/** * \file * \brief Solve the equation \f$f(x)=0\f$ using [Newton-Raphson * method](https://en.wikipedia.org/wiki/Newton%27s_method) for both real and * complex solutions * * The \f$(i+1)^\text{th}\f$ approximation is given by: * \f[ * x_{i+1} = x_i - \frac{f(x_i)}{f'(x_i)} * \f] * * \author [Krishna Vedala](https://github.com/kvedala) * \see bisection_method.cpp, false_position.cpp */ #include #include #include #include constexpr double EPSILON = 1e-10; ///< system accuracy limit constexpr int16_t MAX_ITERATIONS = INT16_MAX; ///< Maximum number of iterations /** define \f$f(x)\f$ to find root for. * Currently defined as: * \f[ * f(x) = x^3 - 4x - 9 * \f] */ static double eq(double i) { return (std::pow(i, 3) - (4 * i) - 9); // original equation } /** define the derivative function \f$f'(x)\f$ * For the current problem, it is: * \f[ * f'(x) = 3x^2 - 4 * \f] */ static double eq_der(double i) { return ((3 * std::pow(i, 2)) - 4); // derivative of equation } /** Main function */ int main() { std::srand(std::time(nullptr)); // initialize randomizer double z = NAN, c = std::rand() % 100, m = NAN, n = NAN; int i = 0; std::cout << "\nInitial approximation: " << c; // start iterations for (i = 0; i < MAX_ITERATIONS; i++) { m = eq(c); n = eq_der(c); z = c - (m / n); c = z; if (std::abs(m) < EPSILON) { // stoping criteria break; } } std::cout << "\n\nRoot: " << z << "\t\tSteps: " << i << std::endl; return 0; }