Merge pull request #118 from skyelaird/claude/fix-disconnection-012KGBEhnNnzfGrWTytHE83a

Fix disconnection issue

Author: skyelaird

NEXT_STEPS.md

@@ -1,14 +1,14 @@
 # DVOACAP-Python: Next Steps Plan
 
-**Date:** 2025-11-15 (Updated)
-**Project Status:** 85% Complete - Target Achieved (Phase 5 validation at 86.6% across 11 test cases)
-**Current Branch:** claude/phase-5-progress-check-01VNZuWkhy7pLfd4qrVAAx2n
+**Date:** 2025-11-18 (Updated)
+**Project Status:** v1.0.1 Production Release - 86.6% validation accuracy, 2.3x performance improvement
+**Current Version:** v1.0.1
 
 ---
 
 ## Executive Summary
 
-DVOACAP-Python has successfully completed Phases 1-5 with **86.6% validation pass rate** across 11 diverse test cases (exceeding the 85% target, approaching 90% stretch goal). The 8-week roadmap (Weeks 1-8) has been completed, along with test coverage expansion. Remaining work focuses on performance optimization and preparing for public release.
+DVOACAP-Python v1.0.1 is production-ready with **86.6% validation pass rate** across 11 diverse test cases and **2.3x performance improvement** over v1.0.0. All 5 implementation phases are complete. The 8-week roadmap (Weeks 1-8) has been completed, including performance optimization (v1.0.1). Remaining work focuses on documentation polish and preparing for PyPI public release.
 
 ---
 
@@ -40,9 +40,9 @@ DVOACAP-Python has successfully completed Phases 1-5 with **86.6% validation pas
 
 ### Current Focus 🎯
 - ~~**Expand Test Coverage**~~ ✅ **COMPLETE** - 11 test cases, 86.6% pass rate
-- **Improve Pass Rate:** Continue toward 90% validation goal (current: 86.6%)
-- **Performance Optimization:** Profile and optimize bottlenecks
-- **Public Release Preparation:** PyPI packaging, community building
+- ~~**Performance Optimization**~~ ✅ **COMPLETE** - v1.0.1: 2.3x speedup achieved
+- **Documentation Polish:** Comprehensive type hints, Sphinx API docs, usage examples
+- **Public Release Preparation:** PyPI packaging, community building, integration guides
 
 ### Key Resources
 - **Active Documentation:**
@@ -368,7 +368,29 @@ DVOACAP-Python has successfully completed Phases 1-5 with **86.6% validation pas
 
 ---
 
-## Priority 6: Performance Optimization (Future)
+## ~~Priority 6: Performance Optimization~~ ✅ **COMPLETED (v1.0.1)**
+
+**Status:** Performance optimization complete with **2.3x speedup** achieved (November 2025)
+
+**Completed Work:**
+- ✅ Profiled prediction engine and identified bottlenecks
+- ✅ Optimized ionospheric profile calculations (binary search: O(n) → O(log n))
+- ✅ Vectorized Gaussian integration (eliminated 40-iteration loop)
+- ✅ Vectorized oblique frequency computation (eliminated 1,200 nested iterations)
+- ✅ Optimized Fourier series with NumPy dot products
+- ✅ Function call reduction: 68-71% fewer calls
+
+**Performance Metrics:**
+- Single prediction: 0.008s → 0.004s (2x faster)
+- Multi-frequency (9 predictions): 0.111s → 0.048s (2.3x faster)
+- 24-hour scan: 0.282s → 0.118s (2.4x faster)
+- Area coverage (100 predictions): 0.82s → 0.35s (2.3x faster)
+
+**Documentation:** See CHANGELOG.md v1.0.1 release notes
+
+---
+
+## ~~Priority 6 (Original): Performance Optimization (Future)~~ (Details below for reference)
 
 ### Profiling
 
@@ -444,13 +466,13 @@ DVOACAP-Python has successfully completed Phases 1-5 with **86.6% validation pas
 ## Success Metrics
 
 ### Technical Quality
-- [x] Phases 1-4: Validated and complete
-- [x] Phase 5: >80% reference validation pass rate (83.8% achieved)
+- [x] Phases 1-5: Validated and complete (100%)
+- [x] Phase 5: >85% validation pass rate (86.6% achieved, exceeds target)
 - [x] Real-world validation: WSPR/PSKReporter integration complete
-- [ ] **Remaining:** Expand test coverage to 7+ diverse paths (85-90% target)
-- [ ] Code coverage: >80%
+- [x] Test coverage: 11 diverse test paths (short/long/polar/equatorial/solar)
+- [x] Performance: 0.004s/prediction (v1.0.1, 2.3x faster than v1.0.0)
 - [x] No crashes for valid inputs
-- [ ] Performance: <1 sec/prediction (profiling needed)
+- [ ] **Remaining:** Code coverage >80%, type hints throughout
 
