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fixed MCMC for multiple visits, applied "uncmulti_val" to error, added model "model_rowshift" #28

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K-Angelique-Kahle
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@K-Angelique-Kahle K-Angelique-Kahle commented Jan 10, 2024

MCMC for multiple visits (applied these changes also for nested sampling, but may not be sufficient to fix nested):

Files: mcmc , nested , util
What? util.format_params_for_Model now alters the parameters of all visits in updated_params. Therefore, model.fit now considers all visits.


applied uncmulti_val to error

Files: mcmc, nested
What? uncmulti_val was previously only applied during sampling, but the final uncmulti_val was not applied on the errors. It is now.


added model model_rowshift

Files: fit_par, obs_par, plots, formatter, functions, model_rowshift (new), read_data, util, s20_extract
What? Added new systematics model that may be needed for fast scans of bright stars. In s20_extract, it measures the vertical (rows) position of the spectrum of all exposures (based on the first non-destructive exposure) with respect to the spectrum-position of the first exposure in the data (rowshift). This rowshift is stored in meta and some diagnostics plots can be saved if needed. In s30, the new function "model_rowshift" fits linear slopes as a function of rowshift to the forward and reverse scans in the data.
I tried to leave the runtime of PACMAN mostly unchanged if the function is not used.

@sebastian-zieba
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Hi @K-Angelique-Kahle
I am finally checking out your PR! Thanks for that! Could you also add some short explanation of your new model in the systematics section of the documentation? I would be this file: https://github.com/sebastian-zieba/PACMAN/blob/master/docs/source/models.rst
I think right before astrophysical models (at the very end of the Instrument Systematics) would be best. Just a brief description of what it does, a reference, and which parameters are needed would be great.

@K-Angelique-Kahle
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Hi @sebastian-zieba
I finally managed to add the two lines of description you asked for, sorry for the delay! The paper reference explains the idea of the method, the actual implementation differs slightly.

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