Refactor fmpy naming conventions and add comprehensive documentation

Summary

This PR improves the readability, maintainability, and documentation of the Financial Module (fmpy) computation code through systematic variable naming refactoring and comprehensive documentation additions.

Changes

1. Variable Naming Convention Refactoring

Established and applied consistent naming patterns across the FM computation module:

• Index/iterator variables: Use _i suffix (e.g., profile_i, layer_i, val_i)
• Count/length variables: Use _count suffix (e.g., children_count, node_val_count)
• Contextual prefixes: Add descriptive prefixes for clarity (e.g., profile_, layer_, node_)
• Constant clarity: Renamed EXTRA_VALUES to EXTRA_SIDX_COUNT for better semantic meaning

Files modified:

• common.py: Updated constant naming
• compare.py: Updated import references
• compute_sparse.py: Refactored loop variables and parameters
• back_allocation.py: Refactored allocation variables
• stream_sparse.py: Refactored stream handling variables
• manager.py: Refactored event loop counter

2. Comprehensive Code Documentation

Added extensive inline documentation to improve code maintainability:

• Module-level docstrings explaining the FM computation architecture
• Detailed function comments documenting the algorithm flow
• CSR-like sparse storage model explanation
• Bottom-up level traversal with aggregation and back allocation logic
• Profile application strategies (per-layer vs cross-layer)
• Back allocation rules and extras handling
• Stream I/O format and parsing state machine

3. Technical Documentation (TECHNICAL.md)

Created comprehensive technical documentation covering:

• Detailed CSR-inspired sparse storage format
• Data structure documentation (nodes, compute_idx, extras)
• Complete computation flow with algorithms
• Aggregation and back allocation explanations
• Stream I/O format specification
• Memory management and performance tips
• Debugging guidance

4. User Guide (README.md)

Created user-friendly documentation including:

• Quick start examples (Python API and CLI)
• Configuration options (allocation rules, net loss, memory)
• Input file requirements and output format explanation
• Supported financial terms
• Performance optimization tips
• Troubleshooting guide
• Architecture overview

5. Code Quality

• Applied PEP8 formatting standards
• Code cleanup and consistency fixes

Impact

These changes significantly improve the maintainability and accessibility of the FM computation module without altering its functionality. The consistent naming conventions make the code easier to understand, while the comprehensive documentation provides both technical details for developers and practical guidance for users.