 ### Documentation
 - [ ] API documentation complete (Sphinx)

README.md

@@ -4,17 +4,18 @@
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 ![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)
-![Version](https://img.shields.io/badge/version-1.0.0-blue)
+![Version](https://img.shields.io/badge/version-1.0.1-blue)
 ![Status](https://img.shields.io/badge/status-production%20ready-brightgreen)
 ![Validation](https://img.shields.io/badge/validation-86.6%25-brightgreen)
+![Performance](https://img.shields.io/badge/performance-2.3x%20faster-orange)
 [![CI](https://github.com/skyelaird/dvoacap-python/actions/workflows/validation.yml/badge.svg)](https://github.com/skyelaird/dvoacap-python/actions/workflows/validation.yml)
 
 ## 🎯 About
 
 DVOACAP-Python is a modern Python port of the [DVOACAP](https://github.com/VE3NEA/DVOACAP) HF propagation prediction engine, originally written in Delphi/Pascal by Alex Shovkoplyas (VE3NEA). This project aims to provide an accessible, well-documented, and maintainable Python implementation of the VOACAP ionospheric propagation model.
 
 **Original DVOACAP by:** Alex Shovkoplyas, VE3NEA
-**Python Port:** Production Ready (v1.0.0, November 2025)
+**Python Port:** Production Ready (v1.0.1, November 2025) - 2.3x faster than v1.0.0
 
 ## ⚡ Quick Start
 
@@ -158,7 +159,7 @@ See [Dashboard/ISSUE_MULTI_USER_WEB_APP.md](Dashboard/ISSUE_MULTI_USER_WEB_APP.m
 
 ## 📊 Project Status
 
-**Status: v1.0.0 Production Release** - 86.6% validation accuracy across 11 diverse test paths
+**Status: v1.0.1 Production Release** - 86.6% validation accuracy across 11 diverse test paths, 2.3x performance improvement
 
 ### ✅ Completed Modules
 
@@ -203,16 +204,24 @@ See [Dashboard/ISSUE_MULTI_USER_WEB_APP.md](Dashboard/ISSUE_MULTI_USER_WEB_APP.m
   - ✓ Real-world validation with PSKReporter/WSPR integration
   - *Source: VoaCapEng.pas, AntGain.pas, NoiseMdl.pas*
 
-### 🚧 In Progress
+### ⚡ Performance (v1.0.1)
 
-- **Performance optimization and profiling** - Active development on this branch
-  - Identifying and optimizing hot paths in prediction engine
-  - Profiling Fourier map interpolation, ionospheric calculations, ray tracing
-  - Target: <1s per prediction, <30s for 100-point area coverage
+- **2.3x faster than v1.0.0** - Comprehensive algorithmic optimizations
+  - Single prediction: 0.008s → 0.004s (2x faster)
+  - Multi-frequency (9 predictions): 0.111s → 0.048s (2.3x faster)
+  - 24-hour scan: 0.282s → 0.118s (2.4x faster)
+  - Area coverage (100 predictions): 0.82s → 0.35s (2.3x faster)
+  - Function call reduction: 68-71% fewer calls
+
+**Optimizations:**
+- Binary search for height-to-density interpolation (O(n) → O(log n))
+- NumPy vectorization in Gaussian integration (eliminated 40-iteration loop)
+- Vectorized oblique frequency computation (eliminated 1,200 nested iterations)
+- Optimized Fourier series with NumPy dot products
 
 ### 📅 Planned
 
-- **PyPI public release** - Package ready (v1.0.0), pending publication decision
+- **PyPI public release** - Package ready (v1.0.1), pending publication decision
 - **Comprehensive type hints** - Add type annotations throughout codebase
 - **Sphinx API documentation** - Complete API reference with examples
 - **Community engagement** - Forum presence, user support, integration examples

pyproject.toml

@@ -4,8 +4,8 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "dvoacap"
-version = "1.0.0"
-description = "Python port of DVOACAP HF propagation prediction engine with 86.6% validation accuracy"
+version = "1.0.1"
+description = "Python port of DVOACAP HF propagation prediction engine with 86.6% validation accuracy and 2.3x performance boost"
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.11"
 license = "MIT"

wiki/Architecture.md

@@ -385,4 +385,4 @@ See the [Validation Status](Validation-Status) page for current testing state an
 
 ---
 
-**Phase completion:** 5 of 5 complete (100% - Production Ready v1.0.0)
+**Phase completion:** 5 of 5 complete (100% - Production Ready v1.0.1 with 2.3x performance boost)

wiki/Getting-Started.md

@@ -1,7 +1,7 @@
 # Getting Started with DVOACAP-Python
 
-> **🎉 v1.0.0 Release - Production Ready!**
-> DVOACAP-Python has reached production-ready status with comprehensive HF propagation prediction capabilities validated against VOACAP reference data.
+> **🎉 v1.0.1 Release - Production Ready with 2.3x Performance Boost!**
+> DVOACAP-Python has reached production-ready status with comprehensive HF propagation prediction capabilities validated against VOACAP reference data. Version 1.0.1 delivers a 2.3x speedup through algorithmic optimizations.
 
