ROM

class ROM(model, *, lifter=None, transformer=None, basis=None, ddt_estimator=None)

Nonparametric 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

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

• opinf.models.ContinuousModel

• opinf.models.DiscreteModel

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.