Parallel computation
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- Dominant language
- Python
- Stars
- 394
- Forks
- 95
- Avg merge
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- Merged PRs (30d)
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Description
I retrieving the Visium spot from a mask.
I found the procedure a little bit slow.
Is it possible to parallelize the following code?
# Determine which spots are within the mask
points_within_mask = points_df.apply(lambda row: mask_geometry.contains(Point(row['x'], row['y'])), axis=1)
spots_in_mask = points_df[points_within_mask]
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Research direction
Start by locating the implementation corresponding to the shown points_df.apply call and inspect how the mask and spot data are represented. Measure the current operation, then define completion as equivalent spots_in_mask results with a demonstrated improvement from parallel computation; the issue names no test or file to run.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 28/100