
During April 2025, Demaross developed and integrated a Muon Selection Workflow for the DUNE/ndlar_flow repository, targeting both Monte Carlo and real data. Leveraging Bash scripting and YAML configuration, Demaross automated the selection process and introduced a new stage in the h5flow pipeline for rock muon identification. This approach reduced manual setup, improved reproducibility, and streamlined end-to-end muon analysis across diverse datasets. The work demonstrated effective use of data processing configuration and shell scripting, aligning with project goals for better configuration management. No bugs were logged, reflecting a focused and well-executed feature delivery within a short development period.

April 2025 monthly summary for DUNE/ndlar_flow focused on feature delivery and pipeline enhancements. Delivered a Muon Selection Workflow for MC and real data by introducing shell scripts and YAML configuration to drive muon selection, and added a new selection stage to the h5flow processing pipeline for rock muon identification. This work improves reproducibility, reduces manual setup, and streamlines end-to-end muon analyses across simulated and real datasets. No major bug fixes were logged for this repository this month. Overall impact includes accelerates data processing for muon studies, better configuration management, and alignment with the project roadmap. Technologies demonstrated include shell scripting, YAML configuration, h5flow pipeline integration, and git-based version control.
April 2025 monthly summary for DUNE/ndlar_flow focused on feature delivery and pipeline enhancements. Delivered a Muon Selection Workflow for MC and real data by introducing shell scripts and YAML configuration to drive muon selection, and added a new selection stage to the h5flow processing pipeline for rock muon identification. This work improves reproducibility, reduces manual setup, and streamlines end-to-end muon analyses across simulated and real datasets. No major bug fixes were logged for this repository this month. Overall impact includes accelerates data processing for muon studies, better configuration management, and alignment with the project roadmap. Technologies demonstrated include shell scripting, YAML configuration, h5flow pipeline integration, and git-based version control.
Overview of all repositories you've contributed to across your timeline