scipy/scipy
Nov 2025 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
Pythondocumentationdata analysisnumerical methodsscientific computingstatistical analysis
AdrianRasoOnGit
PROFILE
Adrianrasoongit
Adrián Raso contributed to the scipy/scipy repository by enhancing both documentation and core statistical routines using Python and numerical methods. He clarified the shape parameter for scipy.sparse.random_array, aligning documentation with actual API behavior to reduce user confusion. Adrián improved the numerical accuracy of the stats.pmean function for small p values by implementing a linearized approximation, and addressed edge cases in multiscale_graphcorr by fixing errors with zero-distance matrices. He also expanded documentation for sh_legendre, adding practical examples. His work demonstrated careful attention to regression testing and documentation consistency, resulting in more robust, reliable, and user-friendly scientific computing tools.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
2
Lines of code
131
Activity Months2
Your Network
209 peopleWork History
January 2026
3 Commits • 1 Features
Jan 1, 2026January 2026 contributions to scipy/scipy focused on numerical robustness, regression testing, and documentation. Key outcomes include improved numerical accuracy for stats.pmean at small p values, robust handling of zero-distance matrices in multiscale_graphcorr, and enhanced sh_legendre documentation with an Examples section. All changes include added tests to prevent regressions and ensure correctness across edge cases, improving reliability for users relying on statistical routines.
3 Commits • 1 Features
Jan 1, 2026January 2026 contributions to scipy/scipy focused on numerical robustness, regression testing, and documentation. Key outcomes include improved numerical accuracy for stats.pmean at small p values, robust handling of zero-distance matrices in multiscale_graphcorr, and enhanced sh_legendre documentation with an Examples section. All changes include added tests to prevent regressions and ensure correctness across edge cases, improving reliability for users relying on statistical routines.
January 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025Month 2025-11 focused on improving documentation quality for SciPy, with a targeted clarification of the random_array shape parameter in scipy.sparse to reduce misuse and user questions. This work enhances API clarity and aligns docs with actual behavior, contributing to better developer experience and lower support overhead.
November 2025
1 Commits • 1 Features
Nov 1, 2025Month 2025-11 focused on improving documentation quality for SciPy, with a targeted clarification of the random_array shape parameter in scipy.sparse to reduce misuse and user questions. This work enhances API clarity and aligns docs with actual behavior, contributing to better developer experience and lower support overhead.
Activity
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Quality Metrics
Correctness100.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Pythondata analysisdocumentationnumerical methodsscientific computingstatistical analysisstatistical modelingtesting
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