AFM-SPM/TopoStats
Oct 2024 – Oct 2025
12 Months active
Languages Used
PythonTOMLYAMLCSVMarkdownNonepythonyaml
Technical Skills
Bug FixCI/CDCode CleanupCode RefactoringConfiguration ManagementDependency Management
Neil Shephard
PROFILE
Neil Shephard
Neil Shephard developed and maintained the AFM-SPM/TopoStats repository, delivering robust data processing pipelines and extensible configuration management for scientific imaging workflows. He engineered features such as multi-format data ingestion, YAML-based configuration extensibility, and HDF5 serialization, while systematically improving CI/CD reliability and test coverage. Using Python and YAML, Neil refactored core modules for maintainability, introduced type hints and linting, and stabilized dependency management to ensure compatibility with evolving scientific libraries. His work addressed real-world challenges in data integrity, reproducibility, and onboarding, resulting in a codebase that supports rapid iteration, reliable analytics, and streamlined integration of new imaging modalities.
Overall Statistics
Feature vs Bugs
72%Features
Repository Contributions
138Total
Bugs
21
Commits
138
Features
55
Lines of code
13,642
Activity Months12
Your Network
23 people
Work History
October 2025
4 Commits • 3 Features
Oct 1, 2025Month 2025-10 Summary for AFM-SPM/TopoStats: Delivered a YAML configuration extension to allow writing YAML config files from extension packages, enabling default configurations from external packages and easier customization of analysis pipelines across different imaging sample types. Clarified the data dictionary for image_statistics.csv to explicitly reflect per-scan summary metrics, improving user understanding and reducing ambiguity. Implemented code quality and linting improvements to strengthen maintainability, including updates to pre-commit and lint configurations, removal of noisy comments, and addition of type hints/docstrings in notebook files. No critical defects surfaced; the improvements reduce risk, accelerate onboarding, and increase CI reliability.
4 Commits • 3 Features
Oct 1, 2025Month 2025-10 Summary for AFM-SPM/TopoStats: Delivered a YAML configuration extension to allow writing YAML config files from extension packages, enabling default configurations from external packages and easier customization of analysis pipelines across different imaging sample types. Clarified the data dictionary for image_statistics.csv to explicitly reflect per-scan summary metrics, improving user understanding and reducing ambiguity. Implemented code quality and linting improvements to strengthen maintainability, including updates to pre-commit and lint configurations, removal of noisy comments, and addition of type hints/docstrings in notebook files. No critical defects surfaced; the improvements reduce risk, accelerate onboarding, and increase CI reliability.
October 2025
August 2025
2 Commits • 2 Features
Aug 1, 2025Monthly summary for Aug 2025 for AFM-SPM/TopoStats. Delivered two key features focused on reliability, security, and maintainability. No major bugs fixed this period. These changes reduce build instability and operational risk, streamline version handling, and prepare the codebase for easier future upgrades. Impacted teams benefit from faster and more reliable CI, easier onboarding, and stronger security posture.
August 2025
2 Commits • 2 Features
Aug 1, 2025Monthly summary for Aug 2025 for AFM-SPM/TopoStats. Delivered two key features focused on reliability, security, and maintainability. No major bugs fixed this period. These changes reduce build instability and operational risk, streamline version handling, and prepare the codebase for easier future upgrades. Impacted teams benefit from faster and more reliable CI, easier onboarding, and stronger security posture.
July 2025
2 Commits
Jul 1, 2025July 2025 monthly summary for AFM-SPM/TopoStats: Delivered dependency stability and mitigation of deprecation risks. Key activities included reverting the numpyencoder dependency to the official PyPI release to avoid issues from Git-based forks and merging upstream fixes for NumPy version detection. To avoid runtime disruptions from Pillow, pinned Pillow to <=11.1.0, addressing DeprecationWarning observed with Pillow 11.3.0. These changes reduce production incidents, improve reliability, and simplify future maintenance. Technologies demonstrated include Python packaging, dependency management, and alignment with upstream community fixes, reinforcing long-term compatibility with the Python scientific stack.
