When trying to fit the DOAS calibration to camera optical depths there are issues if requesting a 2nd order polynomial fit. Pyplis uses scipy.optimize.curve_fit and this doesn't seem to do a good job if the initial guess (which is provided by pyplis) isn't close to the actual parameters. Specifically, the x^2 term just doesn't change at all, so the line remains straight. This is probably to do with the input guesses/bounds which pyplis passes to curve_fit. We can pass our own guesses if we generate them in PyplisWorker, or it may be easier to to our own fit and then update the pyplis DoasCalibData object manually.
When trying to fit the DOAS calibration to camera optical depths there are issues if requesting a 2nd order polynomial fit. Pyplis uses scipy.optimize.curve_fit and this doesn't seem to do a good job if the initial guess (which is provided by pyplis) isn't close to the actual parameters. Specifically, the x^2 term just doesn't change at all, so the line remains straight. This is probably to do with the input guesses/bounds which pyplis passes to curve_fit. We can pass our own guesses if we generate them in PyplisWorker, or it may be easier to to our own fit and then update the pyplis DoasCalibData object manually.