[][src]Trait bacon_sci::ivp::RungeKuttaSolver

pub trait RungeKuttaSolver<N: ComplexField, S: DimName, O: DimName>: Sized where
    DefaultAllocator: Allocator<N, S>,
    DefaultAllocator: Allocator<N::RealField, O>,
    DefaultAllocator: Allocator<N::RealField, O, O>, 
{ pub fn t_coefficients() -> VectorN<N::RealField, O>;
pub fn k_coefficients() -> MatrixMN<N::RealField, O, O>;
pub fn avg_coefficients() -> VectorN<N::RealField, O>;
pub fn error_coefficients() -> VectorN<N::RealField, O>;
pub fn solve_ivp<T: Clone, F: FnMut(N::RealField, &[N], &mut T) -> Result<VectorN<N, S>, String>>(
        self,
        f: F,
        params: &mut T
    ) -> Result<Vec<(N::RealField, VectorN<N, S>)>, String>;
pub fn with_tolerance(self, tol: N::RealField) -> Result<Self, String>;
pub fn with_dt_max(self, max: N::RealField) -> Result<Self, String>;
pub fn with_dt_min(self, min: N::RealField) -> Result<Self, String>;
pub fn with_start(self, t_initial: N::RealField) -> Result<Self, String>;
pub fn with_end(self, t_final: N::RealField) -> Result<Self, String>;
pub fn with_initial_conditions(self, start: &[N]) -> Result<Self, String>;
pub fn build(self) -> Self; }

This trait allows a struct to be used in the Runge-Kutta solver.

Things implementing RungeKuttaSolver should have an RKInfo to handle the actual IVP solving. It should also provide the with_* helper functions for convience.

Examples

See struct RK45 for an example of implementing this trait

Required methods

pub fn t_coefficients() -> VectorN<N::RealField, O>[src]

Returns a vec of coeffecients to multiply the time step by when getting intermediate results. Upper-left portion of Butch Tableaux

pub fn k_coefficients() -> MatrixMN<N::RealField, O, O>[src]

Returns the coefficients to use on the k_i's when finding another k_i. Upper-right portion of the Butch Tableax. Should be an NxN-1 matrix, where N is the order of the Runge-Kutta Method (Or order+1 for adaptive methods)

pub fn avg_coefficients() -> VectorN<N::RealField, O>[src]

Coefficients to use when calculating the final step to take. These are the weights of the weighted average of k_i's. Bottom portion of the Butch Tableaux. For adaptive methods, this is the first row of the bottom portion.

pub fn error_coefficients() -> VectorN<N::RealField, O>[src]

Coefficients to use on the k_i's to find the error between the two orders of Runge-Kutta methods. In the Butch Tableaux, this is the first row of the bottom portion minus the second row.

pub fn solve_ivp<T: Clone, F: FnMut(N::RealField, &[N], &mut T) -> Result<VectorN<N, S>, String>>(
    self,
    f: F,
    params: &mut T
) -> Result<Vec<(N::RealField, VectorN<N, S>)>, String>
[src]

Ideally, call RKInfo.solve_ivp

pub fn with_tolerance(self, tol: N::RealField) -> Result<Self, String>[src]

Set the error tolerance for this solver.

pub fn with_dt_max(self, max: N::RealField) -> Result<Self, String>[src]

Set the maximum time step for this solver.

pub fn with_dt_min(self, min: N::RealField) -> Result<Self, String>[src]

Set the minimum time step for this solver.

pub fn with_start(self, t_initial: N::RealField) -> Result<Self, String>[src]

Set the initial time for this solver.

pub fn with_end(self, t_final: N::RealField) -> Result<Self, String>[src]

Set the end time for this solver.

pub fn with_initial_conditions(self, start: &[N]) -> Result<Self, String>[src]

Set the initial conditions for this solver.

pub fn build(self) -> Self[src]

Build this solver.

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Implementors

impl<N: ComplexField, S: DimName> RungeKuttaSolver<N, S, U6> for RK45<N, S> where
    DefaultAllocator: Allocator<N, S>,
    DefaultAllocator: Allocator<N, U6>,
    DefaultAllocator: Allocator<N, U6, U6>,
    DefaultAllocator: Allocator<N::RealField, U6>,
    DefaultAllocator: Allocator<N::RealField, U6, U6>,
    DefaultAllocator: Allocator<N, S, U6>, 
[src]

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