ParametricContinuousModel#
- class ParametricContinuousModel(operators, solver=None)[source]#
Parametric system of ordinary differential equations \(\ddt\qhat(t; \bfmu) = \fhat(\qhat(t; \bfmu), \u(t); \bfmu)\).
Here,
\(\qhat(t;\bfmu)\in\RR^{r}\) is the model state,
\(\u(t)\in\RR^{m}\) is the (optional) input, and
\(\bfmu\in\RR^{p}\in\RR^{p}\) is the parameter vector.
The structure of \(\fhat\) is specified through the
operators
argument.- Parameters:
- operatorslist of
opinf.operators
objects Operators comprising the terms of the model.
- operatorslist of
Properties:- A_#
opinf.operators.LinearOperator
(orNone
).
- B_#
opinf.operators.InputOperator
(orNone
).
- G_#
opinf.operators.CubicOperator
(orNone
).
- H_#
opinf.operators.QuadraticOperator
(orNone
).
- N_#
opinf.operators.StateInputOperator
(orNone
).
- c_#
opinf.operators.ConstantOperator
(orNone
).
- input_dimension#
Dimension \(m\) of the input (zero if there are no inputs).
- operators#
Operators comprising the terms of the model.
- parameter_dimension#
Dimension \(p\) of a parameter vector \(\bfmu\).
- solver#
Solver for the least-squares regression, see
opinf.lstsq
.
- state_dimension#
Dimension \(r\) of the state.
Methods:Make a copy of the model.
Construct a nonparametric model by fixing the parameter value.
Learn the model operators from data.
Construct a reduced-order model by taking the (Petrov-)Galerkin projection of each model operator.
Sum the state Jacobian of each model operator.
Solve the system of ordinary differential equations.
Solve the Operator Inference regression using the data from the last
fit()
call, then extract the inferred operators.Evaluate the right-hand side of the model by applying each operator and summing the results.