 This guide will help you install DVOACAP-Python and run your first propagation prediction.
 

wiki/Home.md

@@ -45,17 +45,18 @@ DVOACAP-Python is a modern Python port of the DVOACAP HF propagation prediction
 
 ## Project Status
 
-**🎉 Production Ready - v1.0.0 Released! 🎉**
+**🎉 Production Ready - v1.0.1 Released! 🎉**
 
-**Current Phase: 5 of 5 (100% complete)**
+**Current Phase: 5 of 5 (100% complete) + Performance Optimized**
 
 - ✅ 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 test cases)
+- ✅ **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, and ready for real-world amateur radio and professional applications.
+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](Architecture) page for detailed module status.
 

wiki/Performance-Tips.md

@@ -2,8 +2,37 @@
 
 Optimization strategies for speeding up DVOACAP-Python predictions.
 
+## 🚀 v1.0.1 Performance Improvements
+
+**Released:** November 2025
+**Speedup:** 2.3x faster than v1.0.0
+
+DVOACAP-Python v1.0.1 delivers significant performance improvements through algorithmic optimizations and NumPy vectorization:
+
+### Benchmark Results
+
+| Operation | v1.0.0 | v1.0.1 | Speedup |
+|-----------|--------|--------|---------|
+| Single prediction | 0.008s | 0.004s | **2.0x** |
+| Multi-frequency (9 predictions) | 0.111s | 0.048s | **2.3x** |
+| 24-hour scan | 0.282s | 0.118s | **2.4x** |
+| Area coverage (100 predictions) | 0.82s | 0.35s | **2.3x** |
+| Function calls | 100% | 29-32% | **68-71% reduction** |
+
+### Key Optimizations
+
+1. **Binary Search for Height-to-Density** - O(n) → O(log n) complexity
+2. **Vectorized Gaussian Integration** - Eliminated 40-iteration loop using NumPy
+3. **Vectorized Oblique Frequency** - Eliminated 1,200 nested iterations
+4. **Optimized Fourier Series** - Replaced loops with NumPy dot products
+
+See [CHANGELOG.md](https://github.com/skyelaird/dvoacap-python/blob/main/CHANGELOG.md) for full v1.0.1 release notes.
+
+---
+
 ## Table of Contents
 
+- [v1.0.1 Performance Improvements](#-v101-performance-improvements)
 - [Understanding Performance](#understanding-performance)
 - [Quick Wins](#quick-wins)
 - [Configuration Optimization](#configuration-optimization)
@@ -35,21 +64,16 @@ Optimization strategies for speeding up DVOACAP-Python predictions.
 ### Timing Benchmarks
 
 **Single prediction (1 frequency, 1 path):**
-- Fast system (modern CPU): ~3-5 ms (2.3x faster after v1.0 optimizations)
+- Fast system (modern CPU): ~4 ms (v1.0.1 optimized - 2.3x faster than v1.0.0)
 - Average system: ~10-20 ms
 - Slow system (Raspberry Pi): ~50-100 ms
 
 **Full dashboard generation (10 regions × 7 bands × 12 hours):**
-- Fast system: ~20-30 seconds (2.3x faster after v1.0 optimizations)
+- Fast system: ~20-30 seconds (v1.0.1 optimized - 2.3x faster than v1.0.0)
 - Average system: ~30-45 seconds
 - Slow system: ~1-2 minutes
 
-**Performance Optimizations (v1.0.1):**
-- Binary search for height-to-density interpolation
-- Vectorized Gaussian integration using NumPy
-- Vectorized oblique frequency computation
-- Optimized Fourier series calculations
-- Result: 2.3x speedup, 68-71% reduction in function calls
+**Note:** See the [v1.0.1 Performance Improvements](#-v101-performance-improvements) section above for detailed benchmark data and optimization details.
 
 ---
 

wiki/README.md

@@ -298,7 +298,7 @@ If you have questions about the wiki:
 
 **Wiki Status:** ✅ Complete and ready to deploy (with automatic sync!)
 
-**Version:** v1.0.0 (Production Ready)
+**Version:** v1.0.1 (Production Ready - 2.3x Performance Boost)
 
 **Last Updated:** 2025-11-18
 

wiki/Validation-Status.md

@@ -11,7 +11,10 @@ DVOACAP-Python employs a multi-level validation strategy to ensure accurate HF p
 3. **Functional Testing** - Sanity checking across representative paths
 4. **Real-World Validation** (Future) - Comparison with actual propagation measurements
 
-## Current Status: 100% Complete - Production Ready v1.0.0
+## Current Status: 100% Complete - Production Ready v1.0.1
+
+**Latest Release:** v1.0.1 (November 2025) - 2.3x performance improvement
+**Validation Status:** 86.6% pass rate across 11 diverse test cases
 
 **✅ Validated Phases:**
 - Phase 1: Path Geometry
@@ -455,4 +458,4 @@ See [NEXT_STEPS.md](https://github.com/skyelaird/dvoacap-python/blob/main/NEXT_S
 
 **Last Updated:** 2025-11-18
 
-**Overall Progress:** 100% complete - Production Ready v1.0.0 (Phase 5 validated with 86.6% pass rate)
+**Overall Progress:** 100% complete - Production Ready v1.0.1 (Phase 5 validated with 86.6% pass rate, 2.3x performance boost)