# Garmin Analyser A comprehensive Python application for analyzing Garmin workout data from FIT, TCX, and GPX files, as well as direct integration with Garmin Connect. Provides detailed power, heart rate, and performance analysis with beautiful visualizations and comprehensive reports. ## Features - **Multi-format Support**: Parse FIT, TCX, and GPX workout files - **Garmin Connect Integration**: Direct download from Garmin Connect - **Comprehensive Analysis**: Power, heart rate, speed, elevation, and zone analysis - **Advanced Metrics**: Normalized Power, Intensity Factor, Training Stress Score - **Interactive Charts**: Power curves, heart rate zones, elevation profiles - **Detailed Reports**: HTML, PDF, and Markdown reports with customizable templates - **Interval Detection**: Automatic detection and analysis of workout intervals - **Performance Tracking**: Long-term performance trends and summaries ## Installation ### Requirements - Python 3.8 or higher - pip package manager ### Install Dependencies ```bash pip install -r requirements.txt ``` ### Optional Dependencies For PDF report generation: ```bash pip install weasyprint ``` ## Quick Start ### Basic Usage Analyze a single workout file: ```bash python main.py --file path/to/workout.fit --report --charts ``` Analyze all workouts in a directory: ```bash python main.py --directory path/to/workouts --summary --format html ``` Download from Garmin Connect: ```bash python main.py --garmin-connect --report --charts --summary ``` ### Command Line Options ``` usage: main.py [-h] [--config CONFIG] [--verbose] (--file FILE | --directory DIRECTORY | --garmin-connect) [--ftp FTP] [--max-hr MAX_HR] [--zones ZONES] [--output-dir OUTPUT_DIR] [--format {html,pdf,markdown}] [--charts] [--report] [--summary] Analyze Garmin workout data from files or Garmin Connect options: -h, --help show this help message and exit --config CONFIG, -c CONFIG Configuration file path --verbose, -v Enable verbose logging --file FILE, -f FILE Path to workout file (FIT, TCX, or GPX) --directory DIRECTORY, -d DIRECTORY Directory containing workout files --garmin-connect Download from Garmin Connect --ftp FTP Functional Threshold Power (W) --max-hr MAX_HR Maximum heart rate (bpm) --zones ZONES Path to zones configuration file --output-dir OUTPUT_DIR Output directory for reports and charts --format {html,pdf,markdown} Report format --charts Generate charts --report Generate comprehensive report --summary Generate summary report for multiple workouts ``` ## Configuration ### Basic Configuration Create a `config/config.yaml` file: ```yaml # Garmin Connect credentials garmin_username: your_username garmin_password: your_password # Output settings output_dir: output log_level: INFO # Training zones zones: ftp: 250 # Functional Threshold Power (W) max_heart_rate: 185 # Maximum heart rate (bpm) power_zones: - name: Active Recovery min: 0 max: 55 percentage: true - name: Endurance min: 56 max: 75 percentage: true - name: Tempo min: 76 max: 90 percentage: true - name: Threshold min: 91 max: 105 percentage: true - name: VO2 Max min: 106 max: 120 percentage: true - name: Anaerobic min: 121 max: 150 percentage: true heart_rate_zones: - name: Zone 1 min: 0 max: 60 percentage: true - name: Zone 2 min: 60 max: 70 percentage: true - name: Zone 3 min: 70 max: 80 percentage: true - name: Zone 4 min: 80 max: 90 percentage: true - name: Zone 5 min: 90 max: 100 percentage: true ``` ### Advanced Configuration You can also specify zones configuration in a separate file: ```yaml # zones.yaml ftp: 275 max_heart_rate: 190 power_zones: - name: Recovery min: 0 max: 50 percentage: true - name: Endurance min: 51 max: 70 percentage: true # ... additional zones ``` ## Usage Examples ### Single Workout Analysis ```bash # Analyze a single FIT file with custom FTP python main.py --file workouts/2024-01-15-ride.fit --ftp 275 --report --charts # Generate PDF report python main.py --file workouts/workout.tcx --format pdf --report # Quick analysis with verbose output python main.py --file workout.gpx --verbose --report ``` ### Batch Analysis ```bash # Analyze all files in a directory python main.py --directory data/workouts/ --summary --charts --format html # Analyze with custom zones python main.py --directory