Trait OdeSolverMethod

pub trait OdeSolverMethod<'a, Eqn>: Clone
where
    Self: Sized,
    Eqn: 'a + OdeEquations,
{
    type State: OdeSolverState<Eqn::V>;

    // Required methods
    fn problem(&self) -> &'a OdeSolverProblem<Eqn>;
    fn checkpoint(&mut self) -> Self::State;
    fn set_state(&mut self, state: Self::State);
    fn into_state(self) -> Self::State;
    fn state(&self) -> StateRef<'_, Eqn::V>;
    fn state_mut(&mut self) -> StateRefMut<'_, Eqn::V>;
    fn jacobian(&self) -> Option<Ref<'_, Eqn::M>>;
    fn mass(&self) -> Option<Ref<'_, Eqn::M>>;
    fn step(&mut self) -> Result<OdeSolverStopReason<Eqn::T>, DiffsolError>;
    fn set_stop_time(&mut self, tstop: Eqn::T) -> Result<(), DiffsolError>;
    fn interpolate(&self, t: Eqn::T) -> Result<Eqn::V, DiffsolError>;
    fn interpolate_out(&self, t: Eqn::T) -> Result<Eqn::V, DiffsolError>;
    fn interpolate_sens(&self, t: Eqn::T) -> Result<Vec<Eqn::V>, DiffsolError>;
    fn order(&self) -> usize;

    // Provided methods
    fn solve(
        &mut self,
        final_time: Eqn::T,
    ) -> Result<(<Eqn::V as DefaultDenseMatrix>::M, Vec<Eqn::T>), DiffsolError>
       where Eqn::V: DefaultDenseMatrix,
             Self: Sized { ... }
    fn solve_dense(
        &mut self,
        t_eval: &[Eqn::T],
    ) -> Result<<Eqn::V as DefaultDenseMatrix>::M, DiffsolError>
       where Eqn::V: DefaultDenseMatrix,
             Self: Sized { ... }
    fn solve_with_checkpointing(
        &mut self,
        final_time: Eqn::T,
        max_steps_between_checkpoints: Option<usize>,
    ) -> Result<(Checkpointing<'a, Eqn, Self>, <Eqn::V as DefaultDenseMatrix>::M, Vec<Eqn::T>), DiffsolError>
       where Eqn::V: DefaultDenseMatrix,
             Self: Sized { ... }
    fn solve_dense_with_checkpointing(
        &mut self,
        t_eval: &[Eqn::T],
        max_steps_between_checkpoints: Option<usize>,
    ) -> Result<(Checkpointing<'a, Eqn, Self>, <Eqn::V as DefaultDenseMatrix>::M), DiffsolError>
       where Eqn::V: DefaultDenseMatrix,
             Self: Sized { ... }
}

Trait for ODE solver methods. This is the main user interface for the ODE solvers.

The solver is responsible for stepping the solution (given in the OdeSolverState), and interpolating the solution at a given time. However, the solver does not own the state, so the user is responsible for creating and managing the state. If the user wants to change the state, they should call set_problem again.

Example

use diffsol::{ OdeSolverMethod, OdeSolverProblem, OdeSolverState, OdeEquationsImplicit, DefaultSolver };

fn solve_ode<'a, Eqn>(solver: &mut impl OdeSolverMethod<'a, Eqn>, t: Eqn::T) -> Eqn::V
where
   Eqn: OdeEquationsImplicit + 'a,
   Eqn::M: DefaultSolver,
{
    while solver.state().t <= t {
        solver.step().unwrap();
    }
    solver.interpolate(t).unwrap()
}

Required Associated Types

type State: OdeSolverState<Eqn::V>

Required Methods

fn problem(&self) -> &'a OdeSolverProblem<Eqn>

Get the current problem

fn checkpoint(&mut self) -> Self::State

Take a checkpoint of the current state of the solver, returning it to the user. This is useful if you want to use this state in another solver or problem but want to keep this solver active. If you don’t need to use this solver again, you can use take_state instead. Note that this will force a reinitialisation of the internal Jacobian for the solver, if it has one.

fn set_state(&mut self, state: Self::State)

Replace the current state of the solver with a new state.

fn into_state(self) -> Self::State

Take the current state of the solver, if it exists, returning it to the user. This is useful if you want to use this state in another solver or problem. Note that this will unset the current problem and solver state, so you will need to call set_problem again before calling step or solve.

fn state(&self) -> StateRef<'_, Eqn::V>

Get the current state of the solver

fn state_mut(&mut self) -> StateRefMut<'_, Eqn::V>

Get a mutable reference to the current state of the solver Note that calling this will cause the next call to step to perform some reinitialisation to take into account the mutated state, this could be expensive for multi-step methods.

fn jacobian(&self) -> Option<Ref<'_, Eqn::M>>

Returns the current jacobian matrix of the solver, if it has one Note that this will force a full recalculation of the Jacobian.

fn mass(&self) -> Option<Ref<'_, Eqn::M>>

Returns the current mass matrix of the solver, if it has one Note that this will force a full recalculation of the mass matrix.

