2598 bug lo l2 bootstrap correction

[subagonsouth]

Change Summary

Overview

Fixes a few issues with the sputtering and bootstrap corrections.
Also updates the hydrogen geometric factors to a file from Fatemeh.

Fixes to sputtering:

• Only apply sputtering correction where valid values in sputtering are found.
• Set values in numpy arrays using numpy indexing rather than xarray.

Fixes to boostrap:

• Only set values where boostrap is valid
• Fix where that was converting NaNs to zeros

Closes: #2598

[Copilot]

Pull request overview

This PR fixes issues with sputtering and bootstrap corrections in the Lo L2 processing pipeline and updates hydrogen geometric factors with new data from Fatemeh.

Changes:

• Fixed sputtering correction to only apply where valid oxygen intensity values exist, using conditional logic with xr.where
• Fixed bootstrap correction by moving the valid_bootstrap mask definition before its usage and applying corrections conditionally
• Updated numpy array assignment to use .values for proper indexing
• Updated hydrogen geometric factor data with new energy values and uncertainties

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.

File	Description
imap_processing/lo/l2/lo_l2.py	Fixed sputtering and bootstrap corrections to handle invalid/NaN values properly using conditional masking and xr.where
imap_processing/tests/lo/test_lo_l2.py	Updated expected hydrogen energy values to match new geometric factor data
imap_processing/lo/ancillary_data/imap_lo_hydrogen-geometric-factor_v001.csv	Updated hydrogen geometric factors with new center energies, uncertainties, and geometric factor values

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[Copilot]

In the false branch of the xr.where for sputter_corrected_intensity_var, the code returns the statistical uncertainty instead of its square (variance). Since sputter_corrected_intensity_var should contain variances (as indicated by the name and the fact that it's square-rooted on line 1093), this should be "small_dataset['ena_intensity_stat_uncert'] ** 2" to maintain consistency.

Suggested change

	small_dataset["ena_intensity_stat_uncert"],
	small_dataset["ena_intensity_stat_uncert"] ** 2,

[Copilot]

In equation 13 (lines 1081-1087), when j_o_prime_valid is True, the code divides by small_dataset["ena_intensity"] which could be zero or near-zero, potentially causing division by zero errors. Consider adding a check to ensure small_dataset["ena_intensity"] is non-zero before performing the division, or use a small epsilon value to avoid division by zero.

Suggested change

	sputter_corrected_intensity_sys_err = xr.where(
	j_o_prime_valid,
	sputter_corrected_intensity
	/ small_dataset["ena_intensity"]
	# Protect against division by zero in small_dataset["ena_intensity"]
	ena_intensity = small_dataset["ena_intensity"]
	safe_ena_intensity = xr.where(ena_intensity == 0, np.nan, ena_intensity)
	sputter_corrected_intensity_sys_err = xr.where(
	j_o_prime_valid,
	sputter_corrected_intensity
	/ safe_ena_intensity

[greglucas]

Nice work tracking all of this down!

Minor comment that I discussed in-person about whether we should switch to working on numpy arrays right at the beginning of these corrections rather than calling all these xr.where() with multiple cases it would be something like ena_intensity_np = data["ena_intensity"].values; ena_intensity_np[valid_mask] = ...