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Welcome to the DVOACAP-Python documentation wiki! This wiki provides comprehensive guides, tutorials, and reference materials for using and developing with DVOACAP-Python.
DVOACAP-Python is a modern Python port of the DVOACAP HF propagation prediction engine, originally written in Delphi/Pascal by Alex Shovkoplyas (VE3NEA). This project provides an accessible, well-documented, and maintainable Python implementation of the VOACAP ionospheric propagation model.
Key Features:
- Predicts HF radio propagation conditions
- Calculates Maximum Usable Frequency (MUF), signal strength, and reliability
- NEW: VOACAP-style propagation maps with Maidenhead grid overlay
- NEW: Mode presets for WSPR, FT8, CW, SSB with proper bandwidth parameters
- Includes interactive web dashboard for visualization
- Integrates with modern Python scientific stack (NumPy, SciPy, Matplotlib)
- Validated against original VOACAP reference data
- Getting Started - Installation, basic usage, and first prediction
- Quick Examples - Common use cases and code snippets
- Architecture Overview - Understanding the 5-phase structure
- API Reference - Core classes, methods, and data structures
- Dashboard Guide - Web interface setup and usage
- Propagation Maps - NEW! VOACAP-style coverage maps
- Integration Guide - Using DVOACAP in your applications
- Validation Status - Current testing state and accuracy metrics
- Comparison Guide - DVOACAP vs VOACAP vs ITU P.533
- Known Issues - Current limitations and bugs
- Contributing Guide - How to contribute to the project
- Development Setup - Setting up your development environment
- Testing Guide - Running and writing tests
- Common Issues - Solutions to frequent problems
- FAQ - Frequently asked questions
- Performance Tips - Optimizing prediction speed
🎉 Production Ready - v1.0.1 Released! 🎉
All 5 Development Phases Complete - 86.6% Validation Accuracy + 2.3x Performance Boost
- ✅ Phase 1: Path Geometry
- ✅ Phase 2: Solar & Geomagnetic
- ✅ Phase 3: Ionospheric Profiles
- ✅ Phase 4: Raytracing
- ✅ Phase 5: Signal Predictions (86.6% validation pass rate across 11 diverse test paths)
- ✅ NEW in v1.0.1: Performance optimization - 2.3x faster!
DVOACAP-Python has reached production-ready status with comprehensive HF propagation prediction capabilities, validated against VOACAP reference data, optimized for performance (2.3x speedup in v1.0.1), and ready for real-world amateur radio and professional applications.
See the Architecture page for detailed module status.
- Main Repository: github.com/skyelaird/dvoacap-python
- Issues: github.com/skyelaird/dvoacap-python/issues
- Original DVOACAP: github.com/VE3NEA/DVOACAP
DVOACAP-Python is released under the MIT License. See the LICENSE file for details.
- Alex Shovkoplyas (VE3NEA) - Original DVOACAP implementation
- Voice of America / ITS - Original VOACAP development
- Amateur radio and propagation modeling community
Amateur Radio Operators: This tool is designed for HF propagation prediction to help you make better contacts! 73! 📻