uncscode/particula
Apr 2025 – Apr 2025
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Code CorrectionData AnalysisData VisualizationDocumentationJupyter NotebooksScientific Computing
wkchuang
PROFILE
Wkchuang
Worked on the uncscode/particula repository to streamline onboarding and improve simulation reliability by adding comprehensive Conda installation support and enhancing documentation across readme, setup, and tutorial materials. Addressed accuracy issues in Jupyter Notebooks by correcting a typo in the Chamber Forward Simulation and updating atmospheric temperature values in the Atmosphere Tutorial, ensuring scientific correctness. Standardized plot colors and improved documentation readability to present clearer data visualizations. Leveraged Python, Markdown, and Jupyter Notebooks to implement these changes, focusing on code correction, data analysis, and scientific computing. The updates improved accessibility for Conda users and reinforced the overall quality of the project.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
8Total
Bugs
1
Commits
8
Features
2
Lines of code
65
Activity Months1
Your Network
104 peopleShared Repositories
3
Work History
April 2025
8 Commits • 2 Features
Apr 1, 2025April 2025: Consolidated Conda installation support and enhanced documentation across readme, setup, and tutorials for uncscode/particula. Fixed notebook accuracy issues (typo in Chamber Forward Simulation; atmospheric temperature values in Atmosphere Tutorial) and improved notebook visuals with standardized colors and readability improvements. These changes streamline onboarding, improve simulation reliability, and present consistent visualizations, reinforcing product quality and developer productivity.
8 Commits • 2 Features
Apr 1, 2025April 2025: Consolidated Conda installation support and enhanced documentation across readme, setup, and tutorials for uncscode/particula. Fixed notebook accuracy issues (typo in Chamber Forward Simulation; atmospheric temperature values in Atmosphere Tutorial) and improved notebook visuals with standardized colors and readability improvements. These changes streamline onboarding, improve simulation reliability, and present consistent visualizations, reinforcing product quality and developer productivity.
April 2025
Activity
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Quality Metrics
Correctness97.6%
Maintainability97.6%
Architecture97.6%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
Code CorrectionData AnalysisData VisualizationDocumentationJupyter NotebooksScientific ComputingTypo Fixing
Repositories Contributed To
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