Fix GLOWS L3a and L3b variable dimension sizing with fill padding

[leowerneck]

Change Summary

Closes #158

Overview

Fixes inconsistent GLOWS L3a and L3b CDF dimensions by padding L3a spin-angle variables to 90 bins and L3b used_l3a to 50 entries. Padding is removed when L3a files are read for downstream processing.

File Changes

• Added L3a lightcurve padding using the appropriate floating-point and raw-histogram fill values.
• Trimmed padded L3a arrays using the valid bin count when converting CDF data for L3b processing.
• Padded L3b used_l3a with empty strings.
• Updated unit tests to verify fixed dimensions and fill values.

Testing

Ran 15 focused GLOWS L3a/L3b tests successfully, including model creation, CDF conversion, and processor behavior.

[Copilot]

Pull request overview

Fixes GLOWS CDF dimension consistency by padding L3a and L3b variable-length arrays while trimming L3a padding during downstream reads.

Changes:

• Pads L3a lightcurve arrays to 90 bins with type-appropriate fill values.
• Pads L3b used_l3a to 50 entries.
• Updates tests for fixed dimensions and padding values.

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated no comments.

File	Description
imap_l3_processing/glows/l3a/utils.py	Adds L3a padding and downstream trimming.
imap_l3_processing/glows/l3bc/models.py	Pads and bounds L3b used_l3a.
tests/glows/l3a/test_utils.py	Verifies L3a dimensions and fill values.
tests/glows/l3bc/test_models.py	Verifies L3b filename padding.

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[pleasant-menlo]

There is logic downstream that converts np.nan and masked arrays to the correct fill value. Can this function be rewritten to utilize masked arrays for integer type data and np.nans for float type data?

• Sebastian and Karn

[leowerneck]

@pleasant-menlo Good catch, thank you for pointing this out! Could you please review the latest commit?