pmrf.fitting.FitResults

class pmrf.fitting.FitResults(measured=None, initial_model=None, fitted_model=None, solver_results=None, settings=None)

Bases: object

Container for the results of a model fitting process.

Parameters:

• measured (Network | NetworkCollection | None)

• initial_model (Model | None)

• fitted_model (Model | None)

• solver_results (Model)

• settings (FitSettings | None)

measured

The original measured data (target).

Type:

skrf.Network, NetworkCollection, or None

initial_model

The model with the initial parameters.

Type:

Model or None

fitted_model

The model with the fitted parameters.

Type:

Model or None

solver_results

The raw result object returned by the optimization backend.

Type:

Any

settings

The configuration used to execute the fit.

Type:

FitSettings or None

__init__(measured=None, initial_model=None, fitted_model=None, solver_results=None, settings=None)

Parameters:

• measured (Network | NetworkCollection | None)

• initial_model (Model | None)

• fitted_model (Model | None)

• solver_results (Model | None)

• settings (FitSettings | None)

Return type:

None

Methods

__delattr__(name, /)	Implement delattr(self, name).
__dir__()	Default dir() implementation.
__eq__(other)	Return self==value.
__format__(format_spec, /)	Default object formatter.
__ge__(value, /)	Return self>=value.
__getattribute__(name, /)	Return getattr(self, name).
__gt__(value, /)	Return self>value.
__init__([measured, initial_model, ...])
__init_subclass__	This method is called when a class is subclassed.
__le__(value, /)	Return self<=value.
__lt__(value, /)	Return self<value.
__ne__(value, /)	Return self!=value.
__new__(**kwargs)
__reduce__()	Helper for pickle.
__reduce_ex__(protocol, /)	Helper for pickle.
__repr__()	Return repr(self).
__setattr__(name, value, /)	Implement setattr(self, name, value).
__sizeof__()	Size of object in memory, in bytes.
__str__()	Return str(self).
__subclasshook__	Abstract classes can override this to customize issubclass().
_decode_recursive(group)
_encode_recursive(obj, group)
_group_to_dict(group)
_read_from_group(group)	Internal driver to load full object state.
_read_network(group)
_read_settings(group)
_save_dict_to_group(d, group)
_write_network(group, ntwk)
_write_settings(group)
_write_to_group(group[, metadata])	Internal driver to save full object state.
decode_solver_results(group)	Decode solver results from an HDF5 group.
encode_solver_results(group)	Encode solver results into an HDF5 group.
load_hdf(path)	Load fit results from an HDF5 file.
plot_s_db([use_initial_model])	Plots the S-parameters (Magnitude in dB) of the Measured vs Fitted data.
save_hdf(path[, metadata])	Save the fit results to an HDF5 file.

Attributes

__annotations__
__dataclass_fields__
__dataclass_params__
__dict__
__doc__
__hash__
__match_args__
__module__
__weakref__	list of weak references to the object (if defined)
fitted_model
initial_model
measured
settings
solver_results

measured: Network | NetworkCollection | None = None

initial_model: Model | None = None

fitted_model: Model | None = None

solver_results: Model = None

settings: FitSettings | None = None

plot_s_db(use_initial_model=False)

Plots the S-parameters (Magnitude in dB) of the Measured vs Fitted data.

save_hdf(path, metadata=None)

Save the fit results to an HDF5 file.

Parameters:

• path (str)

• metadata (dict | None)

classmethod load_hdf(path)

Load fit results from an HDF5 file.

Parameters:

path (str)

Return type:

FitResults

encode_solver_results(group)

Encode solver results into an HDF5 group.

Base implementation uses recursion to handle FitResults, dicts, and lists. Subclasses can override this for specific formats (e.g. Scipy results).

Parameters:

group (Group)

classmethod decode_solver_results(group)

Decode solver results from an HDF5 group.

Parameters:

group (Group)

Return type:

Any

__init__(measured=None, initial_model=None, fitted_model=None, solver_results=None, settings=None)

Parameters:

• measured (Network | NetworkCollection | None)

• initial_model (Model | None)

• fitted_model (Model | None)

• solver_results (Model | None)

• settings (FitSettings | None)

Return type:

None