EKFComponent

class probnum.filtsmooth.gaussian.approx.EKFComponent(non_linear_model)

Bases: abc.ABC

Interface for extended Kalman filtering components.

Methods Summary

backward_realization(realization_obtained, rv)

Approximate backward-propagation of a realization of a random variable.

backward_rv(rv_obtained, rv[, rv_forwarded, ...])

Approximate backward-propagation of a random variable.

forward_realization(realization, t[, dt, ...])

Approximate forward-propagation of a realization of a random variable.

forward_rv(rv, t[, dt, compute_gain, ...])

Approximate forward-propagation of a random variable.

linearize(at_this_rv)

Linearize the transition and make it tractable.

Methods Documentation

backward_realization(realization_obtained, rv, rv_forwarded=None, gain=None, t=None, dt=None, _diffusion=1.0, _linearise_at=None)[source]

Approximate backward-propagation of a realization of a random variable.

backward_rv(rv_obtained, rv, rv_forwarded=None, gain=None, t=None, dt=None, _diffusion=1.0, _linearise_at=None)[source]

Approximate backward-propagation of a random variable.

forward_realization(realization, t, dt=None, compute_gain=False, _diffusion=1.0, _linearise_at=None)[source]

Approximate forward-propagation of a realization of a random variable.

Return type

Tuple[Normal, Dict]

forward_rv(rv, t, dt=None, compute_gain=False, _diffusion=1.0, _linearise_at=None)[source]

Approximate forward-propagation of a random variable.

Return type

Tuple[Normal, Dict]

abstract linearize(at_this_rv)[source]

Linearize the transition and make it tractable.

Return type

Transition