ibs-lab/cedalion
Nov 2024 – May 2026
10 Months active
Languages Used
Jupyter NotebookPythonYAMLBibTeXMarkdownPytestSQLShell
Technical Skills
3D PlottingBug FixingCode FormattingCode RefactoringComputer VisionConfiguration
Eike Middell
PROFILE
Eike Middell
Worked on the ibs-lab/cedalion repository, delivering robust neuroimaging data analysis and visualization tooling. Developed features for flexible GLM modeling, out-of-core computation, and atlas-based parcel assignment, while enhancing BIDS compliance and supporting new data types such as TD-NIRS SNIRF. Improved reliability through rigorous error handling, unit normalization, and cross-platform test infrastructure, addressing issues like NaN masking and file compatibility. Leveraged Python, NumPy, and Jupyter Notebooks to implement scientific computing workflows, optimize performance, and streamline documentation. Expanded dataset support and visualization fidelity, enabling reproducible, scalable analyses and smoother onboarding for users working with complex neuroscience and photogrammetry data.
Overall Statistics
Feature vs Bugs
69%Features
Repository Contributions
144Total
Bugs
24
Commits
144
Features
54
Lines of code
25,533
Activity Months10
Your Network
11 peopleWork History
May 2026
30 Commits • 11 Features
May 1, 2026May 2026 — ibs-lab/cedalion monthly summary. Focused on delivering reliable features, fixing critical issues, and improving usability, reproducibility, and Colab readiness for neuroimaging workflows.
30 Commits • 11 Features
May 1, 2026May 2026 — ibs-lab/cedalion monthly summary. Focused on delivering reliable features, fixing critical issues, and improving usability, reproducibility, and Colab readiness for neuroimaging workflows.
May 2026
April 2026
16 Commits • 4 Features
Apr 1, 2026In April 2026, the Cedalion project delivered reliability, data I/O, dataset, and documentation improvements across the ibs-lab/cedalion repository, strengthening data integrity, visualization fidelity, and onboarding for new users. Key work included robustness fixes in image_to_channel_space and sensitivity computations to prevent dimension/miscalculation errors and guard against division by zero when fluence is zero, plus a mode switch enhancement for scale_to_landmarks when three landmarks are provided. Visual rendering quality was improved with a higher feature_angle in 3D surface plots, resulting in smoother and more informative visualizations. TD-NIRS SNIRF I/O support was added, including new data types for TD moments and a SNIRF compression function, expanding interoperability with SNIRF-based workflows. Dataset expansions added LUMO test data and Kernel/Artinis datasets, with notebooks updated to align with Artinis data where appropriate. Documentation, citations, and notebook metadata were enhanced for better reproducibility and usability (Sphinx shim, bibliography integration, cell ID warnings, and references sections). These changes collectively reduce data handling errors, improve presentation and reproducibility, and broaden the project’s interoperability and data coverage.
April 2026
16 Commits • 4 Features
Apr 1, 2026In April 2026, the Cedalion project delivered reliability, data I/O, dataset, and documentation improvements across the ibs-lab/cedalion repository, strengthening data integrity, visualization fidelity, and onboarding for new users. Key work included robustness fixes in image_to_channel_space and sensitivity computations to prevent dimension/miscalculation errors and guard against division by zero when fluence is zero, plus a mode switch enhancement for scale_to_landmarks when three landmarks are provided. Visual rendering quality was improved with a higher feature_angle in 3D surface plots, resulting in smoother and more informative visualizations. TD-NIRS SNIRF I/O support was added, including new data types for TD moments and a SNIRF compression function, expanding interoperability with SNIRF-based workflows. Dataset expansions added LUMO test data and Kernel/Artinis datasets, with notebooks updated to align with Artinis data where appropriate. Documentation, citations, and notebook metadata were enhanced for better reproducibility and usability (Sphinx shim, bibliography integration, cell ID warnings, and references sections). These changes collectively reduce data handling errors, improve presentation and reproducibility, and broaden the project’s interoperability and data coverage.
June 2025
27 Commits • 10 Features
Jun 1, 2025June 2025 monthly summary for ibs-lab/cedalion: Focused on scalability, data-robustness, and release-readiness. Delivered out-of-core computation for fluence and sensitivity; integrated Schaefer parcellations for ICBM152/Colin27; exposed general affine register in TwoSurfaceHeadModel workflow; improved documentation and prepared release changelog; fixed TimeOffset handling for auxiliary channels to improve data robustness.
27 Commits • 10 Features
Jun 1, 2025June 2025 monthly summary for ibs-lab/cedalion: Focused on scalability, data-robustness, and release-readiness. Delivered out-of-core computation for fluence and sensitivity; integrated Schaefer parcellations for ICBM152/Colin27; exposed general affine register in TwoSurfaceHeadModel workflow; improved documentation and prepared release changelog; fixed TimeOffset handling for auxiliary channels to improve data robustness.
