PerturbedStepSolution¶

class probnum.diffeq.perturbed.step.PerturbedStepSolution(scales, locations, states, interpolants)[source]¶

Bases: probnum.diffeq.ODESolution

Probabilistic ODE solution corresponding to the PerturbedStepSolver.

Attributes Summary

`frozen`
`locations`
`states`

Methods Summary

`__call__`(t)	Evaluate the time-continuous posterior at location t
`append`(location, state)	rtype `None`
`freeze`()	rtype `None`
`interpolate`(t[, previous_index, next_index])	Evaluate the posterior at a measurement-free point.
`sample`(rng[, t, size])	Sample from the ODE solution.
`transform_base_measure_realizations`(...)	Transform a set of realizations from a base measure into realizations from the posterior.

Attributes Documentation

frozen¶

locations¶

states¶

Methods Documentation

__call__(t)¶

Evaluate the time-continuous posterior at location t

Algorithm: 1. Find closest t_prev and t_next, with t_prev < t < t_next 2. Predict from t_prev to t 3. (if self._with_smoothing=True) Predict from t to t_next 4. (if self._with_smoothing=True) Smooth from t_next to t 5. Return random variable for time t

Parameters: t (Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]) – Location, or time, at which to evaluate the posterior.
Returns: Estimate of the states at time t.
Return type: randvars.RandomVariable or randvars._RandomVariableList

append(location, state)¶

Return type: None

freeze()¶

Return type: None

interpolate(t, previous_index=None, next_index=None)[source]¶

Evaluate the posterior at a measurement-free point.

Returns: Dense evaluation.
Return type: randvars.RandomVariable or randvars._RandomVariableList

sample(rng, t=None, size=())¶

Sample from the ODE solution.

Parameters

rng (Generator) – Random number generator.
t (Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], None]) – Location / time at which to sample. If nothing is specified, samples at the ODE-solver grid points are computed. If it is a float, a sample of the ODE-solution at this time point is computed. Similarly, if it is a list of floats (or an array), samples at the specified grid-points are returned. This is not the same as computing i.i.d samples at the respective locations.
size (Union[int, Integral, integer, Iterable[Union[int, Integral, integer]], None]) – Number of samples.

Return type

ndarray

transform_base_measure_realizations(base_measure_realizations, t)¶

Transform a set of realizations from a base measure into realizations from the posterior.

Parameters

base_measure_realizations (ndarray) – Base measure realizations.
t (Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]) – Locations on which the transformed realizations shall represent realizations from the posterior.

Returns

Transformed realizations.

Return type

np.ndarray