perturb_uniform¶

probnum.diffeq.perturbed.step.perturb_uniform(rng, step, solver_order, noise_scale, size=())[source]¶

Perturb the step with uniformly distributed noise.

Proposed by Abdulle and Garegnani (2020) 1.

Parameters

rng (Generator) – Random number generator
step (Union[float, Real, floating]) – Unperturbed step propesed by the steprule
solver_order (Union[int, Integral, integer]) – Order of the solver
noise_scale (Union[float, Real, floating]) – Scales the perturbation
size (Optional[Union[int, Integral, integer, Iterable[Union[int, Integral, integer]]]]) – Number of perturbation samples to be drawn. Optional. Default is size=().

Return type

Union[float, ndarray]

References

1: Abdulle, A. and Garegnani, G. Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration. Statistics and Computing. 2020.