rhs()#
- InterpDiscreteModel.rhs(parameter, state, input_=None)#
Evaluate the right-hand side of the model by applying each operator and summing the results.
This is the function \(\fhat(\qhat, \u; \bfmu)\) where the model is given by \(\qhat(\bfmu)_{j+1} = \fhat(\qhat(\bfmu)_{j}, \u_{j}; \bfmu)\).
- Parameters:
- parameter(p,) ndarray
Parameter value \(\bfmu\).
- state(r,) ndarray
State vector \(\qhat\).
- input_(m,) ndarray or None
Input vector \(\u\).
- Returns:
- nextstate(r,) ndarray
Evaluation of the right-hand side of the model.
Notes
For repeated
rhs()
calls with the same parameter value, useevaluate()
to first get the nonparametric model corresponding to the parameter value.# Instead of this... >>> values = [parametric_model.rhs(parameter, q, input_) ... for q in list_of_states] # ...it is faster to do this. >>> model_at_parameter = parametric_model.evaluate(parameter) >>> values = [model_at_parameter.rhs(parameter, q, input_) ... for q in list_of_states]