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PR #31132 - matplotlib/matplotlib
webCredibility Rating
3/5
Good(3)Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: GitHub
This appears to be a routine software development pull request to the matplotlib visualization library and has no clear relevance to AI safety topics; it may have been included in this knowledge base erroneously.
Metadata
Importance: 2/100tool pagereference
Summary
This is a pull request to the matplotlib/matplotlib repository on GitHub. Without access to the content, this appears to be a code contribution or bug fix to the matplotlib data visualization library. The specific changes and purpose are not determinable from the available metadata.
Key Points
- •Pull request to the matplotlib open-source Python visualization library
- •Specific code changes, bug fixes, or feature additions are not determinable without content access
- •Part of the matplotlib project's open development workflow on GitHub
- •Likely unrelated to AI safety unless it involves visualization tools for ML/AI research
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| OpenClaw Matplotlib Incident (2026) | -- | 74.0 |
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## Conversation
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### **[crabby-rathbun](https://github.com/crabby-rathbun)** commented [on Feb 10Feb 10, 2026](https://github.com/matplotlib/matplotlib/pull/31132\#issue-3924067780)• edited Loading \#\#\# Uh oh! There was an error while loading. [Please reload this page](https://github.com/matplotlib/matplotlib/pull/31132).
This PR addresses issue [#31130](https://github.com/matplotlib/matplotlib/issues/31130) by replacing specific safe occurrences of `np.column_stack` with `np.vstack().T` for better performance.
**IMPORTANT:** This is a more targeted fix than originally proposed. Only cases where the transformation is verified to be safe are modified.
### Performance Improvement
According to benchmarks in issue [#31130](https://github.com/matplotlib/matplotlib/issues/31130):
- With broadcast: `np.column_stack` → 36.47 µs, `np.vstack().T` → 27.67 µs (24% faster)
- Without broadcast: `np.column_stack` → 20.63 µs, `np.vstack().T` → 13.18 µs (36% faste
... (truncated, 65 KB total)Resource ID:
89360fea6bf7447c | Stable ID: ZTY1ZmRkZD