fn step(&mut self) -> Result<OdeSolverStopReason<Eqn::T>, DiffsolError>

Step the solution forward by one step, altering the internal state of the solver. The return value is a Result containing the reason for stopping the solver, possible reasons are:

• InternalTimestep: The solver has taken a step forward in time, the internal state of the solver is at time self.state().t
• RootFound(t_root): The solver has found a root at time t_root. Note that the internal state of the solver is at the internal time step self.state().t, not at time t_root.
• TstopReached: The solver has reached the stop time set by Self::set_stop_time, the internal state of the solver is at time tstop, which is the same as self.state().t

fn set_stop_time(&mut self, tstop: Eqn::T) -> Result<(), DiffsolError>

Set a stop time for the solver. The solver will stop when the internal time reaches this time. Once it stops, the stop time is unset. If tstop is at or before the current internal time, an error is returned.

fn interpolate(&self, t: Eqn::T) -> Result<Eqn::V, DiffsolError>

Interpolate the solution at a given time. This time should be between the current time and the last solver time step

fn interpolate_out(&self, t: Eqn::T) -> Result<Eqn::V, DiffsolError>

Interpolate the integral of the output function at a given time. This time should be between the current time and the last solver time step

fn interpolate_sens(&self, t: Eqn::T) -> Result<Vec<Eqn::V>, DiffsolError>

Interpolate the sensitivity vectors at a given time. This time should be between the current time and the last solver time step

fn order(&self) -> usize

Get the current order of accuracy of the solver (e.g. explict euler method is first-order)

Provided Methods

fn solve( &mut self, final_time: Eqn::T, ) -> Result<(<Eqn::V as DefaultDenseMatrix>::M, Vec<Eqn::T>), DiffsolError>

where Eqn::V: DefaultDenseMatrix, Self: Sized,

Using the provided state, solve the problem up to time final_time Returns a Vec of solution values at timepoints chosen by the solver. After the solver has finished, the internal state of the solver is at time final_time.

fn solve_dense( &mut self, t_eval: &[Eqn::T], ) -> Result<<Eqn::V as DefaultDenseMatrix>::M, DiffsolError>

where Eqn::V: DefaultDenseMatrix, Self: Sized,

Using the provided state, solve the problem up to time t_eval[t_eval.len()-1] Returns a Vec of solution values at timepoints given by t_eval. After the solver has finished, the internal state of the solver is at time t_eval[t_eval.len()-1].

fn solve_with_checkpointing( &mut self, final_time: Eqn::T, max_steps_between_checkpoints: Option<usize>, ) -> Result<(Checkpointing<'a, Eqn, Self>, <Eqn::V as DefaultDenseMatrix>::M, Vec<Eqn::T>), DiffsolError>

where Eqn::V: DefaultDenseMatrix, Self: Sized,

fn solve_dense_with_checkpointing( &mut self, t_eval: &[Eqn::T], max_steps_between_checkpoints: Option<usize>, ) -> Result<(Checkpointing<'a, Eqn, Self>, <Eqn::V as DefaultDenseMatrix>::M), DiffsolError>

where Eqn::V: DefaultDenseMatrix, Self: Sized,

Solve the problem and write out the solution at the given timepoints, using checkpointing so that the solution can be interpolated at any timepoint. See Self::solve_dense for a similar method that does not use checkpointing.

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors

impl<'a, Eqn, M, AugmentedEqn> OdeSolverMethod<'a, Eqn> for ExplicitRk<'a, Eqn, M, AugmentedEqn>

where Eqn: OdeEquations, M: DenseMatrix<V = Eqn::V, T = Eqn::T, C = Eqn::C>, AugmentedEqn: AugmentedOdeEquations<Eqn>, Eqn::V: DefaultDenseMatrix<T = Eqn::T, C = Eqn::C>,

type State = RkState<<Eqn as Op>::V>

impl<'a, M, Eqn, AugmentedEqn, LS> OdeSolverMethod<'a, Eqn> for Sdirk<'a, Eqn, LS, M, AugmentedEqn>

where LS: LinearSolver<Eqn::M>, M: DenseMatrix<T = Eqn::T, V = Eqn::V, C = Eqn::C>, Eqn: OdeEquationsImplicit, Eqn::V: DefaultDenseMatrix<T = Eqn::T, C = Eqn::C>, AugmentedEqn: AugmentedOdeEquationsImplicit<Eqn>,

type State = RkState<<Eqn as Op>::V>

impl<'a, M, Eqn, Nls, AugmentedEqn> OdeSolverMethod<'a, Eqn> for Bdf<'a, Eqn, Nls, M, AugmentedEqn>

where Eqn: OdeEquationsImplicit, AugmentedEqn: AugmentedOdeEquations<Eqn> + OdeEquationsImplicit, M: DenseMatrix<T = Eqn::T, V = Eqn::V, C = Eqn::C>, Eqn::V: DefaultDenseMatrix, Nls: NonLinearSolver<Eqn::M>, for<'b> &'b Eqn::V: VectorRef<Eqn::V>, for<'b> &'b Eqn::M: MatrixRef<Eqn::M>,

type State = BdfState<<Eqn as Op>::V, M>