- psfr version: latest
- Python version: 3.9
- Operating System: Linux
Description
In the psf error map calculation, the expected noise level (i.e. sqrt(error_map_list[i])) is subtracted from the residuals (lines 358-360).
Here are the lines of code I am talking about:
# subtract expected noise level
if error_map_list[i] is not None:
residuals -= np.sqrt(error_map_list[i])
If I understand correctly, the goal is to avoid double counting the errors, i.e. separate the "expected gaussian+poisson noise" to the one which comes from a true difference between the star and the estimated psf, the latter being the only one which should be taken into account in the psf_error_map. Is it correct ? If so, why are we subtracting simply instead of quadratically substracting ? I am not sure of the right answer, I just wanted to be sure we are consistent.
Description
In the psf error map calculation, the expected noise level (i.e.
sqrt(error_map_list[i])) is subtracted from the residuals (lines 358-360).Here are the lines of code I am talking about:
If I understand correctly, the goal is to avoid double counting the errors, i.e. separate the "expected gaussian+poisson noise" to the one which comes from a true difference between the star and the estimated psf, the latter being the only one which should be taken into account in the psf_error_map. Is it correct ? If so, why are we subtracting simply instead of quadratically substracting ? I am not sure of the right answer, I just wanted to be sure we are consistent.