June 2025
May 2025
5 Commits • 3 Features
May 1, 2025May 2025 performance-focused monthly summary for ibs-lab/cedalion. Delivered robustness, reliability, and performance improvements across modeling, testing, and deployment. Key outcomes include (1) robust NaN handling in ar_irls_GLM fitting by masking non-finite values to prevent degraded iterations, (2) fixed bibliography syntax error in references.bib to ensure proper parsing and references integrity, (3) enhanced test infrastructure with a cross-platform temporary_filename context manager for Windows compatibility, (4) speedups in forward-model computations by applying NumPy matmul and re-packaging results as an Xarray DataArray for faster core calculations, and (5) reproducible deployments by pinning nirfaster to version 0.9.6 in the installation script.
May 2025
5 Commits • 3 Features
May 1, 2025May 2025 performance-focused monthly summary for ibs-lab/cedalion. Delivered robustness, reliability, and performance improvements across modeling, testing, and deployment. Key outcomes include (1) robust NaN handling in ar_irls_GLM fitting by masking non-finite values to prevent degraded iterations, (2) fixed bibliography syntax error in references.bib to ensure proper parsing and references integrity, (3) enhanced test infrastructure with a cross-platform temporary_filename context manager for Windows compatibility, (4) speedups in forward-model computations by applying NumPy matmul and re-packaging results as an Xarray DataArray for faster core calculations, and (5) reproducible deployments by pinning nirfaster to version 0.9.6 in the installation script.
April 2025
5 Commits • 3 Features
Apr 1, 2025April 2025 • Cedalion (ibs-lab/cedalion) monthly summary Key objective: deliver flexible GLM tooling, improve cross-platform reliability, and enhance documentation to empower users and reduce maintenance burden.
5 Commits • 3 Features
Apr 1, 2025April 2025 • Cedalion (ibs-lab/cedalion) monthly summary Key objective: deliver flexible GLM tooling, improve cross-platform reliability, and enhance documentation to empower users and reduce maintenance burden.
April 2025
March 2025
2 Commits
Mar 1, 2025March 2025 focused on robustness and maintainability in the cedalion repository, with two targeted bug fixes that enhance data reliability and user feedback. The work improves downstream data processing pipelines and reduces noise in logs, while maintaining compatibility with existing workflows.
March 2025
2 Commits
Mar 1, 2025March 2025 focused on robustness and maintainability in the cedalion repository, with two targeted bug fixes that enhance data reliability and user feedback. The work improves downstream data processing pipelines and reduces noise in logs, while maintaining compatibility with existing workflows.
February 2025
11 Commits • 5 Features
Feb 1, 2025February 2025 – Focused on strengthening data ingestion, modeling robustness, and visualization to deliver reliable scientific tooling and clearer signal interpretation. Key improvements across NIRS data handling, design matrix reliability, geometry registration, and visualization, with test coverage enhancing quality gates.
11 Commits • 5 Features
Feb 1, 2025February 2025 – Focused on strengthening data ingestion, modeling robustness, and visualization to deliver reliable scientific tooling and clearer signal interpretation. Key improvements across NIRS data handling, design matrix reliability, geometry registration, and visualization, with test coverage enhancing quality gates.
February 2025
January 2025
28 Commits • 10 Features
Jan 1, 2025January 2025 monthly summary for ibs-lab/cedalion focused on modernizing packaging and build tooling, enhancing GVTD reliability, expanding unit tests and data assets, and tightening CI/delivery workflows to improve reproducibility and business value.
January 2025
28 Commits • 10 Features
Jan 1, 2025January 2025 monthly summary for ibs-lab/cedalion focused on modernizing packaging and build tooling, enhancing GVTD reliability, expanding unit tests and data assets, and tightening CI/delivery workflows to improve reproducibility and business value.
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for ibs-lab/cedalion: Delivered two major improvements that enhance build reliability and cross-implementation consistency. GaussianKernels alignment with Homer2, with a new GaussianKernelsWithTails variant to preserve the previous padding behavior, improves consistency for users migrating between implementations. BibTeX References Formatting Fixes ensure Sphinx/BibTeX builds run without errors by correcting an extra newline after the year and aligning entry types (including using @misc for @software). These changes reduce build failures, streamline onboarding, and improve developer experience. Technologies demonstrated include Python, Sphinx/BibTeX integration, and cross-implementation maintenance. Overall impact: more reliable builds, fewer support tickets, and smoother user migration between GaussianKernels and Homer2 implementations.
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for ibs-lab/cedalion: Delivered two major improvements that enhance build reliability and cross-implementation consistency. GaussianKernels alignment with Homer2, with a new GaussianKernelsWithTails variant to preserve the previous padding behavior, improves consistency for users migrating between implementations. BibTeX References Formatting Fixes ensure Sphinx/BibTeX builds run without errors by correcting an extra newline after the year and aligning entry types (including using @misc for @software). These changes reduce build failures, streamline onboarding, and improve developer experience. Technologies demonstrated include Python, Sphinx/BibTeX integration, and cross-implementation maintenance. Overall impact: more reliable builds, fewer support tickets, and smoother user migration between GaussianKernels and Homer2 implementations.
