fit_joint
- pmrf.fitting.fit_joint(model: PyTree, data: NetworkCollection, **kwargs) FitResult
Jointly fits all sub-modules of a circuit using the same features with either optimization or sampling.
This function processes the entire network collection at once. It uses the networks’ names as prefixes for the features to fit, mapping the global model parameters to the entire dataset in a single solve.
Each network is fitted on its own frequency axis, so collections spanning different bands are fitted without being resampled onto a common grid.
- Parameters:
model (PyTree) – The parameter PyTree to fit.
data (NetworkCollection) – A collection of network data whose names are used as prefixes for sub-model features.
**kwargs (dict) – Standard kwargs passed to
pmrf.fitting.fit().
- Returns:
A single result object containing the globally fitted model and backend solution results. (The updated model can be accessed via result.model).
- Return type: