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DVOACAP-Python v0.9.0 - Beta Release

🎉 What's New

DVOACAP-Python is now feature-complete with 86.6% validation accuracy against reference VOACAP data!

This beta release marks a major milestone: the core propagation engine is complete and ready for early adopters, developers, and testers.

📦 Installation

For Developers and Library Users:

pip install dvoacap

For Dashboard Users (includes web interface):

pip install dvoacap[dashboard]

Using Docker:

docker pull skyelaird/dvoacap-dashboard:0.9.0
docker run -p 8000:8000 skyelaird/dvoacap-dashboard:0.9.0

✨ Core Features

Complete Propagation Engine (Phases 1-5)

✅ Phase 1: Path Geometry

  • Great circle path calculations
  • Control point determination
  • Distance and bearing computations

✅ Phase 2: Solar & Geomagnetic

  • Solar position calculations
  • Sunspot number integration
  • Geomagnetic field modeling

✅ Phase 3: Ionospheric Modeling

  • CCIR/URSI coefficient loading
  • Ionospheric profile generation
  • Critical frequency calculations
  • F2 layer foF2 and M(3000)F2 modeling

✅ Phase 4: MUF Calculations

  • Maximum Usable Frequency (MUF) computation
  • Frequency of Optimum Traffic (FOT) determination
  • Multi-hop propagation support
  • Layer-specific MUF calculations

✅ Phase 5: Signal Predictions

  • Signal power calculations
  • D-layer and E-layer absorption
  • Antenna gain modeling
  • Noise floor integration
  • Signal-to-Noise Ratio (SNR) predictions
  • Reliability calculations

Production-Ready Library

  • 📘 Clean Python API for programmatic access
  • 📊 All required CCIR/URSI ionospheric data files included
  • 🧪 Comprehensive test suite with 86.6% validation rate
  • 📚 Example code and documentation
  • 🔄 Compatible with Python 3.11, 3.12, 3.13

Interactive Dashboard

  • 🌐 Flask web server with real-time predictions
  • ☀️ Space weather integration (NOAA SWPC)
  • 🌍 DXCC entity tracking
  • 🐳 Docker support for easy deployment
  • 📡 Point-to-point propagation analysis

📊 Validation Results

  • 226 of 261 tests passing (86.6% accuracy)
  • Validated against reference VOACAP outputs
  • Real-world validation with PSKReporter data
  • Comprehensive test coverage across 11 diverse scenarios:
    • Short paths (US East Coast, Europe)
    • Medium paths (Transatlantic, US-Japan)
    • Long paths (Antipodal, Australia)
    • Equatorial paths
    • Polar/Arctic paths
    • Solar maximum conditions
    • Solar minimum conditions

Known Differences from Reference

The 35 failing tests show consistent patterns:

  • Most failures are in low-reliability scenarios (<10%)
  • Some discrepancies in E-layer absorption calculations
  • Minor differences in auroral zone modeling
  • See PHASE5_VALIDATION_REPORT.md for details

📚 Documentation

🔮 What's Coming in v1.0 (December 2025)

Dashboard Enhancements

  • Enhanced propagation charts (REL/SDBW/SNR over 24 hours)
  • Propagation wheel visualization
  • Mini planner for DXCC targeting
  • Best frequency recommendations
  • Improved UI/UX

Library Improvements

  • Performance optimizations
  • Complete API documentation
  • Additional usage examples
  • Enhanced error handling

See V1_RELEASE_PLAN.md for the complete roadmap.

🚀 Quick Start

Basic Usage

from dvoacap import ControlPoint, FourierMaps, IonosphericProfile, MufCalculator

# Define transmitter and receiver
tx = ControlPoint(latitude=40.0, longitude=-75.0)  # Philadelphia
rx = ControlPoint(latitude=51.5, longitude=-0.1)   # London

# Set ionospheric conditions
fourier_maps = FourierMaps()
fourier_maps.set_conditions(
    month=6,           # June
    ssn=100,           # Sunspot number
    utc_fraction=12.0  # Noon UTC
)

# Calculate ionospheric profile at midpoint
profile = IonosphericProfile()
profile.calculate_profile(
    control_point=tx.midpoint(rx),
    fourier_maps=fourier_maps
)

# Calculate MUF
muf_calc = MufCalculator()
muf = muf_calc.calculate_muf(tx, rx, profile)
print(f"MUF: {muf:.2f} MHz")

Running the Dashboard

# Install with dashboard dependencies
pip install dvoacap[dashboard]

# Run the server
cd Dashboard
python server.py

# Open browser to http://localhost:8000

📦 What's Included

Python Package (dvoacap)

  • 14 core modules implementing full propagation engine
  • 24 ionospheric data files (CCIR/URSI coefficients)
  • Type hints for better IDE support
  • Comprehensive docstrings

Dashboard Application

  • Flask web server
  • React-based frontend (planned for v1.0)
  • RESTful API endpoints
  • Docker deployment support

🙏 Acknowledgments

  • Alex Shovkoplyas (VE3NEA) - Original DVOACAP Delphi implementation
  • NOAA Space Weather Prediction Center - Real-time space weather data
  • Amateur radio community - Testing, feedback, and validation data
  • PSKReporter - Real-world propagation validation data

📝 Release Notes

Changed

  • Fixed license metadata format in pyproject.toml (SPDX expression)
  • Improved package building and distribution

Added

  • Comprehensive PyPI release workflow (GitHub Actions)
  • Detailed PyPI setup guide
  • Release automation documentation

Technical Details

  • Source Distribution: 1.4 MB (includes all data files)
  • Wheel Package: 528 KB
  • Python Version: ≥3.11
  • Dependencies: numpy>=1.20.0
  • Optional Dependencies: flask, flask-cors, requests (for dashboard)

🐛 Known Issues

  • Dashboard UI is functional but basic (v1.0 will have major improvements)
  • Some edge cases in E-layer absorption modeling
  • Performance could be optimized for batch calculations
  • See Known-Issues in the wiki for complete list

🔗 Links

💬 Feedback Welcome!

This is a beta release. Your feedback is valuable:

  • Report bugs via GitHub Issues
  • Suggest features via Discussions
  • Share your use cases
  • Contribute code via Pull Requests

73 de VE1ATM 📻

Happy propagation predictions!