Fix GLOWS L2 - add per-bin zero handling for flux calculations

[vmartinez-cu]

This pull request handles zero exposure values in the DailyLightcurve class to prevent division by zero errors and adds a corresponding test to ensure correct behavior.

Closes #2370

[Copilot]

Pull request overview

This PR updates GLOWS L2 DailyLightcurve flux/uncertainty computation to avoid divide-by-zero when exposure is zero, and adds a regression test around zero-exposure behavior.

Changes:

• Adds a guard to skip flux/uncertainty division when exposure is zero.
• Adds a unit test ensuring zero exposure produces zero flux/uncertainty without triggering NumPy divide/invalid warnings.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.

File	Description
imap_processing/glows/l2/glows_l2_data.py	Changes the flux/uncertainty calculation guard to avoid division when exposure is zero.
imap_processing/tests/glows/test_glows_l2_data.py	Adds a regression test for all-zero exposure values.

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[Copilot]

The new guard self.exposure_times[0] > 0 only checks the first element and then divides the entire array. This doesn’t implement per-bin zero handling (as requested in #2370 / PR title) and would still divide by zero if exposure_times ever contains a mix of zeros and non-zeros. Consider using element-wise division (e.g., np.divide(..., out=..., where=self.exposure_times > 0)) so bins with zero exposure remain 0 without relying on the “uniform across bins” assumption.

Suggested change

	if len(self.exposure_times) != 0 and self.exposure_times[0] > 0:
	self.photon_flux = self.raw_histograms / self.exposure_times
	self.flux_uncertainties = raw_uncertainties / self.exposure_times
	if self.exposure_times.size > 0:
	exposure_mask = self.exposure_times > 0
	np.divide(
	self.raw_histograms,
	self.exposure_times,
	out=self.photon_flux,
	where=exposure_mask,
	)
	np.divide(
	raw_uncertainties,
	self.exposure_times,
	out=self.flux_uncertainties,
	where=exposure_mask,
	)

[vmartinez-cu]

All bins have the same exposure time so just the first one can be checked

[Copilot]

This test only covers the case where all exposure values are zero. Since the underlying bug report/PR title calls for per-bin zero handling, add a test case that exercises mixed exposure values (some bins zero, others non-zero) once the implementation supports it, to ensure only the zero-exposure bins produce zero flux/uncertainty and no divide-by-zero occurs.

Suggested change

	@pytest.mark.xfail(
	reason=(
	"Per-bin zero exposure handling not yet implemented. "
	"Once supported, construct a dataset with mixed exposure values "
	"(some bins zero, others non-zero) and assert that only the "
	"zero-exposure bins have zero flux/uncertainty with no divide-by-zero."
	)
	)
	def test_mixed_zero_exposure_values(l1b_dataset, mock_ecliptic_bin_centers):
	"""Placeholder for mixed per-bin exposure test.
	This test should be updated once the pipeline supports per-bin zero
	exposure handling. The intended behavior is:
	* Bins with zero exposure time produce zero photon_flux and
	flux_uncertainties.
	* Bins with non-zero exposure time retain finite, non-NaN values.
	* No divide-by-zero or invalid floating-point operations occur even when
	using np.errstate(divide="raise", invalid="raise").
	"""
	pytest.xfail(
	"TODO: implement mixed per-bin exposure test when exposure can vary by bin."
	)

[vmartinez-cu]

All bins have the same exposure time so if one is zero all will be zero

[tech3371]

minor requests but looks great. That was so quick! Nice!

[maxinelasp]

Looks good, thanks Veronica!

[vmartinez-cu]

@maxinelasp What should happen if these conditions aren't met. Should an error be raised or should processing proceed?