data/workouts/ --zones config/zones.yaml --summary ``` ### Garmin Connect Integration ```bash # Download and analyze last 30 days python main.py --garmin-connect --report --charts --summary # Download specific period python main.py --garmin-connect --report --output-dir reports/january/ ``` ## Output Structure The application creates the following output structure: ``` output/ ├── charts/ │ ├── workout_20240115_143022_power_curve.png │ ├── workout_20240115_143022_heart_rate_zones.png │ └── ... ├── reports/ │ ├── workout_report_20240115_143022.html │ ├── workout_report_20240115_143022.pdf │ └── summary_report_20240115_143022.html └── logs/ └── garmin_analyser.log ``` ## Analysis Features ### Power Analysis - **Average Power**: Mean power output - **Normalized Power**: Adjusted power accounting for variability - **Maximum Power**: Peak power output - **Power Zones**: Time spent in each power zone - **Power Curve**: Maximum power for different durations ### Heart Rate Analysis - **Average Heart Rate**: Mean heart rate - **Maximum Heart Rate**: Peak heart rate - **Heart Rate Zones**: Time spent in each heart rate zone - **Heart Rate Variability**: Analysis of heart rate patterns ### Performance Metrics - **Intensity Factor (IF)**: Ratio of Normalized Power to FTP - **Training Stress Score (TSS)**: Overall training load - **Variability Index**: Measure of power consistency - **Efficiency Factor**: Ratio of Normalized Power to Average Heart Rate ### Interval Detection - Automatic detection of high-intensity intervals - Analysis of interval duration, power, and recovery - Summary of interval performance ## Customization ### Custom Report Templates You can customize report templates by modifying the files in `visualizers/templates/`: - `workout_report.html`: HTML report template - `workout_report.md`: Markdown report template - `summary_report.html`: Summary report template ### Adding New Analysis Metrics Extend the `WorkoutAnalyzer` class in `analyzers/workout_analyzer.py`: ```python def analyze_custom_metric(self, workout: WorkoutData) -> dict: """Analyze custom metric.""" # Your custom analysis logic here return {'custom_metric': value} ``` ### Custom Chart Types Add new chart types in `visualizers/chart_generator.py`: ```python def generate_custom_chart(self, workout: WorkoutData, analysis: dict) -> str: """Generate custom chart.""" # Your custom chart logic here return chart_path ``` ## Troubleshooting ### Common Issues **File Not Found Errors** - Ensure file paths are correct and files exist - Check file permissions **Garmin Connect Authentication** - Verify username and password in config - Check internet connection - Ensure Garmin Connect account is active **Missing Dependencies** - Run `pip install -r requirements.txt` - For PDF support: `pip install weasyprint` **Performance Issues** - For large datasets, use batch processing - Consider using `--summary` flag for multiple files ### Debug Mode Enable verbose logging for troubleshooting: ```bash python main.py --verbose --file workout.fit --report ``` ## API Reference ### Core Classes - `WorkoutData`: Main workout data structure - `WorkoutAnalyzer`: Performs workout analysis - `ChartGenerator`: Creates visualizations - `ReportGenerator`: Generates reports - `GarminClient`: Handles Garmin Connect integration ### Example API Usage ```python from pathlib import Path from config.settings import Settings from parsers.file_parser import FileParser from analyzers.workout_analyzer import WorkoutAnalyzer # Initialize components settings = Settings('config/config.yaml') parser = FileParser() analyzer = WorkoutAnalyzer(settings.zones) # Parse and analyze workout workout = parser.parse_file(Path('workout.fit')) analysis = analyzer.analyze_workout(workout) # Access results print(f"Average Power: {analysis['summary']['avg_power']} W") print(f"Training Stress Score: {analysis['summary']['training_stress_score']}") ``` ## Contributing 1. Fork the repository 2. Create a feature branch 3. Make your changes 4. Add tests for new functionality 5. Submit a pull request ## License MIT License - see LICENSE file for details. ## Support For issues and questions: - Check the troubleshooting section - Review log files in `output/logs/` - Open an issue on GitHub