ooragan.Fitter.fit#

Fitter.fit(files: list[int] = [], background: BackgroundModel = Model(magnitude_phase_delay), fit_method: Literal['shunt', 'reflection', 'kerr_shunt'] = 'shunt', threshold: float | ndarray[tuple[Any, ...], dtype[float64]] = 0.5, trim_start: int = 0, trim_jump: int = 10, save_fig: bool = False, overwrite_warn: bool = False) → None[source]#

Fitting specified resonator data.

Parameters:

fileslist of int, optional: List of indices of files for which to fit the data. Defaults to [] which fits data for all files.
backgroundresonator.base.BackgroundModel, optional: Background model from the resonator library. The default is background.MagnitudePhaseDelay().
fit_methodstr, optional: Fitting method, either "shunt", "reflection" or "kerr". Defaults to "shunt".
writebool, optional: If True, saves the fit results in a .txt file in the “fit_results” folder in the directory specified by savepath. The default is False.
thresholdfloat, optional: A value greater than 0 which determine the error tolerance on fit values. The default is 0.5 (50%).
trim_startint, optional: Where to start trimming the data. The default is 0.
trim_jumpint, optional: Step between the trimming of the data to fit better. The default is 10.
save_figbool, optional: If True, saves the fit plots generated by the function in the “images” folder in the directory specified by savepath. The default is False.
overwrite_warnbool, optional: If True, does not display the overwriting warning popup. The default is False.

Notes

In the shunt mode, the resonance is fitted using

\[S_{21}(f) = 1-\frac{\frac{Q}{Q_c}}{1+2iQ\frac{f-f_0}{f_0}}\]

In the reflection mode, the resonance is fitted using

\[S_{21}(f) = -1+\frac{\frac{Q}{Q_c}}{1+2iQ\frac{f-f_0}{f_0}}\]

The fit itself is performed by the lmfit library. The fit method uses an auxilary method _test_fit to verify the maximum error tolerance on the fit results is respected. If not, the data is trimmed by a specified amount on both sides and the fits is tried again.