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Fitting the energy calibration with the law d^2/(t-t0)^2 is the most appropriate way and leads to the best results.
However, the function is strongly peaked around t0 and can be unstable against initialization parameters (fit might not converge at all).
In sed.calibrate.energy "fit_energy_calibation" this control is actually implemented in a nice way, with a dictionary input to control not just initial value but also min, max and "lock" (whether the parameter is varied or not during the optimization).
It would be of great benefit to the user, and I think a relatively frequent use case, if this was explained in the documentation of sp.calibrate_energy_axis.
The text was updated successfully, but these errors were encountered:
I don't have much experience in calibrating other than the tutorial usage.
It would be great if you could write the short update to doc that you suggested. It can even be in this thread (just a code block/docs of the relevant section)
Fitting the energy calibration with the law d^2/(t-t0)^2 is the most appropriate way and leads to the best results.
However, the function is strongly peaked around t0 and can be unstable against initialization parameters (fit might not converge at all).
In sed.calibrate.energy "fit_energy_calibation" this control is actually implemented in a nice way, with a dictionary input to control not just initial value but also min, max and "lock" (whether the parameter is varied or not during the optimization).
It would be of great benefit to the user, and I think a relatively frequent use case, if this was explained in the documentation of sp.calibrate_energy_axis.
The text was updated successfully, but these errors were encountered: