Faster implementation available for `vectorize()`
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- Dominant language
- Python
- Stars
- 394
- Forks
- 95
- Avg merge
- 4d 3h
- Merged PRs (30d)
- 7
Description
During the Ghent Hackathon (BioHackrXiv here) a faster implementation for vectorize() has been developed by @hey2homie: https://github.com/saeyslab/VIB_Hackathon_June_2024/blob/main/polygons/polygons_test.ipynb.
The implementation also fixes https://github.com/scverse/spatialdata/issues/583, but relies on opencv, which is a heavy dependency.
Still, we should see if that code could help improving the performance.
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.
Research direction
Start with the polygons_test.ipynb implementation linked in the issue, then locate the current vectorize() implementation in spatialdata. Compare its performance and behavior with the notebook approach, including the fix for issue #583 and the cost of adding opencv. Done means the performance tradeoff and dependency impact are evaluated and any improvement is verified against the reported behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, opencv, python
- Domain
- data, performance
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100