Class astep_boost (o2scl)

O2scl : Class List

template<class step_t, class vec_y_t = boost::numeric::ublas::vector<double>, class vec_dydx_t = vec_y_t, class vec_yerr_t = vec_y_t, class func_t = ode_funct, class fp_t = double>
class astep_boost : public o2scl::astep_base<boost::numeric::ublas::vector<double>, boost::numeric::ublas::vector<double>, boost::numeric::ublas::vector<double>, ode_funct, double>

Adaptive stepper based on Boost.

Note

This class is experimental

Public Functions

inline astep_boost()

inline virtual ~astep_boost()

inline virtual int astep(fp_t &x, fp_t xlimit, fp_t &h, size_t n, vec_y_t &y, vec_dydx_t &dydx_out, vec_yerr_t &yerr, func_t &derivs)

Make an adaptive integration step of the system derivs.

This attempts to take a step of size h from the point x of an n-dimensional system derivs starting with y. On exit, x and y contain the new values at the end of the step, h contains the size of the step, dydx_out contains the derivative at the end of the step, and yerr contains the estimated error at the end of the step.

If the base stepper returns a non-zero value, that value is passed on as the return value of astep(), though the input y may still have been modified by the base stepper.

inline virtual int astep_derivs(fp_t &x, fp_t xlimit, fp_t &h, size_t n, vec_y_t &y, vec_dydx_t &dydx, vec_yerr_t &yerr, func_t &derivs)

Make an adaptive integration step of the system derivs with derivatives.

This attempts to take a step of size h from the point x of an n-dimensional system derivs starting with y and given the initial derivatives dydx. On exit, x, y and dydx contain the new values at the end of the step, h contains the size of the step, dydx contains the derivative at the end of the step, and yerr contains the estimated error at the end of the step.

If the base stepper returns a non-zero value, that value is passed on as the return value of astep(), though the inputs y and dydx may still have been modified by the base stepper.

inline virtual int astep_full(fp_t x, fp_t xlimit, fp_t &x_out, fp_t &h, size_t n, vec_y_t &y, vec_dydx_t &dydx, vec_y_t &yout, vec_yerr_t &yerr, vec_dydx_t &dydx_out, func_t &derivs)

Make an adaptive integration step of the system derivs.

This function performs an adaptive integration step with the n-dimensional system derivs and parameter pa. It Begins at x with initial stepsize h, ensuring that the step goes no farther than xlimit. At the end of the step, the size of the step taken is h and the new value of x is in x_out. Initially, the function values and derivatives should be specified in y and dydx. The function values, derivatives, and the error at the end of the step are given in yout, yerr, and dydx_out. Unlike in ode_step objects, the objects y, yout, dydx, and dydx_out must all be distinct.

If the base stepper returns a non-zero value, that value is passed on as the return value of astep(), though the output parameters may still have been modified by the base stepper.

Public Members

double tol_rel

The maximum relative uncertainty (default \( 10^{-8} \))

double tol_abs

The maximum absolute uncertainty (default \( 10^{-10} \))