Revisit how individual cameras are co-added in specsim results
- Dominant language
- Python
- Stars
- 5
- Forks
- 10
- PR merge metrics
- No merged PRs in 30d
Description
Specsim returns per-camera vectors as well as co-added results. We currently only use the per-camera results in `quickbrick` and `quickgen`, but for SNR-level studies a co-add is still useful.
The coadd is currently throughput weighted:
```
obsflux = sum( thru[c] * resolution.dot(srcflux) ) / sum ( thru[c] )
```
where both sums are over cameras only.
Should we move to ivar weights, or even a full-blown spectro-perfect co-add (a la desi-doc-1056) ?
This is related to #1.
Contributor guide
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Research direction
Start by tracing how co-added results are used in quickbrick and quickgen, and review the per-camera vectors and current throughput-weighted calculation described in the issue. Compare the possible ivar-weighted and spectro-perfect approaches, including desi-doc-1056 and related issue #1. Done should mean an agreed co-add method is implemented and its SNR-study behavior is validated.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100