Struct BackwardEuler

pub struct BackwardEuler {
    pub opt_alg: Optimization,
}

Implicit, single-stage, first-order, fixed-step, Runge-Kutta method.¹

---

1. Also known as the backward Euler method. ↩

Fields

opt_alg: Optimization

Optimization algorithm for equation solving.

Trait Implementations

impl Debug for BackwardEuler

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for BackwardEuler

fn default() -> Self

Returns the “default value” for a type.

impl<Y, J, U> Implicit<Y, J, U> for BackwardEuler

where Self: InterpolateSolution<Y, U>, Y: Tensor + TensorArray + Div<J, Output = Y>, for<'a> &'a Y: Mul<TensorRank0, Output = Y> + Sub<&'a Y, Output = Y>, J: Hessian + Tensor + TensorArray, U: TensorVec<Item = Y>,

fn integrate( &self, function: impl Fn(&TensorRank0, &Y) -> Y, jacobian: impl Fn(&TensorRank0, &Y) -> J, time: &[TensorRank0], initial_condition: Y, ) -> Result<(Vector, U), IntegrationError>

Solves an initial value problem by implicitly integrating a system of ordinary differential equations.

impl<Y, U> InterpolateSolution<Y, U> for BackwardEuler

where Y: Tensor + TensorArray, for<'a> &'a Y: Mul<TensorRank0, Output = Y> + Sub<&'a Y, Output = Y>, U: TensorVec<Item = Y>,

fn interpolate( &self, _time: &Vector, _tp: &Vector, _yp: &U, _function: impl Fn(&TensorRank0, &Y) -> Y, ) -> U

Solution interpolation.