2 Commits
Jul 1, 2025July 2025 monthly summary for AFM-SPM/TopoStats: Delivered dependency stability and mitigation of deprecation risks. Key activities included reverting the numpyencoder dependency to the official PyPI release to avoid issues from Git-based forks and merging upstream fixes for NumPy version detection. To avoid runtime disruptions from Pillow, pinned Pillow to <=11.1.0, addressing DeprecationWarning observed with Pillow 11.3.0. These changes reduce production incidents, improve reliability, and simplify future maintenance. Technologies demonstrated include Python packaging, dependency management, and alignment with upstream community fixes, reinforcing long-term compatibility with the Python scientific stack.
July 2025
June 2025
10 Commits • 6 Features
Jun 1, 2025June 2025 monthly summary for AFM-SPM/TopoStats focusing on delivering stability, broader data support, and measurable business value. Key efforts centered on CI reliability, feature extensions for data processing, and improvements to Bruker data handling and test configuration. The work resulted in more reliable builds, expanded data interoperability with numpy 2.0, and enhanced end-to-end workflows for Bruker data processing and image loading.
June 2025
10 Commits • 6 Features
Jun 1, 2025June 2025 monthly summary for AFM-SPM/TopoStats focusing on delivering stability, broader data support, and measurable business value. Key efforts centered on CI reliability, feature extensions for data processing, and improvements to Bruker data handling and test configuration. The work resulted in more reliable builds, expanded data interoperability with numpy 2.0, and enhanced end-to-end workflows for Bruker data processing and image loading.
May 2025
18 Commits • 5 Features
May 1, 2025May 2025: Stabilized and modernized the TopoStats codebase, delivering faster feedback loops, higher reliability, and improved developer experience. Key bug fixes fixed API setter return behavior, added equality tests, and ensured robust handling of None image paths to prevent crashes. CI now supports parallel test execution, significantly reducing run times. In addition, deprecated modules were removed and packaging was updated to Python 3.10+ with latest numpy dependencies, while code quality improved through type hints and linting. Overall impact: reduced runtime errors, faster releases, and a cleaner, scalable foundation for future features such as expanded testing and clearer user-facing help text.
18 Commits • 5 Features
May 1, 2025May 2025: Stabilized and modernized the TopoStats codebase, delivering faster feedback loops, higher reliability, and improved developer experience. Key bug fixes fixed API setter return behavior, added equality tests, and ensured robust handling of None image paths to prevent crashes. CI now supports parallel test execution, significantly reducing run times. In addition, deprecated modules were removed and packaging was updated to Python 3.10+ with latest numpy dependencies, while code quality improved through type hints and linting. Overall impact: reduced runtime errors, faster releases, and a cleaner, scalable foundation for future features such as expanded testing and clearer user-facing help text.
May 2025
April 2025
15 Commits • 3 Features
Apr 1, 20252025-04 Monthly Summary for AFM-SPM/TopoStats: Focused on increasing data integrity, reliability, and usability across the TopoStats project. Delivered enhanced testing infrastructure, CLI/config improvements, and data-model/IO enhancements to enable robust data workflows and reproducibility. Fixed critical test and CLI-related issues to reduce false positives and improve developer experience. Overall, the work accelerates trustworthy analytics delivery and smoother data interchange for topology statistics.
April 2025
15 Commits • 3 Features
Apr 1, 20252025-04 Monthly Summary for AFM-SPM/TopoStats: Focused on increasing data integrity, reliability, and usability across the TopoStats project. Delivered enhanced testing infrastructure, CLI/config improvements, and data-model/IO enhancements to enable robust data workflows and reproducibility. Fixed critical test and CLI-related issues to reduce false positives and improve developer experience. Overall, the work accelerates trustworthy analytics delivery and smoother data interchange for topology statistics.
