NonProbabilisticFitWithJacobian

class probnum.diffeq.odefilter.init_routines.NonProbabilisticFitWithJacobian(*, dt=0.01, observation_noise_std=1e-07, method='Radau')

Bases: _NonProbabilisticFitBase

Fit the prior process to a few steps of a non-probabilistic solver and use Jacobians.

Attributes Summary

is_exact	Exactness of the computed initial values.
requires_jax	Whether the implementation of the routine relies on JAX.

Methods Summary

__call__(*, ivp, prior_process)

Call self as a function.

Attributes Documentation

Parameters

• dt (Optional[Union[float, Real, floating]]) –

• method (str) –

is_exact

Exactness of the computed initial values.

Some initialization routines yield the exact initial derivatives, some others only yield approximations.

requires_jax

Whether the implementation of the routine relies on JAX.

Methods Documentation

__call__(*, ivp, prior_process)

Call self as a function.

Parameters

• ivp (InitialValueProblem) –

• prior_process (MarkovProcess) –

Return type

RandomVariable