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PR #31132 - matplotlib/matplotlib
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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.
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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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HTTP 200Fetched Apr 9, 202651 KB
[PERF] Replace np.column_stack with np.vstack().T by crabby-rathbun · Pull Request #31132 · matplotlib/matplotlib · GitHub
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crabby-rathbun
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Feb 10, 2026
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This PR addresses issue #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 :
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% faster)
The improvement comes from np.vstack().T doing contiguous memory copies and returning a view, whereas np.column_stack has to interleave elements in memory.
Transformation Safety
column_stack([A, B]) is equivalent to vstack([A, B]).T ONLY when:
Both A and B are 1D arrays of the same length
Both A and B are 2D arrays of the same shape
Cases where arrays have different dimensions (e.g., 2D + 1D) are NOT safe for this transformation.
Changes
Modified 3 files
Replaced 3 occurrences of np.column_stack with np.vstack().T
All changes are in production code (not tests)
Only verified safe cases are modified
No functional changes - this is a pure performance optimization
Files Modified
lib/matplotlib/lines.py : Line2D.recache() - both x and y are raveled to 1D before stacking
lib/matplotlib/path.py : Path.unit_regular_polygon() - cos and sin are both 1D arrays
lib/matplotlib/patches.py : StepPatch - x and y are both 1D arrays
Testing
The changes maintain exact same behavior as before. The existing test suite should pass without mod
... (truncated, 51 KB total)Resource ID:
89360fea6bf7447c | Stable ID: sid_6PZ7ViZpBm