February 2026 monthly summary for gafusion/omas focusing on delivering stability, a critical bug fix, and a clean release cycle. The month emphasized improving numerical accuracy in equilibrium computations and aligning with the project’s release process for reliable deployment.

January 2026 monthly summary focusing on delivering packaging reliability, automation, and cross-repo compatibility across two repositories. Key outcomes include a new IMAS Composer Python library with a conda-forge packaging recipe, hardened packaging metadata and versioning, an automated release workflow with extended regression CI for newer Python versions, dependency simplification to reduce maintenance, and targeted compatibility fixes to ensure future-proof operation. These efforts collectively enable reliable data conversion, streamlined releases, and lower installation friction while expanding Python-version reach.

December 2025 (2025-12) focused on delivering business-value improvements in gafusion/omas through numpy 2.0 compatibility for numerical integration, stabilization of data handling in ec_launcher_active_hardware, and a hardened test/CI environment. Key changes include consolidation of numerical integration updates to align trapz and cumulative_trapezoid with numpy 2.0 and SciPy changes, removal of unused imports, and robust import handling; revert of recent data trimming in ec_launcher_active_hardware to restore consistent D3D machine mappings; and a strengthened test suite with deprecation warning management (matplotlib, pyparsing) and acceptance of packrat warnings to minimize noise and improve test reliability. These changes reduce maintenance friction, prevent runtime regressions, and improve platform reliability for downstream users.

November 2025 monthly summary for gafusion/omas: Deliverables focused on robust data processing, improved observability, and test hygiene to support reliable product decisions and faster CI feedback.

Month: 2025-10 — gafusion/omas: Delivered MDSplus Data Precision Enhancement and Dependency Cleanup. Enhanced data precision by converting float32 arrays to float64 in MDSplus data handling and removed an unused numpy import to streamline code and reduce dependencies. Included a small fix to improve stability. Commit references: 2d1b0a63ccba53650895b78a2154eb0cb2f7a82d; 500dcf0220ed9efd8513429976b86628a797af97. This work improves data fidelity across MDSplus pipelines, reduces dependency footprint, and enhances maintainability. Technologies used include Python, NumPy, MDSplus integration, code cleanup, and dependency management.

September 2025 monthly summary for gafusion/omas focusing on delivering high-value features, stabilizing data workflows, and enhancing performance and plotting reliability for downstream analysis.

In August 2025, gafusion/omas delivered key physics accuracy improvements and profile analysis enhancements. Major work included stabilizing magnetic field calculations (B_field_r, B_field_tor, B_field_z) with added tests, and expanding volume/equilibrium profile capabilities and OMFIT comparison workflows. These changes improve simulation reliability, accuracy of magnetic field physics, and data analysis workflows, supported by updated dependencies and higher-resolution sampling. Collectively, the work enhances trust in results, accelerates iteration cycles, and strengthens the platform for physics-driven decision making.

July 2025 monthly summary for gafusion/omas: - Key features delivered, major bugs fixed, and measurable impact across machine mappings data integration, testing, and data loading for DIII-D, with an emphasis on IMAS compatibility and validation workflows. - Focused on business value via improved onboarding of new machines, more reliable magnetic equilibrium analyses, and more automated validation pipelines.

June 2025 performance summary for gafusion/omas: Delivered two high-impact capabilities that enhance data quality, reproducibility, and workflow efficiency. The work emphasizes business value by tightening core data filtering, simplifying and hardening FUSE data exports, and enabling safer, repeatable data access for downstream analytics.

May 2025 monthly summary for gafusion/omas focusing on MDSplus integration, caching, and multi-server capabilities. Delivered a robust connection and tree caching architecture, migrated to library-backed tree handling, and introduced multi-server support. This work improves cross-server data access, reduces redundant tree openings, and enhances scalability and maintainability.

Summary for 2025-03 (gafusion/omas): Delivered key features and fixed critical bugs, improving beam characterization, reliability, and future configurability. The work emphasizes business value, maintainability, and technical excellence.

February 2025: Focused on increasing accuracy and flexibility for ITER-aligned operations in OMAS. Delivered two major features (DIII-D launcher plotting/coordinate alignment and DIII-D wall function cleanup with EFIT tree configurability), performed targeted refactors to remove fragile hard-coded data paths, and clarified plotting conventions. Result: precise launcher representations, configurable wall-function behavior, and reduced maintenance burden.

January 2025 monthly summary for gafusion/omas. Focused on stabilizing test infrastructure and ensuring plotting accuracy amid library changes. No new user-facing features delivered this month; primary value comes from reliability improvements that reduce CI failures and improve plotting consistency.

November 2024 monthly summary for gafusion/omas focusing on feature delivery and reliability improvements. Implemented Toray bhalf parameter integration into ec_launcher_active_hardware for D3D OMAS mappings, and fixed key reliability issues to ensure robust import of CodeParameters and correct dispersion data access. These changes enhanced parameter accuracy, stability, and future readiness for Toray bhalf-driven configurations.