
Over three months, J. Martin enhanced the MaCh3 and MaCh3Tutorial repositories by developing particle-level plotting features and YAML-driven configuration for kinematic data visualization. He refactored core C++ APIs to support 2D histograms, streamlined sub-event handling, and improved mass data retrieval, enabling more reproducible and maintainable scientific analysis workflows. Martin updated documentation and build configuration using CMake and Markdown, ensuring clear onboarding and reducing misconfiguration risk. His work integrated data analysis, error handling, and code refactoring, resulting in more flexible plotting, consistent API usage, and robust data management across both repositories, demonstrating depth in scientific computing and software engineering.

June 2025 monthly summary for MaCh3 and MaCh3Tutorial: delivered major enhancements to plotting APIs, refined sub-event handling, updated mass data references, and introduced YAML-driven configuration for plotting and fitting workflows. The work focused on business value: richer data visualizations, reproducible analysis, and maintainable APIs that reduce errors and speed up feature delivery.
June 2025 monthly summary for MaCh3 and MaCh3Tutorial: delivered major enhancements to plotting APIs, refined sub-event handling, updated mass data references, and introduced YAML-driven configuration for plotting and fitting workflows. The work focused on business value: richer data visualizations, reproducible analysis, and maintainable APIs that reduce errors and speed up feature delivery.
This month focused on delivering end-to-end particle-level plotting capabilities across MaCh3Tutorial and MaCh3, establishing a cohesive foundation for particle-level data visualization, testing, and analysis. The work bridges tutorial sample generation with core plotting features, enabling richer physics exploration and faster feature iteration.
This month focused on delivering end-to-end particle-level plotting capabilities across MaCh3Tutorial and MaCh3, establishing a cohesive foundation for particle-level data visualization, testing, and analysis. The work bridges tutorial sample generation with core plotting features, enabling richer physics exploration and faster feature iteration.
April 2025: Documentation update to reflect the new CMake Build_NDGAr option for DUNE/MaCh3_DUNE. No code changes; updated README.md and build documentation to ensure accurate guidance for developers configuring builds. This supports faster onboarding and reduces misconfiguration risk.
April 2025: Documentation update to reflect the new CMake Build_NDGAr option for DUNE/MaCh3_DUNE. No code changes; updated README.md and build documentation to ensure accurate guidance for developers configuring builds. This supports faster onboarding and reduces misconfiguration risk.
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