Clarify interaction between center_data and fit_mean in LombScargle #17038

Description

The documentation regarding LombScargle's fit_mean, center_data, and model_parameters is a bit confusing to me. If I understand correctly, the formula in model_parameters should be something like

• The general case: y(t) = offset + y0 + (oscillating terms) where offset is defined as the weighted mean y.
• If center_data is False: offset is instead defined as being equal to zero; y0 is still fitted.
• If fit_mean is False: offset is still the mean y; y0 is not included in the model anymore and in fact not even returned by model_parameters(), i.e. the coefficient at index zero is y1, not y0.

If my understanding is correct, I would guess it may be enough to include such a clarification in the documentation of model_parameters() and point to that docs in the documentation for the fit_mean and center_data parameters.

Expected behavior

No response

How to Reproduce

N/A

Versions

Documentation for Astropy 6.1.3 (https://docs.astropy.org/en/v6.1.3/api/astropy.timeseries.LombScargle.html)