October 2025 performance summary for lsst-ts/donut_viz: Focused on robustness, data integrity, and documentation to strengthen reliability and maintainability of visualizations and data ingestion. Delivered three bug fixes and two robustness improvements that reduce runtime errors with incomplete datasets and improve user trust through clear version-history documentation. Key impacts: - Reduced downstream errors in plotting and data ingestion by adding defensive checks and graceful handling for missing data. - Improved transparency and triage ability with updated version history docs for v2.3.1 and v2.3.3. - Strengthened dashboard reliability and consistency for end-users and analysts. Technologies/skills demonstrated: - Defensive programming in Python data visualization pipelines - Defensive data handling and conditional checks for missing columns/data - Documentation and maintainability through targeted commits Top achievements: - Documentation updates: Donut_viz Version History for v2.3.1/v2.3.3 (commits 77affc7652e8cc27ae5c08d3ee1abe90c6ca93f0 and 6065ac898537c0d3b56edc21b4a68328ddb7a0f7) - Plot robustness: Handle missing 'used' column in plotting (commit 3f5146ebe8ff9e80ca8297d792cb9e32adae82a1) - Intra-focal data robustness: Warn and skip processing when intra-focal data is missing (commit 8ccbb03bd5a476d71eea72b5b45950bfc07b8d96)

Concise monthly summary for 2025-09 focusing on lsst-ts/donut_viz: - Delivered feature-rich donut visualization enhancements with robust handling of historical data, including per-detector brightest donut selection, centroid filtering, donut count limits, and integration of new plot tasks. - Expanded metadata coverage by propagating band information into AggregateZernikeTablesTask metadata and updated tests to validate presence/absence of band metadata across science sensors. - Updated documentation to reflect changes in donut_viz versions (2.2.1 and 2.2.3), improving traceability for users and maintainers. - Fixed several bugs related to plotting and data handling to improve reliability when using legacy test data and ensure correct plot labeling. - Demonstrated strong technical execution across visualization, metadata management, testing, and documentation, driving measurable improvements in reliability, traceability, and user-facing capabilities.

August 2025 performance summary: Focused on delivering features that improve donut data quality, processing reliability, and visual analytics across ts_wep and donut_viz, with robust testing and pipeline integrations to reduce regressions and enable downstream business insights. Key features delivered: - ts_wep: DonutSizeCorrelator integration and donut diameter estimation workflow. Introduced DonutSizeCorrelator, integrated into the donut processing workflow, propagated donut radius through catalog metadata, updated donut-related components (cutOutDonutsBase, DonutStampSelectorTask), and added comprehensive tests. - ts_wep: Zernike calculation cleanup and alignment of related tests. Refactored CalcZernikesTask by removing unused pixel-edge parameters and updated tests to reflect new output shape/columns. - ts_wep: Misc utilities improvement. Added median option to binArray with unit tests covering mean/median binning, edge cases, and shape handling. - donut_viz: PlotDonutFitsTask visualization and pipeline integration. Introduced PlotDonutFitsTask, integrated into donutVizCwfsPipeline, RA Danish pipeline, and TIE RA pipeline; enhanced plotting with labels and metadata; propagated Zernike 'used' flag; updated docs and lint settings. Major bugs fixed: - Stabilized donut processing with removal of unused parameters in Zernike calculations and updated tests to match new outputs; ensured radius metadata is consistently propagated for downstream analyses; addressed test pipeline discrepancies during integration of new visualization task. Overall impact and accomplishments: - Significantly improved donut data quality and traceability by propagating radius and Zernike usage metadata through catalogs and plots, enabling more accurate downstream analyses and reporting. - Expanded test coverage and pipeline reliability across two repos, reducing regressions and accelerating development cycles. - Improved data visualization capabilities with PlotDonutFitsTask, providing clearer donut stamp insights for QA and presentations. Technologies/skills demonstrated: - Python-based data processing, class design (DonutSizeCorrelator), and workflow integration. - Zernike computations, task refactors, and output shape adjustments with corresponding test updates. - Unit/integration testing (pytest), test pipelines, and linting/documentation improvements. - Metadata propagation, charting/plotting enhancements, and cross-repo collaboration for pipeline consistency.

June 2025 performance summary: Focused on stabilizing data processing workflows and expanding configurable donut analysis features across ts_wep and donut_viz. Delivered robust WCS handling, a configurable donut stamp selection bypass, enhanced donut radius fitting, and CWFS visualization enhancements, while stabilizing tests and improving release documentation. These changes improve data product reliability, pipeline configurability, and cross-pipeline diagnostics, delivering business value through more robust analyses, faster onboarding, and clearer release notes.

In April 2025, the team advanced donor donut analysis capabilities and pipeline robustness across lsst-ts/ts_wep and lsst-ts/donut_viz. Delivery focused on core estimation features, robust data handling, streamlined CWFS workflows, and plotting improvements, with release notes documenting changes.

March 2025 monthly summary for lsst-ts/donut_viz: Delivered new CWFS donut visualization capabilities, stabilized plotting logic, and expanded test coverage while maintaining code quality. The work enhances data visualization for CWFS analyses, supports S11-only plotting, and improves overall reliability of plotting workflows in the cwfsWcsCatalogPipeline. Documentation updates reflect the new mode and configuration options, ensuring clear auditability for QA and users.

February 2025 was focused on delivering robust donut-processing capabilities, improving data structures, and enabling richer visualization while stabilizing tests and ensuring compatibility across TSWEP components. Key work spanned three repositories: lsst-ts/ts_wep, lsst-ts/donut_viz, and lsst-ts/ts_externalscripts. Highlights include edge-aware donut processing with edgeMargin across generation and catalog tasks, deterministic Latiss Zernike testing, a new donut plot visualization task, and WEP alignment data processing upgrades with QTable data models and improved code quality. A DM-49046 compatibility bug fix was implemented to ensure compatibility with ts_wep 13.4.0.

January 2025 monthly summary for lsst-ts/ts_wep: Focused on hardening the Donut Direct Detect workflow and cleaning up donut-related code. Delivered robust edge-case handling, improved test coverage, and formatting consistency to boost reliability and maintainability, enabling smoother production pipelines and faster iteration.

December 2024: Implemented Rotator AOS Sequence Test Coverage in MTScheduler for lsst-ts/ts_config_ocs. Added a dedicated test case to validate scheduler behavior under an AOS sequence, implemented in commit 997bb4b8c27d975600f7721e70bacf2949b71155. This work strengthens validation of rotation workflows and reduces production risk by catching edge-case issues earlier.