Scientific Analysis & Reporting

Instructions

1. Project Exploration & Domain Mapping

Before analyzing data, map the scientific context of the repository:

• Dependency & Logic Scan: Check pyproject.toml for libraries and main.py (or equivalent) for the execution flow.
• Consult References: Check the references/ directory for background materials, standard definitions (e.g., NEMA, IEC), or methodology specifications. Use these files to define terms and expected behaviors.
• Identify Physical Models: Locate the core logic defining the system (constants, equations like Inverse Square Law, statistical models).
• Locate Data: All experimental and simulation data is stored in data/ with comprehensive filenames (e.g., data/radial_positions_10min_run.csv). Always inspect file headers to confirm units and column definitions.
• Locate Assets: All assets like images or plots are stored in assets/ with comprehensive filenames.