Struct rgsl::types::ordinary_differential_equations::ODEiv2StepType
source · pub struct ODEiv2StepType { /* private fields */ }
Implementations§
source§impl ODEiv2StepType
impl ODEiv2StepType
sourcepub fn rk2() -> ODEiv2StepType
pub fn rk2() -> ODEiv2StepType
Explicit embedded Runge-Kutta (2, 3) method.
sourcepub fn rk4() -> ODEiv2StepType
pub fn rk4() -> ODEiv2StepType
Explicit 4th order (classical) Runge-Kutta. Error estimation is carried out by the step doubling method. For more efficient estimate of the error, use the embedded methods described below.
sourcepub fn rk45() -> ODEiv2StepType
pub fn rk45() -> ODEiv2StepType
Explicit embedded Runge-Kutta-Fehlberg (4, 5) method. This method is a good general-purpose integrator.
sourcepub fn rkck() -> ODEiv2StepType
pub fn rkck() -> ODEiv2StepType
Explicit embedded Runge-Kutta Cash-Karp (4, 5) method.
sourcepub fn rk8pd() -> ODEiv2StepType
pub fn rk8pd() -> ODEiv2StepType
Explicit embedded Runge-Kutta Prince-Dormand (8, 9) method.
sourcepub fn rk1imp() -> ODEiv2StepType
pub fn rk1imp() -> ODEiv2StepType
Implicit Gaussian first order Runge-Kutta. Also known as implicit Euler or backward Euler method. Error estimation is carried out by the step doubling method. This algorithm requires the Jacobian and access to the driver object via gsl_odeiv2_step_set_driver.
sourcepub fn rk2imp() -> ODEiv2StepType
pub fn rk2imp() -> ODEiv2StepType
Implicit Gaussian second order Runge-Kutta. Also known as implicit mid-point rule. Error estimation is carried out by the step doubling method. This stepper requires the Jacobian and access to the driver object via gsl_odeiv2_step_set_driver.
sourcepub fn rk4imp() -> ODEiv2StepType
pub fn rk4imp() -> ODEiv2StepType
Implicit Gaussian 4th order Runge-Kutta. Error estimation is carried out by the step doubling method. This algorithm requires the Jacobian and access to the driver object via gsl_odeiv2_step_set_driver.
sourcepub fn bsimp() -> ODEiv2StepType
pub fn bsimp() -> ODEiv2StepType
Implicit Bulirsch-Stoer method of Bader and Deuflhard. The method is generally suitable for stiff problems. This stepper requires the Jacobian.
sourcepub fn msadams() -> ODEiv2StepType
pub fn msadams() -> ODEiv2StepType
A variable-coefficient linear multistep Adams method in Nordsieck form. This stepper uses explicit Adams-Bashforth (predictor) and implicit Adams-Moulton (corrector) methods in P(EC)^m functional iteration mode. Method order varies dynamically between 1 and 12. This stepper requires the access to the driver object via gsl_odeiv2_step_set_driver.
sourcepub fn msbdf() -> ODEiv2StepType
pub fn msbdf() -> ODEiv2StepType
A variable-coefficient linear multistep backward differentiation formula (BDF) method in Nordsieck form. This stepper uses the explicit BDF formula as predictor and implicit BDF formula as corrector. A modified Newton iteration method is used to solve the system of non-linear equations. Method order varies dynamically between 1 and 5. The method is generally suitable for stiff problems. This stepper requires the Jacobian and the access to the driver object via gsl_odeiv2_step_set_driver.
Trait Implementations§
source§impl Clone for ODEiv2StepType
impl Clone for ODEiv2StepType
source§fn clone(&self) -> ODEiv2StepType
fn clone(&self) -> ODEiv2StepType
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
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