ConstantDiffusion

class probnum.randprocs.markov.continuous.ConstantDiffusion

Bases: Diffusion

Constant diffusion and its calibration.

Methods Summary

__call__(t)

Evaluate the diffusion \(\sigma(t)\) at \(t\).

estimate_locally(meas_rv, ...)

Estimate the (local) diffusion and update current (global) estimation in- place.

update_in_place(local_estimate, t)

Methods Documentation

__call__(t)[source]

Evaluate the diffusion \(\sigma(t)\) at \(t\).

Parameters:

t (_SupportsArray[dtype] | _NestedSequence[_SupportsArray[dtype]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) –

Return type:

_SupportsArray[dtype] | _NestedSequence[_SupportsArray[dtype]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes] | ndarray

estimate_locally(meas_rv, meas_rv_assuming_zero_previous_cov, t)[source]

Estimate the (local) diffusion and update current (global) estimation in- place.

Used for uncertainty calibration in the ODE solver.

Parameters:
Return type:

_SupportsArray[dtype] | _NestedSequence[_SupportsArray[dtype]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]

update_in_place(local_estimate, t)[source]