Optimal Weights are powers of 3 int ans = 1; for ( int i = 1; i <= power; i++) { Console.Write(ans + " " ); ans = ans * 3; } } // Driver code static public void Main () { int X = 2; findWeights(X); } } // This code is contributed by ajit. |
Javascript
<script> // JavaScript implementation of the approach // Function to find the optimal weights function findWeights(X) { let sum = 0; // Number of weights required let power = 0; let number = 3; // Finding the value of required powers of 3 while (sum < X) { sum = number - 1; sum = Math.floor(sum/2); power++; number *= 3; } // Optimal Weights are powers of 3 let ans = 1; for (let i = 1; i <= power; i++) { document.write(ans + " " ); ans = ans * 3; } } // Driver code let X = 2; findWeights(X); // This code is contributed by unknown2108 </script> |
Output:
1 3
Time Complexity: O(logn)
Auxiliary Space: O(1)
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