March 2025
10 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for AFM-SPM/TopoStats: Delivered end-to-end data I/O enhancements and stabilized the test suite, translating grain crop data structures to dictionaries and supporting HDF5 I/O. Implemented serialization-to-dict for ImageGrainCrops, GrainCrops, and GrainCropsDirection, added recursive dict conversion, and updated the topostats format to 0.3. Stabilized AFMReader tests after refactor and aligned dependencies to ensure consistent JPK/JPK2 behavior. This work reduces data pipeline friction, improves storage interoperability, and increases test reliability, enabling smoother analytics workflows and faster iteration. Skills demonstrated include Python data modeling, HDF5 I/O (via h5py), test engineering, and dependency management.
10 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for AFM-SPM/TopoStats: Delivered end-to-end data I/O enhancements and stabilized the test suite, translating grain crop data structures to dictionaries and supporting HDF5 I/O. Implemented serialization-to-dict for ImageGrainCrops, GrainCrops, and GrainCropsDirection, added recursive dict conversion, and updated the topostats format to 0.3. Stabilized AFMReader tests after refactor and aligned dependencies to ensure consistent JPK/JPK2 behavior. This work reduces data pipeline friction, improves storage interoperability, and increases test reliability, enabling smoother analytics workflows and faster iteration. Skills demonstrated include Python data modeling, HDF5 I/O (via h5py), test engineering, and dependency management.
March 2025
February 2025
4 Commits • 2 Features
Feb 1, 2025February 2025 - AFM-SPM/TopoStats: Maintained code quality, improved data ingestion robustness, and enhanced CI compatibility. Key outcomes include dictionary-based parameter handling, consolidated vet_grains configuration, AFMReader integration with dictated I/O, and proactive directory management to prevent processing failures. These changes reduce manual maintenance, improve reliability of analyses, and accelerate iteration cycles.
February 2025
4 Commits • 2 Features
Feb 1, 2025February 2025 - AFM-SPM/TopoStats: Maintained code quality, improved data ingestion robustness, and enhanced CI compatibility. Key outcomes include dictionary-based parameter handling, consolidated vet_grains configuration, AFMReader integration with dictated I/O, and proactive directory management to prevent processing failures. These changes reduce manual maintenance, improve reliability of analyses, and accelerate iteration cycles.
January 2025
15 Commits • 2 Features
Jan 1, 2025January 2025 (AFM-SPM/TopoStats): Delivered core data extraction enhancements and a grain-detection workflow, stabilized the test suite, and improved documentation and code quality. These changes advance data pipeline reliability, reproducibility, and onboarding. Key deliverables and business value: - TopoStats: Extract components from .topostats - Added extraction for raw data, filtered data, cleaned image, and metadata; tests cover multiple extraction options and error handling for invalid requests; improves downstream analysis pipelines and data integrity. - Commit: b353a4ae1aeddcba902a902cc5fffc237b734d3c - Grains Sub-command for Grain Detection - New grains sub-command to process grain detection on image data; includes processing/run functions and tests; supports extracting flattened images and re-running grain detection with output saved for comparison, enabling reproducibility and benchmarking. - Commits: 369ef2d5f913e9404b444a123d5e1690ff730afe; 778caaa9d976f0d43eec8f5ab9f3d443007bfc42 - Test stability and reliability improvements - Relaxed dict_almost_equal tolerance to reduce flaky CI; removed OS-specific paths from caplog tests to improve portability. - Commits: 059ed396880a674cc440c8ed24968da6259c43ef; eca6fd553f39cbfecffbb7eec5f862c3340a950e; d7a6e8bc183a80a0afaa8e8d41cc1956199bc795 - Data naming standardization and code quality - Standardized image data naming (image_flattened -> image) and updated tests; Ruff lint config updated (ignore