CosmoStat / CosmoStat/shapepipe

Merge shape + photometry masks by intersection; build N(x)/randoms mask

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Dominant language
Python
Stars
18
Forks
14
Avg merge
8h 40m
Merged PRs (30d)
10

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

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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.

Assessment

Tech stack
python
Domain
data
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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