glotzerlab/freud
Nov 2024 – Aug 2025
6 Months active
Languages Used
C++CMakeCythonPythonYAMLMarkdown
Technical Skills
Build SystemBuild System ConfigurationC++C++ DevelopmentCI/CDClass Implementation
Domagoj Fijan
PROFILE
Domagoj Fijan
Domagoj Fijan contributed to the glotzerlab/freud repository by modernizing core modules, enhancing Python bindings, and improving data analysis workflows. Over six months, he ported C++ modules to Python, unified APIs, and strengthened NumPy interoperability, focusing on maintainability and reliability. His work included refactoring build systems with CMake, implementing robust error handling, and introducing optional plotting dependencies to streamline user experience. Fijan addressed bugs in MSD computation and data handling, updated documentation for clarity, and managed release engineering for version 3.4.0. Using C++, Python, and CI/CD practices, he delivered well-structured, maintainable code that improved scientific computing workflows.
Overall Statistics
Feature vs Bugs
65%Features
Repository Contributions
55Total
Bugs
6
Commits
55
Features
11
Lines of code
5,826
Activity Months6
Work History
August 2025
2 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Release engineering focused on glotzerlab/freud. Delivered Release 3.4.0 with a system-wide version bump and CHANGELOG update, establishing a stable baseline for downstream users. No major bugs fixed this month; the work centers on release readiness, upgrade path clarity, and traceability. Tech stack involved: versioned changes across configuration and source files, and release-note generation. Business impact: predictable upgrade cycle, improved release visibility, and reduced risk for users upgrading to 3.4.0.
2 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Release engineering focused on glotzerlab/freud. Delivered Release 3.4.0 with a system-wide version bump and CHANGELOG update, establishing a stable baseline for downstream users. No major bugs fixed this month; the work centers on release readiness, upgrade path clarity, and traceability. Tech stack involved: versioned changes across configuration and source files, and release-note generation. Business impact: predictable upgrade cycle, improved release visibility, and reduced risk for users upgrading to 3.4.0.
August 2025
July 2025
14 Commits • 2 Features
Jul 1, 2025Monthly summary for 2025-07 (glotzerlab/freud). Focused on delivering robust plotting behavior, stabilizing core analytics, and improving code quality for maintainability and user value.
July 2025
14 Commits • 2 Features
Jul 1, 2025Monthly summary for 2025-07 (glotzerlab/freud). Focused on delivering robust plotting behavior, stabilizing core analytics, and improving code quality for maintainability and user value.
March 2025
1 Commits • 1 Features
Mar 1, 2025Month: 2025-03 — Documentation maintenance for freud examples focused on aligning the subproject reference with the latest external dependency state. This iteration delivered an updated Examples Documentation Reference commit: bbeed3b3bbf1f4b6c56252f2d8172963001a1a6b. No major bugs fixed this period. Overall impact: improved reproducibility and onboarding by ensuring example references are current and accurate; reduced risk of mismatches in tutorials and sample workflows. Technologies/skills demonstrated: Git/subproject management, documentation accuracy, cross-repo coordination, and emphasis on reproducible examples.
1 Commits • 1 Features
Mar 1, 2025Month: 2025-03 — Documentation maintenance for freud examples focused on aligning the subproject reference with the latest external dependency state. This iteration delivered an updated Examples Documentation Reference commit: bbeed3b3bbf1f4b6c56252f2d8172963001a1a6b. No major bugs fixed this period. Overall impact: improved reproducibility and onboarding by ensuring example references are current and accurate; reduced risk of mismatches in tutorials and sample workflows. Technologies/skills demonstrated: Git/subproject management, documentation accuracy, cross-repo coordination, and emphasis on reproducible examples.
March 2025
February 2025
14 Commits • 1 Features
Feb 1, 2025February 2025 (glotzerlab/freud) delivered core API improvements, data-handling hardening, and documentation/maintenance cleanup across the repository. Key outcomes include API unification of CorrelationFunction to a single complex double implementation, removal of the separate CorrelationFunctionDouble class, updated exports, and a fixed __repr__ that correctly reports the number of bins. Orientation data handling was strengthened by making equiv_orientations immutable and standardizing conversion to NumPy arrays within relevant functions, increasing reliability for downstream analyses. Comprehensive documentation updates and code-cleanup (docstrings for bin_centers/bin_edges, locality and diffraction docs) plus tooling hygiene (pre-commit fixes, ruff improvements, clang-tidy cleanups) reduce technical debt and improve maintainability and onboarding. Demonstrated capabilities include Python data processing, API design, NumPy usage, and adherence to software-quality practices.
