Merge shape + photometry masks by intersection; build N(x)/randoms mask
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 48/100
Research direction
Start with the Paris meeting notes and inspect the existing ShapePipe N_point mask and the shape and PhotoPipe mask implementations. Determine where their intersection and the N_exp>=2, N_point>3, and CCD-failure N(x)/randoms masks should be produced. Done means these masks are built for clustering and void analyses, with the existing N_point logic incorporated.
Written by the indexing model from the issue text.
Description
Combine the shape and PhotoPipe masks by intersection. Build the N_exp>=2 and N_point>=3 masks (N_point already in ShapePipe). The CCD-failure-based N(x) / randoms mask (where galaxies are not, for clustering/void work) is the missing piece.
Context: Paris meeting notes
- Dominant language
- Python
- Stars
- 18
- Forks
- 14
- Avg merge
- 8h 40m
- Merged PRs (30d)
- 10
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.
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