Module Documentation

This section provides detailed documentation for each module in the AnalysisG framework, organized by functionality.

Overview

The AnalysisG framework is organized into several key modules, each providing specific functionality for high-energy physics analysis with graph neural networks.

Core Modules

Core Module - Fundamental building blocks and base templates
Events Module - Event processing for various physics analyses
Graphs Module - Graph construction from physics events
Metrics Module - Performance metrics and evaluation
Models Module - Neural network model implementations

Infrastructure

Infrastructure Modules - Low-level infrastructure components
Python-C++ Interface - Python-C++ interface via Cython
Templates Module - Code templates and examples

Module Relationships

The modules have the following dependency structure:

Core (templates)
├── Events (inherits from event_template)
├── Graphs (inherits from graph_template)
├── Models (inherits from model_template)
└── Metrics (inherits from metric_template)

Infrastructure
├── Used by all modules
└── Provides low-level functionality

Python Interface
└── Wraps all modules for Python access

Templates
└── Provides examples for all module types