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feat : Implemented Babylonian Method (#1837)
* feat : Implemented Babylonian Method
Babylonian method is used to calculate square roots .
* Update numerical_methods/babylonian_method.cpp
Co-authored-by: David Leal <halfpacho@gmail.com>
* updating DIRECTORY.md
* clang-format and clang-tidy fixes for 9596ac79
Co-authored-by: David Leal <halfpacho@gmail.com>
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
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* [Volume](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/math/volume.cpp)
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## Numerical Methods
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* [Babylonian Method](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/numerical_methods/babylonian_method.cpp)
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* [Bisection Method](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/numerical_methods/bisection_method.cpp)
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* [Brent Method Extrema](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/numerical_methods/brent_method_extrema.cpp)
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* [Composite Simpson Rule](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/numerical_methods/composite_simpson_rule.cpp)
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101
numerical_methods/babylonian_method.cpp
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numerical_methods/babylonian_method.cpp
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/**
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* @file
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* @brief [A babylonian method
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* (BM)](https://en.wikipedia.org/wiki/Methods_of_computing_square_roots#Babylonian_method)
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* is an algorithm that computes the square root.
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* @details
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* This algorithm has an application in use case scenario where a user wants
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* find accurate square roots of large numbers
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* @author [Ameya Chawla](https://github.com/ameyachawlaggsipu)
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*/
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#include <cassert> /// for assert
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#include <iostream> /// for IO operations
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#include "math.h"
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/**
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* @namespace numerical_methods
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* @brief Numerical algorithms/methods
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*/
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namespace numerical_methods {
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/**
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* @brief Babylonian methods is an iterative function which returns
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* square root of radicand
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* @param radicand is the radicand
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* @returns x1 the square root of radicand
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*/
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double babylonian_method(double radicand) {
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int i = 1; /// To find initial root or rough approximation
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while (i * i <= radicand) {
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i++;
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}
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i--; /// Real Initial value will be i-1 as loop stops on +1 value
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double x0 = i; /// Storing previous value for comparison
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double x1 =
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(radicand / x0 + x0) / 2; /// Storing calculated value for comparison
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double temp = NAN; /// Temp variable to x0 and x1
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while (std::max(x0, x1) - std::min(x0, x1) < 0.0001) {
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temp = (radicand / x1 + x1) / 2; /// Newly calculated root
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x0 = x1;
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x1 = temp;
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}
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return x1; /// Returning final root
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}
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} // namespace numerical_methods
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/**
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* @brief Self-test implementations
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* @details
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* Declaring two test cases and checking for the error
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* in predicted and true value is less than 0.0001.
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* @returns void
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*/
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static void test() {
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/* descriptions of the following test */
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auto testcase1 = 125348; /// Testcase 1
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auto testcase2 = 752080; /// Testcase 2
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auto real_output1 = 354.045194855; /// Real Output 1
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auto real_output2 = 867.225460881; /// Real Output 2
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auto test_result1 = numerical_methods::babylonian_method(testcase1);
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/// Test result for testcase 1
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auto test_result2 = numerical_methods::babylonian_method(testcase2);
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/// Test result for testcase 2
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assert(std::max(test_result1, real_output1) -
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std::min(test_result1, real_output1) <
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0.0001);
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/// Testing for test Case 1
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assert(std::max(test_result2, real_output2) -
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std::min(test_result2, real_output2) <
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0.0001);
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/// Testing for test Case 2
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std::cout << "All tests have successfully passed!\n";
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}
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/**
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* @brief Main function
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* @param argc commandline argument count (ignored)
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* @param argv commandline array of arguments (ignored)
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* calls automated test function to test the working of fast fourier transform.
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* @returns 0 on exit
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*/
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int main(int argc, char const *argv[]) {
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test(); // run self-test implementations
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// with 2 defined test cases
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return 0;
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}
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