Apply dynamic background bonus to rolled "n_stars"

[jeanconn]

Description

Apply dynamic background bonus to rolled "n_stars".

The catalogs in roll optimization were correctly carrying forward any dynamic background options (dyn_bgd_n_faint, dyn_bgd_dt_ccd) but these options were not applied to the optimized "n_stars". This PR fixes that for consistency.

Interface impacts

n_stars in the roll optimization table should now match the "final" catalog guide_count used in operations, if the same input kwargs for proseco are used.

Testing

Unit tests

• Mac with a recent ska3-flight-latest

(ska3-flight-latest) flame:sparkles jean$ git rev-parse HEAD
ab4628e8d2f629d6c42d9d1af60f0064c9e7261c
(ska3-flight-latest) flame:sparkles jean$ pytest
=============================================== test session starts ===============================================
platform darwin -- Python 3.11.8, pytest-8.0.2, pluggy-1.4.0
PyQt5 5.15.9 -- Qt runtime 5.15.8 -- Qt compiled 5.15.8
rootdir: /Users/jean/git
configfile: pytest.ini
plugins: astropy-0.11.0, qt-4.4.0, cov-5.0.0, timeout-2.2.0, remotedata-0.4.1, anyio-4.3.0, filter-subpackage-0.2.0, doctestplus-1.2.1, astropy-header-0.2.2, hypothesis-6.112.0, arraydiff-0.6.1, mock-3.14.0
collected 104 items                                                                                               

sparkles/tests/test_checks.py ............................................................................  [ 73%]
sparkles/tests/test_find_er_catalog.py .....                                                                [ 77%]
sparkles/tests/test_review.py ...................                                                           [ 96%]
sparkles/tests/test_yoshi.py ....                                                                           [100%]

============================================== 104 passed in 28.53s

Independent check of unit tests by [REVIEWER NAME]

• [PLATFORM]:

Functional tests

New unit test added.

[taldcroft]

Awesome! The only nit I could find is that np.allclose() does not require np.array() casting, you can just pass in lists and it works just fine. No need to fix that but remember for the future.