mne-tools/mne-python
Nov 2024 – Jul 2026
7 Months active
Languages Used
PythonreStructuredTextShellrstYAMLRST
Technical Skills
Data VisualizationDocumentationTutorial DevelopmentBug FixCI/CDCode Refactoring
Marijn van Vliet
PROFILE
Marijn Van Vliet
Contributed to the mne-tools/mne-python repository by developing and refining scientific visualization features, interactive plotting tools, and robust system utilities. Delivered enhancements such as unit-aware fieldmap overlays, interactive sensor selection, and time point indicators in evoked topography plots, improving data interpretability and user experience. Addressed cross-platform compatibility for system information retrieval on Windows and resolved critical bugs in sensor inclusion logic and API stability. Applied Python, Matplotlib, and CI/CD practices to ensure maintainable, testable code. Work emphasized clear documentation, reliable bug fixes, and alignment with evolving dependencies, supporting both exploratory analysis and reproducible research in neuroimaging workflows.
Overall Statistics
Feature vs Bugs
46%Features
Repository Contributions
14Total
Bugs
7
Commits
14
Features
6
Lines of code
1,394
Activity Months7
Your Network
65 peopleWork History
July 2026
1 Commits • 1 Features
Jul 1, 2026Month 2026-07 — mne-tools/mne-python: Delivered Evoked Topography Visualization: Time Point Indicator. Added a solid vertical line in evoked topo plots to indicate the currently selected time, improving interaction clarity and allowing analysts to align topographic responses with precise time points. This feature enhances plot usability, enabling faster interpretation and more reliable QA of evoked data. No major bugs reported this month for the repository; maintenance work focused on delivering robust plotting improvements and keeping a clean commit history. Technologies demonstrated include Python, Matplotlib-based plotting, and UX-oriented enhancements in scientific visualization. Commit reference: ddcefca90a609e107e129c59afb13f9445c95ad8; related issue: #14032.
1 Commits • 1 Features
Jul 1, 2026Month 2026-07 — mne-tools/mne-python: Delivered Evoked Topography Visualization: Time Point Indicator. Added a solid vertical line in evoked topo plots to indicate the currently selected time, improving interaction clarity and allowing analysts to align topographic responses with precise time points. This feature enhances plot usability, enabling faster interpretation and more reliable QA of evoked data. No major bugs reported this month for the repository; maintenance work focused on delivering robust plotting improvements and keeping a clean commit history. Technologies demonstrated include Python, Matplotlib-based plotting, and UX-oriented enhancements in scientific visualization. Commit reference: ddcefca90a609e107e129c59afb13f9445c95ad8; related issue: #14032.
July 2026
January 2026
1 Commits
Jan 1, 2026January 2026 focused on stabilizing Windows cross-version behavior for system information utilities in mne-python. Delivered a PowerShell 7+ compatibility fix for mne.sys_info() on Windows by dynamically selecting the correct PowerShell executable to run the command, ensuring reliable system information across PowerShell versions and environments. This reduces user friction and support effort for Windows users relying on system information in data workflows.
January 2026
1 Commits
Jan 1, 2026January 2026 focused on stabilizing Windows cross-version behavior for system information utilities in mne-python. Delivered a PowerShell 7+ compatibility fix for mne.sys_info() on Windows by dynamically selecting the correct PowerShell executable to run the command, ensuring reliable system information across PowerShell versions and environments. This reduces user friction and support effort for Windows users relying on system information in data workflows.
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for mne-tools/mne-python focusing on forward modeling reliability and sphere auto-fit behavior. Delivered a refactor and tests for forward modeling, and resolved a warning/fit path issue to improve robustness and maintainability.
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for mne-tools/mne-python focusing on forward modeling reliability and sphere auto-fit behavior. Delivered a refactor and tests for forward modeling, and resolved a warning/fit path issue to improve robustness and maintainability.
September 2025
August 2025
3 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary focused on reliability improvements and visualization enhancements in the MNE-Python project. Delivered targeted bug fixes to sensor inclusion logic and interactive picking, plus an enhancement to topomap sphere fitting options to support additional digitization point types. These changes improve analysis accuracy, user interaction, and plotting flexibility for MEG workflows.
August 2025
3 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary focused on reliability improvements and visualization enhancements in the MNE-Python project. Delivered targeted bug fixes to sensor inclusion logic and interactive picking, plus an enhancement to topomap sphere fitting options to support additional digitization point types. These changes improve analysis accuracy, user interaction, and plotting flexibility for MEG workflows.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for mne-tools/mne-python highlighting the development of fieldmap visualization with unit-aware scaling on brain models, along with updated tests and robust unit handling.
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for mne-tools/mne-python highlighting the development of fieldmap visualization with unit-aware scaling on brain models, along with updated tests and robust unit handling.
February 2025
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for mne-python: Delivered targeted visualization enhancements, API stability, and dependency readiness to support researchers with more reliable and efficient workflows. Key outcomes include: interactive sensor selection in plot_evoked_topo via a new lasso tool; restored vmin/vmax controls for plot_evoked_field when plot_density=False; API compatibility improvements to make the close event parameter optional across MNEAnnotationFigure, MNESelectionFigure, and BrowserBase; and SciPy deprecation compatibility along with CI/dependency updates to maintain ecosystem alignment. These changes reduce user friction, improve exploratory analysis capabilities, and minimize maintenance risk for downstream users.
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for mne-python: Delivered targeted visualization enhancements, API stability, and dependency readiness to support researchers with more reliable and efficient workflows. Key outcomes include: interactive sensor selection in plot_evoked_topo via a new lasso tool; restored vmin/vmax controls for plot_evoked_field when plot_density=False; API compatibility improvements to make the close event parameter optional across MNEAnnotationFigure, MNESelectionFigure, and BrowserBase; and SciPy deprecation compatibility along with CI/dependency updates to maintain ecosystem alignment. These changes reduce user friction, improve exploratory analysis capabilities, and minimize maintenance risk for downstream users.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024: Focused on delivering a critical Dipole Orientation tutorial enhancement in mne-python to improve the reliability and interpretability of pooling analyses. Implemented a warning about pooling across dipole orientations, clarifying that default retention of only magnitude can distort averages and oscillatory signals, and added minor 3D view adjustments to enhance visualization. Consolidated around documentation and visualization improvements; no major bug fixes reported this month.
1 Commits • 1 Features
Nov 1, 2024November 2024: Focused on delivering a critical Dipole Orientation tutorial enhancement in mne-python to improve the reliability and interpretability of pooling analyses. Implemented a warning about pooling across dipole orientations, clarifying that default retention of only magnitude can distort averages and oscillatory signals, and added minor 3D view adjustments to enhance visualization. Consolidated around documentation and visualization improvements; no major bug fixes reported this month.
November 2024
Activity
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Quality Metrics
Correctness90.8%
Maintainability87.2%
Architecture81.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonRSTShellYAMLreStructuredTextrst
Technical Skills
Bug FixBug FixingCI/CDCode RefactoringData VisualizationDependency ManagementDocumentationInteractive PlottingMatplotlibPythonPython DevelopmentPython ScriptingScientific ComputingSignal ProcessingSoftware Engineering
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