Characterization - First Processes
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- Dominant language
- Python
- Stars
- 0
- Forks
- 3
- Avg merge
- 21h 35m
- Merged PRs (30d)
- 8
Description
1 - We need a cosine-weighted area map that corrects pixel area to solar surface area, so we can get the feature areas.
2 - Thresholding and LOS correction (no smoothing needed though).
3 - Extract individual features found during the IGM (Indexed Grown Mask) process.
4 - Get dB/dt by subtracting the magnetograms and then dividing by the time difference.
5 - Using the cosine-weighted area map and the dB/dt map, calculate the flux emergence rate, dΦ/dt, of each feature.
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 by locating the existing Indexed Grown Mask (IGM) process and magnetogram handling; the issue does not name files or tests. Trace how thresholding, line-of-sight correction, feature extraction, time differences, and area maps are currently represented, then define completion as producing a flux-emergence rate for each extracted feature.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100