simonsobs / simonsobs/sotodlib
Should we interpolate TES bias values for missing samples in books?
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 19
- Forks
- 23
- Avg merge
- 1d 5h
- Merged PRs (30d)
- 14
Description
This is a question brought about from this discussion: https://github.com/simonsobs/daq-discussions/discussions/70
The bookbinder currently does not interpolate TES bias values for missing samples, so for samples that are gap-filled, the bias levels will read 0. We probably want to interpolate these like we do for detector data.
Contributor guide
No contributing guide indexed for this repository
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 with the bookbinder code that handles gap-filled samples, then compare its TES bias handling with the existing detector-data interpolation path. Confirm the desired behavior against discussion 70 and verify that missing-sample TES bias values are interpolated rather than left at zero.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-engineering
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100