Diffusion¶
- class probnum.randprocs.markov.continuous.Diffusion¶
Bases:
ABC
Interface for diffusion models \(\sigma: \mathbb{R} \rightarrow \mathbb{R}^d\) and their 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
- abstract __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
- abstract 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.