cositools/cosipy
Apr 2026 – Jun 2026
3 Months active
Languages Used
Jupyter NotebookPythonYAMLreStructuredText
Technical Skills
Jupyter Notebook usagePythonPython developmentPython programmingdata analysisdata processing
Jeremy Buhler
PROFILE
Jeremy Buhler
Contributed to the cositools/cosipy repository over three months, delivering eight features and resolving critical bugs to enhance spacecraft data processing workflows. Focused on performance optimization, data integrity, and reproducibility, the work included refactoring Python code for faster data paths, standardizing orientation and detector response data formats, and improving polarization handling. Leveraged Python, Jupyter Notebooks, and YAML for backend development, configuration management, and scientific computing. Enhanced documentation, expanded unit tests, and introduced new visualization options for model validation. These efforts improved throughput, reduced memory overhead, and strengthened onboarding resources, resulting in more robust and maintainable data analysis pipelines.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
25Total
Bugs
2
Commits
25
Features
8
Lines of code
2,077
Activity Months3
Your Network
52 peopleShared Repositories
35
Abhijeet NardeleMember
Koothodil Abhijith AugustintineMember
abhijeet nardeleMember
Alberto SciaccalugaMember
Andreas ZoglauerMember
Ashwin AravindarajMember
Gus ThomasMember
Christopher M. KarwinMember
Christopher M. KarwinMember
Work History
June 2026
6 Commits • 3 Features
Jun 1, 2026Month 2026-06: Delivered key features and robustness improvements in cosipy with a clear focus on performance, validation, and diagnostics. Implemented major enhancements to instrument response and polarization processing for faster data paths and fewer redundant checks, along with test-driven polish (test figure management and warning suppression). Introduced Visualization enhancements for model injection to aid validation (spectrum and PsiChi plots). Expanded documentation and tests for floating-point precision mapping and source injector visuals to improve correctness and maintainability. Overall, these efforts reduced processing time, improved stability, and provided stronger validation signals for analysts and developers.
6 Commits • 3 Features
Jun 1, 2026Month 2026-06: Delivered key features and robustness improvements in cosipy with a clear focus on performance, validation, and diagnostics. Implemented major enhancements to instrument response and polarization processing for faster data paths and fewer redundant checks, along with test-driven polish (test figure management and warning suppression). Introduced Visualization enhancements for model injection to aid validation (spectrum and PsiChi plots). Expanded documentation and tests for floating-point precision mapping and source injector visuals to improve correctness and maintainability. Overall, these efforts reduced processing time, improved stability, and provided stronger validation signals for analysts and developers.
June 2026
May 2026
11 Commits • 3 Features
May 1, 2026May 2026 achieved a robust data-path standardization across cosipy deployments, migrating orientation and detector response data to .fits, and redirecting legacy paths to the correct DC release trees. Implemented YAML patching for ori files to YAML to fix light_curve breaks, updated tutorials and data references to reflect new paths and polarization data versions, and regenerated tutorial outputs to reduce error messages. Enhanced detector polarization handling by allowing responses to carry their own conventions and hardening RspConverter naming. Resolved code stability issues, including a merge conflict in photon_types.py, and cleaned up references to non-DC4 data across API docs and notebooks, improving reproducibility and reliability.
May 2026
11 Commits • 3 Features
May 1, 2026May 2026 achieved a robust data-path standardization across cosipy deployments, migrating orientation and detector response data to .fits, and redirecting legacy paths to the correct DC release trees. Implemented YAML patching for ori files to YAML to fix light_curve breaks, updated tutorials and data references to reflect new paths and polarization data versions, and regenerated tutorial outputs to reduce error messages. Enhanced detector polarization handling by allowing responses to carry their own conventions and hardening RspConverter naming. Resolved code stability issues, including a merge conflict in photon_types.py, and cleaned up references to non-DC4 data across API docs and notebooks, improving reproducibility and reliability.
April 2026
8 Commits • 2 Features
Apr 1, 2026Month: 2026-04 – The cosipy repository saw a focused set of performance improvements, stability fixes, and code quality enhancements across spacecraft data processing workflows. The changes delivered measurable business value by increasing throughput, reducing memory overhead, and stabilizing tutorials and notebooks used for onboarding and verification.
8 Commits • 2 Features
Apr 1, 2026Month: 2026-04 – The cosipy repository saw a focused set of performance improvements, stability fixes, and code quality enhancements across spacecraft data processing workflows. The changes delivered measurable business value by increasing throughput, reducing memory overhead, and stabilizing tutorials and notebooks used for onboarding and verification.
April 2026
Activity
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Quality Metrics
Correctness95.2%
Maintainability88.8%
Architecture88.8%
Performance90.6%
AI Usage21.6%
Skills & Technologies
Programming Languages
Jupyter NotebookPythonYAMLreStructuredText
Technical Skills
API designAPI developmentJupyter Notebook usageJupyter NotebooksPythonPython developmentPython programmingPython scriptingbackend developmentconfiguration managementdata analysisdata handlingdata integritydata managementdata processing
Repositories Contributed To
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