Check denominator computation performance
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esssans
- Dominant language
- Python
- Stars
- 1
- Forks
- 3
- Avg merge
- 2d 11h
- Merged PRs (30d)
- 17
Description
Computing a denominator in the loki direct beam workflow uses a lot of memory.
Probably because of the 500_000 pixels * 200 wavelength bins, plus the 50 wavelength bands.
We should however revisit, to see if we are doing something wrong (or in the wrong order).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the Loki direct beam workflow and the denominator computation. Measure memory use around the 500,000-pixel, 200-bin, and 50-band calculation, then inspect whether the operation order creates unnecessary intermediate data. Done means the computation uses substantially less memory while preserving its results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100