logistic_ode¶

probnum.problems.zoo.filtsmooth.logistic_ode(y0=None, timespan=(0.0, 2.0), step=0.1, params=(6.0, 1.0), initrv=None, evlvar=None, ek0_or_ek1=1, order=3, forward_implementation='classic', backward_implementation='classic')[source]¶

Filtering/smoothing setup for a probabilistic ODE solver for the logistic ODE.

This state space model assumes an integrated Brownian motion prior on the dynamics and constructs the ODE likelihood based on the vector field defining the logistic ODE.

Parameters

y0 (Union[Real, ndarray, None]) – Initial conditions of the Initial Value Problem
timespan (Tuple[Real, Real]) – Time span of the problem
params (Tuple[Real, Real]) – Parameters for the logistic ODE
initrv (Optional[RandomVariable]) – Initial random variable of the probabilistic ODE solver
evlvar (Union[Real, ndarray, None]) – See probnum.diffeq.GaussianIVPFilter
ek0_or_ek1 (Integral) – See probnum.diffeq.GaussianIVPFilter
order (Integral) – Order of integration for the Integrated Brownian Motion prior of the solver.

Returns

regression_problem – RegressionProblem object with time points and zero-observations.
statespace_components – Dictionary containing
- dynamics model
- measurement model
- initial random variable
- The initial value problem based on the logistic ODE.