TonyKat007/Astral-trails
Jul 2025 – Jul 2025
1 Month active
Languages Used
Python
Technical Skills
API IntegrationData VisualizationMatplotlibNumPyScientific ComputingStreamlit
Ssssshlok
PROFILE
Ssssshlok
Developed enhanced radiation risk modeling and data visualization features for the Astral-trails repository, focusing on improving mission planning accuracy and interpretability of Monte Carlo simulation results. Leveraged Python, NumPy, and Matplotlib to expand the Radiation Risk Calculator with additional shielding materials and dose attenuation factors, enabling more precise dose estimation for space missions. Refined the user interface and visual outputs using Streamlit, updating plot layouts and labels for greater clarity. Maintained and harmonized calculation and plotting logic within app.py, ensuring consistency and maintainability across the codebase. The work addressed realistic scientific computing challenges in radiation modeling and data-driven decision support.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
2
Lines of code
156
Activity Months1
Your Network
17 peopleSame Organization
@iitk.ac.in6
Work History
July 2025
9 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for TonyKat007/Astral-trails focused on delivering enhanced radiation risk modeling and clearer visualization of Monte Carlo results. Key features implemented improved mission planning accuracy and data interpretability, with codebase improvements to app.py ensuring maintainability and consistency across calculations and plots. This period demonstrates strong Python engineering, data visualization, and domain modeling capabilities, with direct business value in safer, data-informed planning for space missions.
9 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for TonyKat007/Astral-trails focused on delivering enhanced radiation risk modeling and clearer visualization of Monte Carlo results. Key features implemented improved mission planning accuracy and data interpretability, with codebase improvements to app.py ensuring maintainability and consistency across calculations and plots. This period demonstrates strong Python engineering, data visualization, and domain modeling capabilities, with direct business value in safer, data-informed planning for space missions.
July 2025
Activity
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Quality Metrics
Correctness91.0%
Maintainability91.0%
Architecture75.6%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API IntegrationData VisualizationMatplotlibNumPyScientific ComputingStreamlitUI Development
Repositories Contributed To
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