December 2024
November 2024
17 Commits • 7 Features
Nov 1, 2024November 2024 (2024-11) monthly summary for ibs-lab/cedalion: Key features delivered: - SNIRF CRS support: Add capability to specify Coordinate Reference System when reading SNIRF data by passing CRS through to geometry_from_probe, enabling geo-accurate analyses across datasets. - GLM and to_epochs enhancements: Extend GLM design matrix to permit averaging of short channels into a single regressor; improve to_epochs robustness across datasets (time units, interpolation, edge cases). - Pruning flexibility with flag_drop: Introduce flag_drop to prune_ch to choose between dropping pruned channels or setting them to NaN, increasing data handling flexibility. - Image reconstruction improvements: Refactor reconstruction flow to encapsulate flattening of channel/vertex dims and introduce apply_inv_sensitivity for inversion and application of sensitivity matrices; update related plots. - Photogrammetry notebooks enhancements: Add descriptive text, scalp plots for mapping validation, extended sticker-processing visuals, and non-interactive rendering to improve clarity and batch execution. - Development environment and dependencies: Update environment to include PyQt, ipympl, and updated core dependencies for compatibility and tooling. - Artifact generation and optical computations refactor: Refactor artifact generation to use a Protocol, remove mutable defaults, dynamically derive wavelengths in optical density calculations, and rename TDDR to tddr for PEP8 consistency. Major bugs fixed: - SNIRF data loading robustness: Fix handling of empty/malformed stimulus objects in SNIRF loading by validating 2D shape, logging a warning, and returning an empty DataFrame to prevent crashes. Overall impact and accomplishments: - Strengthened data integrity and reliability of SNIRF imports, enabling robust multi-dataset analyses. - Improved modeling fidelity and analysis pipeline resilience through GLM/to_epochs enhancements and dataset-agnostic robustness. - Increased flexibility in data curation and processing, better plotting and notebook usability, and smoother onboarding via updated development tooling. Technologies/skills demonstrated: - Python, data validation, and robust error handling in data loading. - GLM design and time-series processing, with improved epoch handling across datasets. - Photogrammetry tooling and notebook storytelling with mapping validation visuals. - Modern software engineering practices: Protocol-based design, PEP8 naming, dependency management, and refactoring for performance and readability. - Cross-discipline toolchain experience (PyQt, ipympl) and pipeline end-to-end improvements.
November 2024
17 Commits • 7 Features
Nov 1, 2024November 2024 (2024-11) monthly summary for ibs-lab/cedalion: Key features delivered: - SNIRF CRS support: Add capability to specify Coordinate Reference System when reading SNIRF data by passing CRS through to geometry_from_probe, enabling geo-accurate analyses across datasets. - GLM and to_epochs enhancements: Extend GLM design matrix to permit averaging of short channels into a single regressor; improve to_epochs robustness across datasets (time units, interpolation, edge cases). - Pruning flexibility with flag_drop: Introduce flag_drop to prune_ch to choose between dropping pruned channels or setting them to NaN, increasing data handling flexibility. - Image reconstruction improvements: Refactor reconstruction flow to encapsulate flattening of channel/vertex dims and introduce apply_inv_sensitivity for inversion and application of sensitivity matrices; update related plots. - Photogrammetry notebooks enhancements: Add descriptive text, scalp plots for mapping validation, extended sticker-processing visuals, and non-interactive rendering to improve clarity and batch execution. - Development environment and dependencies: Update environment to include PyQt, ipympl, and updated core dependencies for compatibility and tooling. - Artifact generation and optical computations refactor: Refactor artifact generation to use a Protocol, remove mutable defaults, dynamically derive wavelengths in optical density calculations, and rename TDDR to tddr for PEP8 consistency. Major bugs fixed: - SNIRF data loading robustness: Fix handling of empty/malformed stimulus objects in SNIRF loading by validating 2D shape, logging a warning, and returning an empty DataFrame to prevent crashes. Overall impact and accomplishments: - Strengthened data integrity and reliability of SNIRF imports, enabling robust multi-dataset analyses. - Improved modeling fidelity and analysis pipeline resilience through GLM/to_epochs enhancements and dataset-agnostic robustness. - Increased flexibility in data curation and processing, better plotting and notebook usability, and smoother onboarding via updated development tooling. Technologies/skills demonstrated: - Python, data validation, and robust error handling in data loading. - GLM design and time-series processing, with improved epoch handling across datasets. - Photogrammetry tooling and notebook storytelling with mapping validation visuals. - Modern software engineering practices: Protocol-based design, PEP8 naming, dependency management, and refactoring for performance and readability. - Cross-discipline toolchain experience (PyQt, ipympl) and pipeline end-to-end improvements.
Activity
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Quality Metrics
Correctness91.4%
Maintainability90.2%
Architecture88.0%
Performance84.2%
AI Usage21.2%
Skills & Technologies
Programming Languages
BibTeXJSONJavaScriptJupyter NotebookMakefileMarkdownPytestPythonSQLShell
Technical Skills
3D Plotting3D Transformations3D renderingAPI DesignAPI IntegrationAffine TransformationsBIDS complianceBibTeXBrainstormBug FixingBuild AutomationBuild SystemBuild SystemsCAT12CI/CD
Repositories Contributed To
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