romtools.workflows.inverse.mf_eki_drivers

Multifidelity ensemble Kalman inversion drivers.

This module extends the single-fidelity EKI workflow with an adaptive low-fidelity surrogate, typically a ROM, to reduce the cost of the inverse solve while preserving high-fidelity correction steps. The implementation uses one high-fidelity ensemble and an additional ROM-only ensemble so that the Kalman update benefits from a larger effective sample set.

MF-EKI supports the same adaptive or periodic ensemble rejuvenation as romtools.workflows.inverse.eki_drivers.run_eki(). When rejuvenation moves the ensemble, the FOM is reevaluated on the shared high-fidelity sample set and the existing ROM validity check is applied. If the ROM error exceeds rom_tolerance, the surrogate is rebuilt before the multifidelity Kalman update is recomputed.

Functions

compute_mf_eki_update(parameter_sample_sets, ...)

Compute the update matrices for the MF-EKI algorithm.

Classes

GaussianProcessQoiModelBuilderWithTrainingData(...)

romtools.workflows.inverse.mf_eki_drivers.compute_mf_eki_update(parameter_sample_sets, fom_results_for_sample_sets, rom_results_for_sample_sets, observations_covariance, regularization_parameter)

Compute the update matrices for the MF-EKI algorithm.