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:
modelopinf.models object

Parametric system model, an instance of one of the following:

lifteropinf.lift object or None

Lifting transformation.

transformeropinf.pre object or None

Preprocesser.

basisopinf.basis object or None

Dimensionality reducer.

ddt_estimatoropinf.ddt object or None

Time derivative estimator. Ignored if model is not time continuous.

Properties:
basis#

Dimensionality reducer.

ddt_estimator#

Time derivative estimator.

lifter#

Lifting transformation.

model#

System model.

transformer#

Preprocesser.

Methods:

decode

Map low-dimensional data to the original state space.

encode

Map high-dimensional data to its low-dimensional representation.

fit

Calibrate the model to training data.

fit_regselect_continuous

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.

fit_regselect_discrete

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.

predict

Evaluate the reduced-order model.

project

Project a high-dimensional state vector to the subset of the high-dimensional space that can be represented by the basis.