WrappedScipyODESolution¶
- class probnum.diffeq.perturbed.scipy_wrapper.WrappedScipyODESolution(scipy_solution, rvs)¶
Bases:
probnum.diffeq.ODESolution
ODE solution corresponding to the
WrappedScipyRungeKutta
.Attributes Summary
Methods Summary
__call__
(t)Evaluate the time-continuous solution at time t.
append
(location, state)- rtype
freeze
()- rtype
interpolate
(t[, previous_index, next_index])Evaluate the posterior at a measurement-free point.
sample
(rng[, t, size])Sample from the ODE solution.
Transform a set of realizations from a base measure into realizations from the posterior.
Attributes Documentation
- frozen¶
- locations¶
- states¶
Methods Documentation
- __call__(t)[source]¶
Evaluate the time-continuous solution at time t.
- Parameters
- Returns
Estimate of the states at time
t
based on a fourth order polynomial.- Return type
randvars.RandomVariable or _randomvariablelist._RandomVariableList
- interpolate(t, previous_index=None, next_index=None)¶
Evaluate the posterior at a measurement-free point.
- Returns
Dense evaluation.
- Return type
randvars.RandomVariable or _randomvariablelist._RandomVariableList
- sample(rng, t=None, size=())¶
Sample from the ODE solution.
- Parameters
rng (
Generator
) – Random number generator.t (
Union
[Real
,ndarray
,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
[Integral
,Iterable
[Integral
],None
]) – Number of samples.
- Return type
- transform_base_measure_realizations(base_measure_realizations, t)¶
Transform a set of realizations from a base measure into realizations from the posterior.