perturb_uniform

probnum.diffeq.perturbed.step.perturb_uniform(rng, step, solver_order, noise_scale, size=())

Perturb the step with uniformly distributed noise.

Proposed by Abdulle and Garegnani (2020) [1].

Parameters:

• rng (Generator) – Random number generator

• step (float | Real | floating) – Unperturbed step propesed by the steprule

• solver_order (int | Integral | integer) – Order of the solver

• noise_scale (float | Real | floating) – Scales the perturbation

• size (int | Integral | integer | Iterable[int | Integral | integer] | None) – Number of perturbation samples to be drawn. Optional. Default is size=().

Return type:

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.