Given four integers a, b, c and d. Player A & B try to score a penalty. Probability of A shooting the target is a / b while probability of B shooting the target is c / d. The player who scores the penalty first wins. The task is to find the probability of A winning the match.
Examples:
Input: a = 1, b = 3, c = 1, d = 3
Output: 0.6
Input: a = 1, b = 2, c = 10, d = 11
Output: 0.52381
Approach: If we consider variables K = a / b as the probability of A shooting the target and R = (1 – (a / b)) * (1 – (c / d)) as the probability that A as well as B both missing the target.
Therefore, the solution forms a Geometric progression K * R0 + K * R1 + K * R2 + ….. whose sum is (K / 1 – R). After putting the values of K and R we get the formula as K * (1 / (1 – (1 – r) * (1 – k))).
Below is the implementation of the above approach:
C++
// C++ implementation of the approach #include <bits/stdc++.h> using namespace std; // Function to return the probability of A winning double getProbability( int a, int b, int c, int d) { // p and q store the values // of fractions a / b and c / d double p = ( double )a / ( double )b; double q = ( double )c / ( double )d; // To store the winning probability of A double ans = p * (1 / (1 - (1 - q) * (1 - p))); return ans; } // Driver code int main() { int a = 1, b = 2, c = 10, d = 11; cout << getProbability(a, b, c, d); return 0; } |
Java
// Java implementation of the approach class GFG { // Function to return the probability // of A winning static double getProbability( int a, int b, int c, int d) { // p and q store the values // of fractions a / b and c / d double p = ( double ) a / ( double ) b; double q = ( double ) c / ( double ) d; // To store the winning probability of A double ans = p * ( 1 / ( 1 - ( 1 - q) * ( 1 - p))); return ans; } // Driver code public static void main(String[] args) { int a = 1 , b = 2 , c = 10 , d = 11 ; System.out.printf( "%.5f" , getProbability(a, b, c, d)); } } // This code contributed by Rajput-Ji |
Python3
# Python3 implementation of the approach # Function to return the probability # of A winning def getProbability(a, b, c, d) : # p and q store the values # of fractions a / b and c / d p = a / b; q = c / d; # To store the winning probability of A ans = p * ( 1 / ( 1 - ( 1 - q) * ( 1 - p))); return round (ans, 5 ); # Driver code if __name__ = = "__main__" : a = 1 ; b = 2 ; c = 10 ; d = 11 ; print (getProbability(a, b, c, d)); # This code is contributed by Ryuga |
C#
// C# implementation of the approach using System; class GFG { // Function to return the probability // of A winning public static double getProbability( int a, int b, int c, int d) { // p and q store the values // of fractions a / b and c / d double p = ( double ) a / ( double ) b; double q = ( double ) c / ( double ) d; // To store the winning probability of A double ans = p * (1 / (1 - (1 - q) * (1 - p))); return ans; } // Driver code public static void Main( string [] args) { int a = 1, b = 2, c = 10, d = 11; Console.Write( "{0:F5}" , getProbability(a, b, c, d)); } } // This code is contributed by Shrikant13 |
PHP
<?php // PHP implementation of the approach // Function to return the probability // of A winning function getProbability( $a , $b , $c , $d ) { // p and q store the values // of fractions a / b and c / d $p = $a / $b ; $q = $c / $d ; // To store the winning probability of A $ans = $p * (1 / (1 - (1 - $q ) * (1 - $p ))); return round ( $ans ,6); } // Driver code $a = 1; $b = 2; $c = 10; $d = 11; echo getProbability( $a , $b , $c , $d ); // This code is contributed by chandan_jnu ?> |
Javascript
<script> // JavaScript implementation of the approach // Function to return the probability // of A winning function getProbability(a , b , c , d) { // p and q store the values // of fractions a / b and c / d var p = a / b; var q = c / d; // To store the winning probability of A var ans = p * (1 / (1 - (1 - q) * (1 - p))); return ans; } // Driver code var a = 1, b = 2, c = 10, d = 11; document.write( getProbability(a, b, c, d).toFixed(5)); // This code contributed by aashish1995 </script> |
0.52381
Time Complexity: O(1)
Auxiliary Space: O(1)
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