/** * \file * \authors [Krishna Vedala](https://github.com/kvedala) * \brief Solve a multivariable first order [ordinary differential equation * (ODEs)](https://en.wikipedia.org/wiki/Ordinary_differential_equation) using * [midpoint Euler * method](https://en.wikipedia.org/wiki/Midpoint_method) * * \details * The ODE being solved is: * \f{eqnarray*}{ * \dot{u} &=& v\\ * \dot{v} &=& -\omega^2 u\\ * \omega &=& 1\\ * [x_0, u_0, v_0] &=& [0,1,0]\qquad\ldots\text{(initial values)} * \f} * The exact solution for the above problem is: * \f{eqnarray*}{ * u(x) &=& \cos(x)\\ * v(x) &=& -\sin(x)\\ * \f} * The computation results are stored to a text file `midpoint_euler.csv` and * the exact soltuion results in `exact.csv` for comparison. Implementation solution * * To implement [Van der Pol * oscillator](https://en.wikipedia.org/wiki/Van_der_Pol_oscillator), change the * ::problem function to: * ```cpp * const double mu = 2.0; * dy[0] = y[1]; * dy[1] = mu * (1.f - y[0] * y[0]) * y[1] - y[0]; * ``` * \see ode_forward_euler.c, ode_semi_implicit_euler.c */ #include #include #include #include #define order 2 /**< number of dependent variables in ::problem */ /** * @brief Problem statement for a system with first-order differential * equations. Updates the system differential variables. * \note This function can be updated to and ode of any order. * * @param[in] x independent variable(s) * @param[in,out] y dependent variable(s) * @param[in,out] dy first-derivative of dependent variable(s) */ void problem(const double *x, double *y, double *dy) { const double omega = 1.F; // some const for the problem dy[0] = y[1]; // x dot dy[1] = -omega * omega * y[0]; // y dot } /** * @brief Exact solution of the problem. Used for solution comparison. * * @param[in] x independent variable * @param[in,out] y dependent variable */ void exact_solution(const double *x, double *y) { y[0] = cos(x[0]); y[1] = -sin(x[0]); } /** * @brief Compute next step approximation using the midpoint-Euler * method. * @f[y_{n+1} = y_n + dx\, f\left(x_n+\frac{1}{2}dx, * y_n + \frac{1}{2}dx\,f\left(x_n,y_n\right)\right)@f] * @param[in] dx step size * @param[in,out] x take @f$x_n@f$ and compute @f$x_{n+1}@f$ * @param[in,out] y take @f$y_n@f$ and compute @f$y_{n+1}@f$ * @param[in,out] dy compute @f$y_n+\frac{1}{2}dx\,f\left(x_n,y_n\right)@f$ */ void midpoint_euler_step(double dx, double *x, double *y, double *dy) { problem(x, y, dy); double tmp_x = (*x) + 0.5 * dx; double tmp_y[order]; int o; for (o = 0; o < order; o++) tmp_y[o] = y[o] + 0.5 * dx * dy[o]; problem(&tmp_x, tmp_y, dy); for (o = 0; o < order; o++) y[o] += dx * dy[o]; } /** * @brief Compute approximation using the midpoint-Euler * method in the given limits. * @param[in] dx step size * @param[in] x0 initial value of independent variable * @param[in] x_max final value of independent variable * @param[in,out] y take \f$y_n\f$ and compute \f$y_{n+1}\f$ * @param[in] save_to_file flag to save results to a CSV file (1) or not (0) * @returns time taken for computation in seconds */ double midpoint_euler(double dx, double x0, double x_max, double *y, char save_to_file) { double dy[order]; FILE *fp = NULL; if (save_to_file) { fp = fopen("midpoint_euler.csv", "w+"); if (fp == NULL) { perror("Error! "); return -1; } } /* start integration */ clock_t t1 = clock(); double x = x0; do // iterate for each step of independent variable { if (save_to_file && fp) fprintf(fp, "%.4g,%.4g,%.4g\n", x, y[0], y[1]); // write to file midpoint_euler_step(dx, &x, y, dy); // perform integration x += dx; // update step } while (x <= x_max); // till upper limit of independent variable /* end of integration */ clock_t t2 = clock(); if (save_to_file && fp) fclose(fp); return (double)(t2 - t1) / CLOCKS_PER_SEC; } /** Main Function */ int main(int argc, char *argv[]) { double X0 = 0.f; /* initial value of x0 */ double X_MAX = 10.F; /* upper limit of integration */ double Y0[] = {1.f, 0.f}; /* initial value Y = y(x = x_0) */ double step_size; if (argc == 1) { printf("\nEnter the step size: "); scanf("%lg", &step_size); } else // use commandline argument as independent variable step size step_size = atof(argv[1]); // get approximate solution double total_time = midpoint_euler(step_size, X0, X_MAX, Y0, 1); printf("\tTime = %.6g ms\n", total_time); /* compute exact solution for comparion */ FILE *fp = fopen("exact.csv", "w+"); if (fp == NULL) { perror("Error! "); return -1; } double x = X0; double *y = &(Y0[0]); printf("Finding exact solution\n"); clock_t t1 = clock(); do { fprintf(fp, "%.4g,%.4g,%.4g\n", x, y[0], y[1]); // write to file exact_solution(&x, y); x += step_size; } while (x <= X_MAX); clock_t t2 = clock(); total_time = (t2 - t1) / CLOCKS_PER_SEC; printf("\tTime = %.6g ms\n", total_time); fclose(fp); return 0; }