A005); improved code quality and consistency. - Commits: e9fac78f0bebf307e76280ede1a07ede6ba5f63b; 67fa4fca0c455281f5aabebf618cfca249ba7299 - Documentation and contributor guidance - Comprehensive docs on adding new functions/modules, workflow overview, argument parsing, configuration, and parallel processing; fixes to typos and contributing guidance. - Commits: 53b4463a39ae5fa9c04c34362d9c2e3b552130c0; c4dc753fedd6b9fd7180629a6440de83421bf35a; a90a101fdef5a22f1dc0e5f6df675494dc3493e1; caf9a4ab49750624d52b52a8a950e85d4d21a36f; 5e2a26bb7b976397576a2651889390e269a24c9d; 294005b120f35cc93cead5b5e862e80decc2fc6f; 7c981af3625e77f539ebd91c0dc46b1b742ff128
15 Commits • 2 Features
Jan 1, 2025January 2025 (AFM-SPM/TopoStats): Delivered core data extraction enhancements and a grain-detection workflow, stabilized the test suite, and improved documentation and code quality. These changes advance data pipeline reliability, reproducibility, and onboarding. Key deliverables and business value: - TopoStats: Extract components from .topostats - Added extraction for raw data, filtered data, cleaned image, and metadata; tests cover multiple extraction options and error handling for invalid requests; improves downstream analysis pipelines and data integrity. - Commit: b353a4ae1aeddcba902a902cc5fffc237b734d3c - Grains Sub-command for Grain Detection - New grains sub-command to process grain detection on image data; includes processing/run functions and tests; supports extracting flattened images and re-running grain detection with output saved for comparison, enabling reproducibility and benchmarking. - Commits: 369ef2d5f913e9404b444a123d5e1690ff730afe; 778caaa9d976f0d43eec8f5ab9f3d443007bfc42 - Test stability and reliability improvements - Relaxed dict_almost_equal tolerance to reduce flaky CI; removed OS-specific paths from caplog tests to improve portability. - Commits: 059ed396880a674cc440c8ed24968da6259c43ef; eca6fd553f39cbfecffbb7eec5f862c3340a950e; d7a6e8bc183a80a0afaa8e8d41cc1956199bc795 - Data naming standardization and code quality - Standardized image data naming (image_flattened -> image) and updated tests; Ruff lint config updated (ignore A005); improved code quality and consistency. - Commits: e9fac78f0bebf307e76280ede1a07ede6ba5f63b; 67fa4fca0c455281f5aabebf618cfca249ba7299 - Documentation and contributor guidance - Comprehensive docs on adding new functions/modules, workflow overview, argument parsing, configuration, and parallel processing; fixes to typos and contributing guidance. - Commits: 53b4463a39ae5fa9c04c34362d9c2e3b552130c0; c4dc753fedd6b9fd7180629a6440de83421bf35a; a90a101fdef5a22f1dc0e5f6df675494dc3493e1; caf9a4ab49750624d52b52a8a950e85d4d21a36f; 5e2a26bb7b976397576a2651889390e269a24c9d; 294005b120f35cc93cead5b5e862e80decc2fc6f; 7c981af3625e77f539ebd91c0dc46b1b742ff128
January 2025
December 2024
30 Commits • 17 Features
Dec 1, 2024December 2024: Expanded data ingestion, improved code quality, and strengthened CI hygiene for AFM-SPM/TopoStats. Delivered IO improvements enabling AFMReader to load .spm, .topostats, .ibw, .jpk, and .gwy; added a new --image-set option to topostats and a sub-command to run filtering. Hardened tests with a parameterized missing-data scenario. Fixed key data quality issues: removed the index column from all_statistics.csv and eliminated saving of numpy arrays. Introduced nbqa pre-commit hooks and broad linting/formatting improvements to raise code quality and consistency.
December 2024
30 Commits • 17 Features
Dec 1, 2024December 2024: Expanded data ingestion, improved code quality, and strengthened CI hygiene for AFM-SPM/TopoStats. Delivered IO improvements enabling AFMReader to load .spm, .topostats, .ibw, .jpk, and .gwy; added a new --image-set option to topostats and a sub-command to run filtering. Hardened tests with a parameterized missing-data scenario. Fixed key data quality issues: removed the index column from all_statistics.csv and eliminated saving of numpy arrays. Introduced nbqa pre-commit hooks and broad linting/formatting improvements to raise code quality and consistency.
