scipy/scipy
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
Pythondata analysisdata sciencematrix operationsnumerical analysistesting
CJ Carey
PROFILE
Cj Carey
During December 2025, Perimosocordiae enhanced sparse matrix utilities in the scipy/scipy repository, focusing on robustness and compatibility improvements. They improved the handling of sparse.linalg.norm across multiple matrix formats by refining non-zero element counting and expanding test coverage to include a wide range of norm orders and edge cases. Their work also updated axis support criteria for the count_nonzero function, ensuring correctness and cross-format compatibility. Using Python and leveraging skills in data analysis, matrix operations, and numerical analysis, Perimosocordiae delivered a well-tested feature that increases the reliability of sparse operations and supports more robust scientific computing workflows across formats.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
79
Activity Months1
Your Network
173 peopleWork History
December 2025
2 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for scipy/scipy: Released Sparse Matrix Utilities Robustness and Compatibility Improvements. Enhanced sparse.linalg.norm handling across matrix formats with improved non-zero counting and expanded test coverage for a broad range of norm orders, including edge cases. Updated axis support criteria for count_nonzero across sparse formats to improve correctness and cross-format compatibility. The work increases reliability of sparse operations, enabling accurate scientific computing across formats and more robust downstream workflows. Commits included: 105ec0f46b15698f03e070ac40f205b0f4fc5bdf (Improve test coverage for sparse.linalg.norm and fix the broken cases) and fe554a55e52b8cff6e6138aad59e5725526e52a9 (TST: Update count_nonzero axis support criteria).
2 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for scipy/scipy: Released Sparse Matrix Utilities Robustness and Compatibility Improvements. Enhanced sparse.linalg.norm handling across matrix formats with improved non-zero counting and expanded test coverage for a broad range of norm orders, including edge cases. Updated axis support criteria for count_nonzero across sparse formats to improve correctness and cross-format compatibility. The work increases reliability of sparse operations, enabling accurate scientific computing across formats and more robust downstream workflows. Commits included: 105ec0f46b15698f03e070ac40f205b0f4fc5bdf (Improve test coverage for sparse.linalg.norm and fix the broken cases) and fe554a55e52b8cff6e6138aad59e5725526e52a9 (TST: Update count_nonzero axis support criteria).
December 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Pythondata analysisdata sciencematrix operationsnumerical analysistesting
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