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added ode solve using forward euler method
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207
numerical_methods/ode_forward_euler.cpp
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207
numerical_methods/ode_forward_euler.cpp
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/**
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* \file
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* \authors [Krishna Vedala](https://github.com/kvedala)
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* \brief Solve a multivariable first order [ordinary differential equation
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* (ODEs)](https://en.wikipedia.org/wiki/Ordinary_differential_equation) using
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* [forward Euler
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* method](https://en.wikipedia.org/wiki/Numerical_methods_for_ordinary_differential_equations#Euler_method)
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*
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* \details
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* The ODE being solved is:
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* \f{eqnarray*}{
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* \dot{u} &=& v\\
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* \dot{v} &=& -\omega^2 u\\
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* \omega &=& 1\\
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* [x_0, u_0, v_0] &=& [0,1,0]\qquad\ldots\text{(initial values)}
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* \f}
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* The exact solution for the above problem is:
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* \f{eqnarray*}{
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* u(x) &=& \cos(x)\\
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* v(x) &=& -\sin(x)\\
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* \f}
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* The computation results are stored to a text file `forward_euler.csv` and the
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* exact soltuion results in `exact.csv` for comparison.
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* <img
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* src="https://raw.githubusercontent.com/kvedala/C-Plus-Plus/docs/images/numerical_methods/ode_forward_euler.svg"
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* alt="Implementation solution"/>
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*
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* To implement [Van der Pol
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* oscillator](https://en.wikipedia.org/wiki/Van_der_Pol_oscillator), change the
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* ::problem function to:
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* ```cpp
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* const double mu = 2.0;
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* dy[0] = y[1];
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* dy[1] = mu * (1.f - y[0] * y[0]) * y[1] - y[0];
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* ```
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* \see ode_midpoint_euler.cpp, ode_semi_implicit_euler.cpp
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*/
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#include <cmath>
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#include <ctime>
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#include <fstream>
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#include <iostream>
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#include <valarray>
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/**
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* @brief Problem statement for a system with first-order differential
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* equations. Updates the system differential variables.
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* \note This function can be updated to and ode of any order.
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*
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* @param[in] x independent variable(s)
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* @param[in,out] y dependent variable(s)
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* @param[in,out] dy first-derivative of dependent variable(s)
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*/
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void problem(const double &x, std::valarray<double> *y,
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std::valarray<double> *dy) {
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const double omega = 1.F; // some const for the problem
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dy[0][0] = y[0][1]; // x dot
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dy[0][1] = -omega * omega * y[0][0]; // y dot
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}
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/**
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* @brief Exact solution of the problem. Used for solution comparison.
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*
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* @param[in] x independent variable
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* @param[in,out] y dependent variable
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*/
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void exact_solution(const double &x, std::valarray<double> *y) {
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y[0][0] = std::cos(x);
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y[0][1] = -std::sin(x);
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}
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/** \addtogroup ode Ordinary Differential Equations
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* @{
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*/
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/**
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* @brief Compute next step approximation using the forward-Euler
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* method. @f[y_{n+1}=y_n + dx\cdot f\left(x_n,y_n\right)@f]
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* @param[in] dx step size
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* @param[in] x take \f$x_n\f$ and compute \f$x_{n+1}\f$
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* @param[in,out] y take \f$y_n\f$ and compute \f$y_{n+1}\f$
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* @param[in,out] dy compute \f$f\left(x_n,y_n\right)\f$
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*/
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void forward_euler_step(const double dx, const double &x,
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std::valarray<double> *y, std::valarray<double> *dy) {
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problem(x, y, dy);
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y[0] += dy[0] * dx;
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}
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/**
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* @brief Compute approximation using the forward-Euler
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* method in the given limits.
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* @param[in] dx step size
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* @param[in] x0 initial value of independent variable
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* @param[in] x_max final value of independent variable
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* @param[in,out] y take \f$y_n\f$ and compute \f$y_{n+1}\f$
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* @param[in] save_to_file flag to save results to a CSV file (1) or not (0)
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* @returns time taken for computation in seconds
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*/
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double forward_euler(double dx, double x0, double x_max,
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std::valarray<double> *y, bool save_to_file = false) {
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std::valarray<double> dy = y[0];
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std::ofstream fp;
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if (save_to_file) {
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fp.open("forward_euler.csv", std::ofstream::out);
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if (!fp.is_open()) {
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std::perror("Error! ");
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}
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}
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std::size_t L = y->size();
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/* start integration */
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std::clock_t t1 = std::clock();
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double x = x0;
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do // iterate for each step of independent variable
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{
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if (save_to_file && fp.is_open()) {
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// write to file
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fp << x << ",";
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for (int i = 0; i < L - 1; i++) {
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fp << y[0][i] << ",";
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}
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fp << y[0][L - 1] << "\n";
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}
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forward_euler_step(dx, x, y, &dy); // perform integration
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x += dx; // update step
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} while (x <= x_max); // till upper limit of independent variable
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/* end of integration */
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std::clock_t t2 = std::clock();
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if (fp.is_open())
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fp.close();
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return static_cast<double>(t2 - t1) / CLOCKS_PER_SEC;
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}
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/** @} */
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/**
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* Function to compute and save exact solution for comparison
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*
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* \param [in] X0 initial value of independent variable
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* \param [in] X_MAX final value of independent variable
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* \param [in] step_size independent variable step size
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* \param [in] Y0 initial values of dependent variables
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*/
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void save_exact_solution(const double &X0, const double &X_MAX,
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const double &step_size,
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const std::valarray<double> &Y0) {
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double x = X0;
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std::valarray<double> y = Y0;
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std::ofstream fp("exact.csv", std::ostream::out);
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if (!fp.is_open()) {
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std::perror("Error! ");
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return;
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}
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std::cout << "Finding exact solution\n";
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std::clock_t t1 = std::clock();
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do {
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fp << x << ",";
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for (int i = 0; i < y.size() - 1; i++) {
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fp << y[i] << ",";
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}
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fp << y[y.size() - 1] << "\n";
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exact_solution(x, &y);
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x += step_size;
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} while (x <= X_MAX);
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std::clock_t t2 = std::clock();
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double total_time = static_cast<double>(t2 - t1) / CLOCKS_PER_SEC;
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std::cout << "\tTime = " << total_time << " ms\n";
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fp.close();
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}
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/**
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* Main Function
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*/
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int main(int argc, char *argv[]) {
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double X0 = 0.f; /* initial value of x0 */
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double X_MAX = 10.F; /* upper limit of integration */
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std::valarray<double> Y0 = {1.f, 0.f}; /* initial value Y = y(x = x_0) */
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double step_size;
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if (argc == 1) {
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std::cout << "\nEnter the step size: ";
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std::cin >> step_size;
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} else {
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// use commandline argument as independent variable step size
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step_size = std::atof(argv[1]);
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}
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// get approximate solution
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double total_time = forward_euler(step_size, X0, X_MAX, &Y0, true);
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std::cout << "\tTime = " << total_time << " ms\n";
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/* compute exact solution for comparion */
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save_exact_solution(X0, X_MAX, step_size, Y0);
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return 0;
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}
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