InitializationRoutine¶
- class probnum.diffeq.odefilter.init_routines.InitializationRoutine(*, is_exact, requires_jax)[source]¶
Bases:
ABC
Initialization routines for a filtering-based ODE solver.
One crucial factor for stable implementation of probabilistic ODE solvers is starting with a good approximation of the derivatives of the initial condition [1]. (This is common in all Nordsieck-like ODE solvers.) For this reason, efficient methods of initialization need to be devised. All initialization routines in ProbNum implement the interface
InitializationRoutine
.References
Attributes Summary
Exactness of the computed initial values.
Whether the implementation of the routine relies on JAX.
Methods Summary
__call__
(*, ivp, prior_process)Call self as a function.
Attributes Documentation
- 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
- abstract __call__(*, ivp, prior_process)[source]¶
Call self as a function.
- Parameters:
ivp (InitialValueProblem) –
prior_process (MarkovProcess) –
- Return type: