ibs-lab/cedalion
Mar 2025 – Jun 2025
3 Months active
Languages Used
PythonJupyter Notebook
Technical Skills
Code CleanupData AnalysisData VisualizationDebuggingLinear AlgebraMatplotlib
David Boas
PROFILE
David Boas
David Boas developed advanced data visualization and analysis features for the ibs-lab/cedalion repository, focusing on scientific computing workflows in Python and Jupyter Notebook. Over three months, he enhanced plotting tools to support multi-subject and multi-run time series, introduced animated and multi-view 3D scalp and brain visualizations, and improved GUI usability for navigating complex datasets. His work included robust code cleanup, expanded unit testing, and the integration of spatial and measurement regularization into optimization pipelines. These contributions improved code maintainability, visualization clarity, and data processing flexibility, enabling more efficient cross-subject analysis and reproducible research in neuroscience applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
8
Lines of code
669
Activity Months3
Your Network
54 people
Work History
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 performance highlights for ibs-lab/cedalion: Implemented multi-subject and multi-run support for time series plotting, enabling visualization of BU-pipeline processed data across multiple subjects and runs. Updated data ingestion to parse pkl files containing a list of recording containers (multi-subject/multi-run format) and extended the GUI with subject and run selectors to simplify navigation. Linked work to commit 412d4402ec66c0f6214f49468080d36c39b73ed4 with message 'faciliate time series plots from files processed by the BU pipeline (#108)'. No major bugs documented this month. Impact: broader data coverage, faster insight, and improved data-driven decision making.
1 Commits • 1 Features
Jun 1, 2025June 2025 performance highlights for ibs-lab/cedalion: Implemented multi-subject and multi-run support for time series plotting, enabling visualization of BU-pipeline processed data across multiple subjects and runs. Updated data ingestion to parse pkl files containing a list of recording containers (multi-subject/multi-run format) and extended the GUI with subject and run selectors to simplify navigation. Linked work to commit 412d4402ec66c0f6214f49468080d36c39b73ed4 with message 'faciliate time series plots from files processed by the BU pipeline (#108)'. No major bugs documented this month. Impact: broader data coverage, faster insight, and improved data-driven decision making.
June 2025
April 2025
4 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for ibs-lab/cedalion focusing on visualization feature delivery and impact. Key features delivered include Scalp_plot enhancements with custom colormap, configurable colorbar labels, and visibility control; Scalp_plot_gif.py to generate animated scalp topography visuals with configurable frame ranges and options; surface_multi_view.py for multi-view 3D brain/scalp visualizations with static or GIF outputs; notebook demos demonstrating new features to accelerate adoption. No major bugs reported this period; the work improves visualization clarity, reproducibility, and user onboarding, driving faster insight generation and better data storytelling. Technologies demonstrated include Python scripting, data visualization pipelines, animation workflows, and Jupyter notebook integration for reproducible demos.
April 2025
4 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for ibs-lab/cedalion focusing on visualization feature delivery and impact. Key features delivered include Scalp_plot enhancements with custom colormap, configurable colorbar labels, and visibility control; Scalp_plot_gif.py to generate animated scalp topography visuals with configurable frame ranges and options; surface_multi_view.py for multi-view 3D brain/scalp visualizations with static or GIF outputs; notebook demos demonstrating new features to accelerate adoption. No major bugs reported this period; the work improves visualization clarity, reproducibility, and user onboarding, driving faster insight generation and better data storytelling. Technologies demonstrated include Python scripting, data visualization pipelines, animation workflows, and Jupyter notebook integration for reproducible demos.
March 2025
4 Commits • 3 Features
Mar 1, 2025Month: 2025-03 | This period focused on enhancing data visualization, strengthening solver robustness, and improving production code quality for ibs-lab/cedalion. Key outcomes include more usable plots, a more robust optimization pipeline with spatial and measurement regularization, and significantly cleaner production code with guarded logging. These changes improve user effectiveness, reduce risk of solver failures in production, and ease long-term maintenance.
4 Commits • 3 Features
Mar 1, 2025Month: 2025-03 | This period focused on enhancing data visualization, strengthening solver robustness, and improving production code quality for ibs-lab/cedalion. Key outcomes include more usable plots, a more robust optimization pipeline with spatial and measurement regularization, and significantly cleaner production code with guarded logging. These changes improve user effectiveness, reduce risk of solver failures in production, and ease long-term maintenance.
March 2025
Activity
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Quality Metrics
Correctness92.2%
Maintainability91.2%
Architecture87.8%
Performance84.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
3D RenderingCode CleanupData AnalysisData ProcessingData VisualizationDebuggingGUI DevelopmentImage ProcessingLinear AlgebraMatplotlibNumerical MethodsPlotting LibrariesPythonPython DevelopmentScientific Computing
Repositories Contributed To
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