pyepr.resonator_profile_analysis.ResonatorProfileAnalysis¶

class pyepr.resonator_profile_analysis.ResonatorProfileAnalysis(dataset, f_lims=(32, 36))¶

Analysis and calculation of resonator profiles.

Parameters:

datasetxr.xarray: The dataset containing the nutations. It must have both a ‘LO’ axis and a ‘pulse0_tp’ axis.
f_limstuple, optional: The frequency limits of the resonator profile, by default (33,35)

process_nutations(noisedensity=None, threshold=2, nfft=1000)¶

Uses a power series to extract the resonator profile.

Parameters:

noisedensitytuple, optional: If not given the first trace is assumed to be so far off resonance that it is just noise.
nfft: int, optional: The length of the fft to be used, zero padded if requred, default is 1000.
threshold: int, optional: The multiples above the noise a single must be to not be excluded, default is 2.

Returns:

prof_data: np.ndarray: The resonator profile, give in nutation frequency (GHz)
prof_frqs: np.ndarray: The frequency axis in GHz

Parameters:

fit(f_diff_threshold=2, cores=1, multi_mode=False, fc_guess=None)¶

Fit the resonator profile with a sum of lorentzians.

Parameters:

f_diff_thresholdfloat, optional: The difference between two peaks at which they will be merged into one, by default 0.03

plot(fieldsweep=None, axs=None, fig=None)¶

plot.

Parameters:

fieldsweepFieldSweepAnalysis, optional: Overlays the FieldSweep if provided, by default None
axsmatplotlib.Axes, optional: Axes to plot on, by default None
figmatplotlib.Figure, optional: Figure to plot on, by default None

Returns: