ParametricROM#
- class ParametricROM(model, *, lifter=None, transformer=None, basis=None, ddt_estimator=None)[source]#
Parametric reduced-order model.
This class connects classes from the various submodules to form a complete reduced-order modeling workflow.
High-dimensional data \(\to\) transformed / preprocessed data \(\to\) compressed data \(\to\) low-dimensional model.
- Parameters:
- model
opinf.models
object Parametric system model, an instance of one of the following:
- lifter
opinf.lift
object or None Lifting transformation.
- transformer
opinf.pre
object or None Preprocesser.
- basis
opinf.basis
object or None Dimensionality reducer.
- ddt_estimator
opinf.ddt
object or None Time derivative estimator. Ignored if
model
is not time continuous.
- model
Properties:- basis#
Dimensionality reducer.
- ddt_estimator#
Time derivative estimator.
- lifter#
Lifting transformation.
- model#
System model.
- transformer#
Preprocesser.
Methods:Map low-dimensional data to the original state space.
Map high-dimensional data to its low-dimensional representation.
Calibrate the model to training data.
Calibrate the time-continuous model to training data, selecting the regularization hyperparameter(s) that minimize the training error while maintaining stability over the testing regime.
Calibrate the fully discrete model to training data, selecting the regularization hyperparameter(s) that minimize the training error while maintaining stability over the testing regime.
Evaluate the reduced-order model.
Project a high-dimensional state vector to the subset of the high-dimensional space that can be represented by the basis.