lsst-sitcom/notebooks_vandv
Oct 2025 – Oct 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisData VisualizationInteractive PlottingJupyter NotebookJupyter NotebooksPython
Diego Hurtado
PROFILE
Diego Hurtado
Diego Hurtado developed an interactive educational notebook focused on Fourier transforms for the lsst-sitcom/notebooks_vandv repository. He designed the notebook to demonstrate FFT and DFT concepts, using Python and Jupyter Notebook to create visualizations that illustrate the effects of noise, sampling rate, and frequency content on signal analysis. Diego enhanced the codebase with type annotations and introduced amplitude variables, improving both maintainability and clarity for users. His work emphasized practical teaching applications, combining data analysis, scientific computing, and signal processing skills to deliver a well-annotated, user-friendly resource that supports both learning and reproducibility in computational signal analysis.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
438
Activity Months1
Work History
October 2025
3 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Fourier Transforms Notebook (FFT) - an interactive educational notebook in lsst-sitcom/notebooks_vandv that demonstrates FFT, DFT, and the efficient FFT algorithm with visualizations illustrating the effects of noise, sampling rate, and frequency content. The work included three commits: adding the FFT sample ipynb, introducing amplitude variables with commentary fixes, and adding type annotations. Focused on delivering a practical, teaching-oriented tool with maintainable, well-annotated code.
3 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Fourier Transforms Notebook (FFT) - an interactive educational notebook in lsst-sitcom/notebooks_vandv that demonstrates FFT, DFT, and the efficient FFT algorithm with visualizations illustrating the effects of noise, sampling rate, and frequency content. The work included three commits: adding the FFT sample ipynb, introducing amplitude variables with commentary fixes, and adding type annotations. Focused on delivering a practical, teaching-oriented tool with maintainable, well-annotated code.
October 2025
Activity
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Quality Metrics
Correctness96.6%
Maintainability93.4%
Architecture86.6%
Performance93.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisData VisualizationInteractive PlottingJupyter NotebookJupyter NotebooksPythonScientific ComputingSignal Processing
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