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2399611b28
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Update summary documents to reflect 100% completion
Both COMPLETION_SUMMARY.md and CONVERSION_SUMMARY.md have been updated to accurately reflect the current project state:
Updates:
- ✅ ATD module: Updated from 70% to 100% (all 9 sensor types complete)
- ✅ Added validation system section (1,294 lines)
- ✅ Updated line counts: ~11,452 total lines (was ~8,000)
- ✅ Added .env migration details (removed Java driver)
- ✅ Updated all completion statuses to 100%
- ✅ Removed outdated "remaining work" sections
- ✅ Added validation workflow and examples
Current Status:
- RSN: 100% (5 sensor types)
- Tilt: 100% (4 sensor types)
- ATD: 100% (9 sensor types)
- Validation: 100% (full comparison framework)
- Total: 18+ sensor types, production ready
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-10-13 15:40:16 +02:00 |
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23c53cf747
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Add comprehensive validation system and migrate to .env configuration
This commit includes:
1. Database Configuration Migration:
- Migrated from DB.txt (Java JDBC) to .env (python-dotenv)
- Added .env.example template with clear variable names
- Updated database.py to use environment variables
- Added python-dotenv>=1.0.0 to dependencies
- Updated .gitignore to exclude sensitive files
2. Validation System (1,294 lines):
- comparator.py: Statistical comparison with RMSE, correlation, tolerances
- db_extractor.py: Database queries for all sensor types
- validator.py: High-level validation orchestration
- cli.py: Command-line interface for validation
- README.md: Comprehensive validation documentation
3. Validation Features:
- Compare Python vs MATLAB outputs from database
- Support for all sensor types (RSN, Tilt, ATD)
- Statistical metrics: max abs/rel diff, RMSE, correlation
- Configurable tolerances (abs, rel, max)
- Detailed validation reports
- CLI and programmatic APIs
4. Examples and Documentation:
- validate_example.sh: Bash script example
- validate_example.py: Python programmatic example
- Updated main README with validation section
- Added validation workflow and troubleshooting guide
Benefits:
- ✅ No Java driver needed (native Python connectors)
- ✅ Secure .env configuration (excluded from git)
- ✅ Comprehensive validation against MATLAB
- ✅ Statistical confidence in migration accuracy
- ✅ Automated validation reports
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-10-13 15:34:13 +02:00 |
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