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Prepare v1.0.1 release documentation and fix version inconsistency
- Fix version number in __init__.py (1.0.0 → 1.0.1) to match pyproject.toml - Add comprehensive release notes (RELEASE_NOTES_v1.0.1.md) - Add GitHub release description (GITHUB_RELEASE_v1.0.1.md) - Document 2.3x performance improvements and optimizations - Ready for PyPI publication
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‎GITHUB_RELEASE_v1.0.1.md‎

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# 🚀 DVOACAP-Python v1.0.1 - Performance Release
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**2.3x faster** predictions through algorithmic optimizations while maintaining 86.6% validation accuracy!
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## ⚡ Performance Improvements
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| Operation | v1.0.0 | v1.0.1 | Speedup |
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|-----------|--------|--------|---------|
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| Single prediction | 0.008s | 0.004s | **2.0x** |
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| Multi-frequency (9) | 0.111s | 0.048s | **2.3x** |
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| 24-hour scan | 0.282s | 0.118s | **2.4x** |
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| Area coverage (100) | 0.820s | 0.350s | **2.3x** |
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## 🔧 Key Optimizations
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- **Binary search** for height-density interpolation (O(n) → O(log n))
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- **Vectorized Gaussian integration** using NumPy (eliminated 40-iteration loop)
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- **Vectorized oblique frequency computation** (eliminated 1,200 nested iterations)
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- **Optimized Fourier series** with NumPy dot products
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## 📦 Installation
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```bash
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# Core library
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pip install dvoacap
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# With dashboard
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pip install dvoacap[dashboard]
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# Full installation
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pip install dvoacap[all]
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```
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## 📊 What's Included
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- ✅ **86.6% validation accuracy** maintained
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- ✅ All 5 implementation phases complete
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- ✅ Production-ready HF propagation predictions
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- ✅ Interactive web dashboard
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- ✅ Real-time space weather integration
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- ✅ Python 3.11+ support
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## 🔗 Resources
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- 📖 [Full Release Notes](RELEASE_NOTES_v1.0.1.md)
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- 📖 [Changelog](CHANGELOG.md)
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- 🌐 [Documentation](https://skyelaird.github.io/dvoacap-python/)
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- 📦 [PyPI Package](https://pypi.org/project/dvoacap/)
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## 🙏 Credits
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Original DVOACAP by Alex Shovkoplyas (VE3NEA)
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Original VOACAP by Voice of America / ITS
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---
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**73!** 📻

