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 for the lsst-sitcom/notebooks_vandv repository, focusing on Fourier analysis concepts such as FFT and DFT. Using Python and Jupyter Notebooks, he created a tool that visualizes the effects of noise, sampling rate, and frequency content on FFT results, making complex signal processing concepts accessible for teaching and exploration. His approach emphasized maintainability by adding type annotations and improving code readability through clarified comments and the introduction of amplitude variables. The work demonstrated depth in scientific computing and data visualization, resulting in a practical, well-annotated resource for both learners and instructors.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
438
Activity Months1
Your Network
16 peopleShared Repositories
16
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
Repositories Contributed To
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