cositools/cosipy
Mar 2026 – Mar 2026
1 Month active
Languages Used
Python
Technical Skills
JupyterJupyter NotebooksPythonPython programmingdata analysisdata visualization
Juan Botha
PROFILE
Juan Botha
Worked on the cositools/cosipy repository to enhance the GRB spectral fitting workflow by refactoring and stabilizing Jupyter notebooks for improved clarity, correctness, and usability. Leveraged Python and Jupyter to streamline data processing, eliminating the need for an external grb_bkg dependency by reconstructing it from existing GRB and background data. This approach reduced redundancy and simplified the data workflow, supporting more reproducible analyses. Additional improvements included renaming and removing duplicate notebooks, refining file handling, and organizing resources for better maintainability. These updates accelerated onboarding for new users and minimized errors in plotting and data processing within scientific computing tasks.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
2
Lines of code
5,287
Activity Months1
Your Network
65 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
March 2026
5 Commits • 2 Features
Mar 1, 2026March 2026 — Delivered major enhancements to the GRB spectral fitting workflow in cosipy (cositools/cosipy). Key features include refactoring and stabilization of the GRB spectral fitting tutorials/notebooks for clarity, correctness, and usability, and a streamlined data workflow that eliminates an external grb_bkg dependency by constructing it from existing grb and background data. Housekeeping improvements included renaming the GRB notebook and removing a duplicate, improving maintainability. These changes reduce data dependencies and maintenance burden while accelerating end-to-end GRB analyses. Technologies demonstrated: Python, Jupyter notebooks, data processing, file handling, and code refactoring. Business value: faster onboarding for new users, fewer plotting/processing errors, more reproducible results, and a cleaner codebase.
5 Commits • 2 Features
Mar 1, 2026March 2026 — Delivered major enhancements to the GRB spectral fitting workflow in cosipy (cositools/cosipy). Key features include refactoring and stabilization of the GRB spectral fitting tutorials/notebooks for clarity, correctness, and usability, and a streamlined data workflow that eliminates an external grb_bkg dependency by constructing it from existing grb and background data. Housekeeping improvements included renaming the GRB notebook and removing a duplicate, improving maintainability. These changes reduce data dependencies and maintenance burden while accelerating end-to-end GRB analyses. Technologies demonstrated: Python, Jupyter notebooks, data processing, file handling, and code refactoring. Business value: faster onboarding for new users, fewer plotting/processing errors, more reproducible results, and a cleaner codebase.
March 2026
Activity
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Quality Metrics
Correctness88.0%
Maintainability84.0%
Architecture84.0%
Performance84.0%
AI Usage32.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
JupyterJupyter NotebooksPythonPython programmingdata analysisdata visualizationscientific computing
Repositories Contributed To
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