February 2025
14 Commits • 1 Features
Feb 1, 2025February 2025 (glotzerlab/freud) delivered core API improvements, data-handling hardening, and documentation/maintenance cleanup across the repository. Key outcomes include API unification of CorrelationFunction to a single complex double implementation, removal of the separate CorrelationFunctionDouble class, updated exports, and a fixed __repr__ that correctly reports the number of bins. Orientation data handling was strengthened by making equiv_orientations immutable and standardizing conversion to NumPy arrays within relevant functions, increasing reliability for downstream analyses. Comprehensive documentation updates and code-cleanup (docstrings for bin_centers/bin_edges, locality and diffraction docs) plus tooling hygiene (pre-commit fixes, ruff improvements, clang-tidy cleanups) reduce technical debt and improve maintainability and onboarding. Demonstrated capabilities include Python data processing, API design, NumPy usage, and adherence to software-quality practices.
January 2025
9 Commits • 2 Features
Jan 1, 2025January 2025: Strengthened Freud Python bindings and cross-language data flow. Delivered the following: (1) Freud Python bindings: expose and stabilize MatchEnv exports (minimizeRMSD, isSimilar) with overload handling and safe namespace-based casting; (2) Environment module: Python bindings improvements and data export utilities to convert internal structures to Python lists, add conversion helpers, adjust signatures, and enhance NumPy interoperability; (3) Box class initialization robustness: cast all dimensions and tilt to float to prevent initialization errors; (4) BiMap API modernization: remove const qualifiers from key accessors to enable internal mutations. Overall impact: more robust, Python-friendly API with improved NumPy interoperability and fewer runtime errors. Technologies/skills: C++/Python bindings, overload resolution, namespace wrapping, data export interoperability with NumPy, API modernization for mutability, and thorough documentation.
9 Commits • 2 Features
Jan 1, 2025January 2025: Strengthened Freud Python bindings and cross-language data flow. Delivered the following: (1) Freud Python bindings: expose and stabilize MatchEnv exports (minimizeRMSD, isSimilar) with overload handling and safe namespace-based casting; (2) Environment module: Python bindings improvements and data export utilities to convert internal structures to Python lists, add conversion helpers, adjust signatures, and enhance NumPy interoperability; (3) Box class initialization robustness: cast all dimensions and tilt to float to prevent initialization errors; (4) BiMap API modernization: remove const qualifiers from key accessors to enable internal mutations. Overall impact: more robust, Python-friendly API with improved NumPy interoperability and fewer runtime errors. Technologies/skills: C++/Python bindings, overload resolution, namespace wrapping, data export interoperability with NumPy, API modernization for mutability, and thorough documentation.
January 2025
November 2024
15 Commits • 4 Features
Nov 1, 2024November 2024 highlights for glotzerlab/freud: delivered core module modernization and feature work with a focus on Python-native implementations, robust testing, and packaging stability. The work lays the groundwork for easier Python usage, stronger API compatibility, and improved performance for end-users.
November 2024
15 Commits • 4 Features
Nov 1, 2024November 2024 highlights for glotzerlab/freud: delivered core module modernization and feature work with a focus on Python-native implementations, robust testing, and packaging stability. The work lays the groundwork for easier Python usage, stronger API compatibility, and improved performance for end-users.
Activity
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Quality Metrics
Correctness92.2%
Maintainability93.0%
Architecture88.8%
Performance82.0%
AI Usage21.2%
Skills & Technologies
Programming Languages
C++CMakeCythonMarkdownPythonYAML
Technical Skills
API DesignBuild SystemBuild System ConfigurationC++C++ DevelopmentC++ IntegrationCI/CDCMakeClass ImplementationCode CleanupCode FormattingCode HygieneCode LintingCode OrganizationCode Refactoring
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