November 2024
23 Commits • 14 Features
Nov 1, 2024November 2024: Delivered stability, maintainability, and quality improvements for AFM-SPM/TopoStats, focusing on enhancing reliability of the data pipeline and accelerating PR reviews. Key outcomes include stabilizing the macOS test suite, enabling faster adoption of newer dependencies, and strengthening CI/CD and documentation practices, along with expanded test coverage for edge cases in traces and processing.
23 Commits • 14 Features
Nov 1, 2024November 2024: Delivered stability, maintainability, and quality improvements for AFM-SPM/TopoStats, focusing on enhancing reliability of the data pipeline and accelerating PR reviews. Key outcomes include stabilizing the macOS test suite, enabling faster adoption of newer dependencies, and strengthening CI/CD and documentation practices, along with expanded test coverage for edge cases in traces and processing.
November 2024
October 2024
5 Commits
Oct 1, 2024October 2024 focused on stability, maintainability, and build reliability in AFM-SPM/TopoStats. No new user-facing features delivered this month; instead, a set of targeted bug fixes and a dependency stabilization effort were completed to reduce runtime risk and streamline future development. Key actions: - Initialization and Configuration Cleanup: Removed a redundant TensorFlow log level initialization and corrected a configuration file comment to improve initialization reliability and configuration parsing. - Remove Legacy Entry Points: Deleted legacy entry points and their tests to simplify the codebase and prevent outdated functionality from being used. - Dependency Stabilization: Pin skan to version 0.11.1 to avoid Numba/nbgraph-related compilation errors introduced in 0.12.0. Impact: - Stability: Fewer startup and compilation-time errors, leading to more predictable CI results and smoother onboarding for new contributors. - Maintainability: Reduced code surface area and clearer configuration handling support faster future changes. - Risk reduction: Eliminated legacy code paths that could cause regressions under refactors. Technologies/Skills Demonstrated: - TensorFlow logging management and config parsing - Codebase refactoring and test cleanup - Dependency pinning and environment stabilization - Clear, commit-referenced change records for traceability
October 2024
5 Commits
Oct 1, 2024October 2024 focused on stability, maintainability, and build reliability in AFM-SPM/TopoStats. No new user-facing features delivered this month; instead, a set of targeted bug fixes and a dependency stabilization effort were completed to reduce runtime risk and streamline future development. Key actions: - Initialization and Configuration Cleanup: Removed a redundant TensorFlow log level initialization and corrected a configuration file comment to improve initialization reliability and configuration parsing. - Remove Legacy Entry Points: Deleted legacy entry points and their tests to simplify the codebase and prevent outdated functionality from being used. - Dependency Stabilization: Pin skan to version 0.11.1 to avoid Numba/nbgraph-related compilation errors introduced in 0.12.0. Impact: - Stability: Fewer startup and compilation-time errors, leading to more predictable CI results and smoother onboarding for new contributors. - Maintainability: Reduced code surface area and clearer configuration handling support faster future changes. - Risk reduction: Eliminated legacy code paths that could cause regressions under refactors. Technologies/Skills Demonstrated: - TensorFlow logging management and config parsing - Codebase refactoring and test cleanup - Dependency pinning and environment stabilization - Clear, commit-referenced change records for traceability
Activity
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Quality Metrics
Correctness92.4%
Maintainability94.6%
Architecture89.8%
Performance87.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVGitGit IgnoreINIJSONJupyter NotebookMarkdownMermaidNoneNumPy
Technical Skills
Argument ParsingBackend DevelopmentBug FixBug FixingBuild ProcessCI/CDCLI developmentCSV HandlingCode CleanupCode FormattingCode LintingCode MaintenanceCode OrganizationCode QualityCode Refactoring
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