All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- readme.ipynb to generate images shown in README.md.
- Moved configuration from
setup.py
tosetup.cfg
- First pass at docs using
sphinx
guess.smooth()
no longer fails with data lengths too short to convolve.
- Added LinearSymmetricTransmissionLeakage model, and corresponding fitter, to use when the input signal couples directly to the output.
- Added frequency keyword to KerrFitter.kerr_coefficient_from_power
- Added
kerr_coefficient_from_power
method tokerr.KerrFitter
- Added properties
measurement_frequency
andmeasurement_data
tobackground.Known
- Updated documentation, README, and example notebooks.
- The default guessing function now handles data irregularly spaced in frequency.
- Harmonized some keyword arguments in
see.py
- Instead of causing an exception, errors on derived values (e.g. quality factors) are None when the parameter errors are None because the fit cannot estimate them.
crosshairs
keyword insee.real_and_imaginary
adds lines through origin.
- Updated example notebooks.
- Typo in shunt.KerrShuntFitter.
- Methods in
base.ResonatorFitter
to evaluate the composite model and the background and foreground models.
- Renamed some options in
see.py
for consistency. - Re-organized and upgraded guessing functions.
- A module
guess.py
to consolidate functions related to initial value guesses.
- The
see.py
plotting functions can now plot the initial fit, and they can now create and return their own figure and axes. - Example notebooks updated to demonstrate new plotting abilities, including initial fit for debugging.
- The Reflection fitters should now work with the backgrounds that include an electrical delay.
- The MeasurementModelResonance object and associated method in
ResonatorFitter
.
- Version number corrected; minor typos
- Example notebooks reflect renaming.
- This changelog.
- Code in
kerr.py
used for fitting resonators measured with sufficiently high power that a Kerr-type nonlinearity is important. - Models
reflection.KerrReflection
andshunt.KerrShunt
and corresponding fitters that use the Kerr model. - Photon number calculations for both linear and Kerr nonlinear resonators in both shunt and reflection configurations.
- Example notebooks that demonstrate fitting with the Kerr model.
- Plotting function
see.triptych
that creates three plots. - Background model
Magnitude
with only free magnitude. - Method
base.initial_model_values
that evaluates the model with initial values, useful for debugging. - Example notebooks
basic.ipynb
andadvanced.ipynb
that demonstrate basic fitting and some more advanced techniques.
- The linear resonator model classes and fitters have been renamed:
Shunt
->LinearShunt
andShuntFitter
->LinearShuntFitter
Reflection
->LinearReflection
andReflectionFitter
->LinearReflectionFitter
SymmetricTransmission
->LinearSymmetricTransmission
- Most of the backgrounds have been renamed by their free parameters:
UnitNorm
->Phase
ComplexConstant
->MagnitudePhase
ConstantMagnitudeConstantDelay
->MagnitudePhaseDelay
LinearMagnitudeConstantDelay
->MagnitudeSlopeOffsetPhaseDelay
- A
lmfit.Parameters
object passed to a fitter on creation now updates the initial parameters, giving the user full control over initial values, bounds, and which parameters are varied in the fit. ResonatorFitter.fit
now overwrites the existing result instead of returning it.- Plotting functions now give the axes reasonable labels by default.
- Energy loss rates ("kappas") have been renamed, since kappa is used to mean various things in papers.
background.MagnitudeSlopeOffsetPhaseDelay
: magnitude_reference renamed magnitude_offsetResonatorFitter.evaluate_model
->model_values
One
,Phase
, andMagnitudePhase
model functions accepted numpy scalars but not floats.