lincc-frameworks/notebooks_lf
Jul 2025 – Jul 2025
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
AstrophysicsData AnalysisData SimulationData VisualizationDocumentationJupyter Notebook
Mi Dai
PROFILE
Mi Dai
In July 2025, Ming Dai developed an end-to-end DP1 Object Simulation Notebook for the lincc-frameworks/notebooks_lf repository, focusing on astrophysics data analysis and simulation. Using Python and Jupyter Notebooks, Ming integrated TDAstro to simulate DP1 objects, incorporating observation logs, passband configuration, and SALT2-H17 light curve generation. The notebook included quality cuts, visualization, and parameter refinement for host galaxies and light curves, with comprehensive documentation and references to support reproducibility. Through four iterative commits, Ming scaffolded and stabilized the notebook, enabling reproducible prototyping and quality assurance for DP1 analyses, and demonstrating depth in scientific computing and data visualization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
1
Lines of code
1,594
Activity Months1
Work History
July 2025
4 Commits • 1 Features
Jul 1, 2025July 2025 — Lincc notebooks LF: Delivered an end-to-end DP1 Object Simulation Notebook using TDAstro in lincc-frameworks/notebooks_lf. The notebook supports DP1 object simulation with observation logs, passband setup, SALT2-H17 light curve generation, quality cuts, visualization, and refined host-galaxy/light-curve parameters, with integrated references. Work advanced through four commits that scaffolded and stabilized the notebook, enabling reproducible DP1 scenario prototyping and QA readiness.
4 Commits • 1 Features
Jul 1, 2025July 2025 — Lincc notebooks LF: Delivered an end-to-end DP1 Object Simulation Notebook using TDAstro in lincc-frameworks/notebooks_lf. The notebook supports DP1 object simulation with observation logs, passband setup, SALT2-H17 light curve generation, quality cuts, visualization, and refined host-galaxy/light-curve parameters, with integrated references. Work advanced through four commits that scaffolded and stabilized the notebook, enabling reproducible DP1 scenario prototyping and QA readiness.
July 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture85.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
AstrophysicsData AnalysisData SimulationData VisualizationDocumentationJupyter NotebookJupyter NotebooksPythonScientific Computing
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