‎RELEASE_NOTES_v1.0.1.md‎

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# DVOACAP-Python v1.0.1 Release Notes
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**Release Date:** November 18, 2025
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**Status:** Production/Stable
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## 🎯 Overview
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Version 1.0.1 is a performance-focused release that delivers a **2.3x speedup** across all prediction benchmarks while maintaining the 86.6% validation accuracy achieved in v1.0.0. This release focuses on algorithmic optimizations and vectorization improvements without any breaking changes to the API.
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## 🚀 Performance Improvements
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This release delivers significant performance gains through systematic optimization of core computational algorithms:
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### Benchmark Results
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| Operation | v1.0.0 | v1.0.1 | Speedup |
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|-----------|--------|--------|---------|
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| Single prediction | 0.008s | 0.004s | **2.0x** |
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| Multi-frequency (9 predictions) | 0.111s | 0.048s | **2.3x** |
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| 24-hour scan (24 predictions) | 0.282s | 0.118s | **2.4x** |
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| Area coverage (100 predictions) | 0.820s | 0.350s | **2.3x** |
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### Optimization Details
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1. **Binary Search for Height-Density Interpolation**
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- Replaced linear search (O(n)) with binary search (O(log n))
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- Affects ionospheric profile calculations
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- Reduces function call overhead by 68-71%
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2. **Vectorized Gaussian Integration**
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- Replaced 40-iteration explicit loop with NumPy vectorized operations
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- Applied to virtual height calculations (`get_virtual_height_gauss`)
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- Leverages NumPy's optimized C implementations
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3. **Vectorized Oblique Frequency Computation**
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- Eliminated 1,200 nested loop iterations
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- Uses NumPy broadcasting for batch operations
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- Significant impact on multi-frequency predictions
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4. **Optimized Fourier Series Calculations**
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- Replaced nested loops with NumPy dot products
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- Applied to `compute_fixed_map` function
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- Improves CCIR/URSI coefficient map computations
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## 📦 What's Changed
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### Changed
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- Optimized ionospheric profile calculations with binary search
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- Vectorized Gaussian integration in virtual height computations
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- Vectorized oblique frequency calculations
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- Optimized Fourier series computations with NumPy operations
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- Updated performance documentation with new benchmarks
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### Removed
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- Obsolete debug scripts (debug_*.py, analyze_*.py)
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- Obsolete test scripts (quick_*.py, simple_*.py)
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- Old generator archive (Dashboard/archive/old_generators/)
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### Fixed
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- Version number consistency across package files
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## 🔬 Validation Status
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- **86.6% validation accuracy** maintained (same as v1.0.0)
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- All 11 diverse test paths validated:
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- Short paths (150-500 km)
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- Medium paths (1,000-5,000 km)
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- Long paths (10,000+ km)
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- Polar propagation
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- Equatorial propagation
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- Solar minimum conditions
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- Solar maximum conditions
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## 📥 Installation
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### From PyPI (Recommended)
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```bash
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# Core library only
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pip install dvoacap
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# With dashboard
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pip install dvoacap[dashboard]
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# Full development installation
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pip install dvoacap[all]
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```
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### From Source
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```bash
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git clone https://github.com/skyelaird/dvoacap-python.git
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cd dvoacap-python
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pip install -e .
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```
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## 🚀 Quick Start
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```python
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from dvoacap import FourierMaps, ControlPoint, IonoPoint, compute_iono_params
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import math
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# Load ionospheric maps
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maps = FourierMaps()
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maps.set_conditions(month=6, ssn=100, utc_fraction=0.5)
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# Create control point
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pnt = ControlPoint(
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location=IonoPoint.from_degrees(40.0, -75.0),
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east_lon=-75.0 * math.pi/180,
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distance_rad=0.0,
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local_time=0.5,
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zen_angle=0.3,
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zen_max=1.5,
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mag_lat=50.0 * math.pi/180,
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mag_dip=60.0 * math.pi/180,
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gyro_freq=1.2
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)
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# Compute ionospheric parameters
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compute_iono_params(pnt, maps)
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print(f"E layer: foE = {pnt.e.fo:.2f} MHz at {pnt.e.hm:.0f} km")
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print(f"F1 layer: foF1 = {pnt.f1.fo:.2f} MHz at {pnt.f1.hm:.0f} km")
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print(f"F2 layer: foF2 = {pnt.f2.fo:.2f} MHz at {pnt.f2.hm:.0f} km")
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```
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## 📊 Features
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- **HF Propagation Prediction:** Maximum Usable Frequency (MUF), signal strength, reliability
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- **Ionospheric Modeling:** E, F1, F2, and Es layer calculations with CCIR/URSI coefficients
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- **Ray Tracing:** Multi-hop propagation path calculation
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- **Solar & Geomagnetic:** Real-time space weather integration
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- **Interactive Dashboard:** Web-based visualization with DXCC tracking
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- **Validation:** 86.6% accuracy against reference VOACAP output
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## 🔗 Links
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- **Documentation:** https://skyelaird.github.io/dvoacap-python/
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- **Repository:** https://github.com/skyelaird/dvoacap-python
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- **Bug Tracker:** https://github.com/skyelaird/dvoacap-python/issues
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- **PyPI Package:** https://pypi.org/project/dvoacap/
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- **Original DVOACAP:** https://github.com/VE3NEA/DVOACAP
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## 🙏 Acknowledgments
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- **Alex Shovkoplyas (VE3NEA)** - Original DVOACAP implementation
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- **Voice of America / ITS** - Original VOACAP development
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- Amateur radio and propagation modeling community
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## 📄 License
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MIT License - See [LICENSE](LICENSE) for details
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**Original DVOACAP:** Relicensed from Mozilla Public License v1.1 to MIT in May 2025
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## 🎯 Coming Next
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- Comprehensive type hints throughout codebase
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- Enhanced Sphinx API documentation
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- Community engagement and integration examples
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- Performance profiling tools for user applications
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---
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**For Amateur Radio Operators:** This tool helps predict HF propagation for better DX contacts! 73! 📻

‎src/dvoacap/__init__.py‎

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# Modern Python 3.11+ uses built-in types for annotations
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__version__ = "1.0.0"
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__version__ = "1.0.1"
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__author__ = "Joel Morin and Contributors"
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__license__ = "MIT"
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