uncscode/particula
Apr 2025 – Apr 2025
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Code CorrectionData AnalysisData VisualizationDocumentationJupyter NotebooksScientific Computing
wkchuang
PROFILE
Wkchuang
Wenhao Chen enhanced the uncscode/particula repository by consolidating Conda installation support and refining documentation to streamline onboarding for new users. Using Python and Jupyter Notebooks, Wenhao corrected simulation accuracy issues by fixing a typo in the Chamber Forward Simulation and updating atmospheric temperature values in the Atmosphere Tutorial. He also standardized plot colors and improved documentation readability, ensuring consistent data visualization and clearer instructional materials. His work focused on code correction, data analysis, and scientific computing, resulting in more reliable simulations and a smoother setup process. These targeted improvements addressed both usability and technical accuracy within a short timeframe.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
8Total
Bugs
1
Commits
8
Features
2
Lines of code
65
Activity Months1
Your Network
76 peopleShared Repositories
2
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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