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
Developed an interactive educational notebook focused on Fourier transforms within the lsst-sitcom/notebooks_vandv repository, delivering a practical tool for teaching FFT and DFT concepts. The notebook, implemented in Python and Jupyter Notebook, features interactive visualizations that demonstrate the effects of noise, sampling rate, and frequency content on FFT results. The work emphasized maintainability by introducing type annotations and improving code readability through clarified comments and the addition of amplitude variables. Leveraging skills in data analysis, scientific computing, and signal processing, the developer created a resource that supports both exploration and instruction in fundamental signal processing techniques.
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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