mne-tools/mne-python
Jul 2025 – Feb 2026
2 Months active
Languages Used
Python
Technical Skills
3D RenderingData VisualizationScientific ComputingSoftware DevelopmentPythondata processing
Victor Férat
PROFILE
Victor Férat
Victor Ferat contributed to the mne-tools/mne-python repository by developing advanced visualization and data processing features for scientific computing workflows. He enhanced the MNE-Python Report with 3D source space and BEM visualizations, refining coordinate frames and view configurations to improve data interpretability for researchers. In addition, Victor introduced an optional reuse_seghead parameter to the scalp surface generation process, enabling more reliable and efficient segmentation file handling and reducing unnecessary recomputation. His work demonstrated strong proficiency in Python, 3D rendering, and data visualization, with careful attention to workflow stability, reproducibility, and collaborative code quality practices throughout the development process.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
516
Activity Months2
Your Network
51 peopleShared Repositories
51
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – Key achievements in mne-python focused on scalp surface generation reliability and efficiency. Delivered an optional reuse of segmentation files via a new reuse_seghead parameter for make_scalp_surfaces, addressing issues with stale assets and reducing recomputation. Fixed a bug in make_scalp_surfaces (Fixes make_scalp_surfaces (#13024)) with commit a5bf268a1a8645a6b4addc467dec70eb0ec26ce3, improving correctness and workflow stability. Overall impact: reduced risk of stale segmentation, faster generation, and better reproducibility for users. Technologies/skills demonstrated: Python parameterization, segmentation workflows, GitHub collaboration (PRs/commit references), and code quality practices (pre-commit-ci, co-authored commits).
1 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – Key achievements in mne-python focused on scalp surface generation reliability and efficiency. Delivered an optional reuse of segmentation files via a new reuse_seghead parameter for make_scalp_surfaces, addressing issues with stale assets and reducing recomputation. Fixed a bug in make_scalp_surfaces (Fixes make_scalp_surfaces (#13024)) with commit a5bf268a1a8645a6b4addc467dec70eb0ec26ce3, improving correctness and workflow stability. Overall impact: reduced risk of stale segmentation, faster generation, and better reproducibility for users. Technologies/skills demonstrated: Python parameterization, segmentation workflows, GitHub collaboration (PRs/commit references), and code quality practices (pre-commit-ci, co-authored commits).
February 2026
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for mne-tools/mne-python: Focused on enhancing visualization capabilities in the MNE-Python Report by introducing Source Space Visualizations with precise coordinate frames and configurable views, delivering improved analytics visualization for researchers. This work enhances data interpretability and reporting quality, bridging technical depth with user-facing clarity.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for mne-tools/mne-python: Focused on enhancing visualization capabilities in the MNE-Python Report by introducing Source Space Visualizations with precise coordinate frames and configurable views, delivering improved analytics visualization for researchers. This work enhances data interpretability and reporting quality, bridging technical depth with user-facing clarity.
Activity
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Quality Metrics
Correctness95.0%
Maintainability80.0%
Architecture85.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
3D RenderingData VisualizationPythonScientific ComputingSoftware Developmentdata processingscientific computing
Repositories Contributed To
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