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@@ -225,6 +225,57 @@ class GarminWorkoutAnalyzer:
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print("Failed to download activity in any supported format")
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return None
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def download_all_workouts(self) -> None:
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"""Download all cycling activities without analysis."""
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if not self.garmin_client:
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if not self.connect_to_garmin():
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return
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try:
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activities = self.garmin_client.get_activities(0, 1000) # Get up to 1000 activities
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if not activities:
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print("No activities found")
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return
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cycling_keywords = ['cycling', 'bike', 'road_biking', 'mountain_biking', 'indoor_cycling', 'biking']
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cycling_activities = []
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for activity in activities:
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activity_type = activity.get('activityType', {})
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type_key = activity_type.get('typeKey', '').lower()
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type_name = str(activity_type.get('typeId', '')).lower()
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activity_name = activity.get('activityName', '').lower()
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if any(keyword in type_key or keyword in type_name or keyword in activity_name
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for keyword in cycling_keywords):
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cycling_activities.append(activity)
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if not cycling_activities:
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print("No cycling activities found")
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return
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print(f"Found {len(cycling_activities)} cycling activities")
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os.makedirs("data", exist_ok=True)
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for activity in cycling_activities:
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activity_id = activity['activityId']
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activity_name = activity.get('activityName', 'Unnamed')
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print(f"\nDownloading activity: {activity_name} (ID: {activity_id})")
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# Check if already downloaded
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existing_files = [f for f in os.listdir("data") if str(activity_id) in f]
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if existing_files:
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print(f" Already exists: {existing_files[0]}")
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continue
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self._download_workout(activity_id)
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print("\nAll cycling activities downloaded")
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except Exception as e:
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print(f"Error downloading workouts: {e}")
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return
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def _manual_activity_selection(self, activities: List[Dict]) -> Optional[Dict]:
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"""Allow user to manually select an activity from the list."""
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print("\nRecent activities:")
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@@ -913,6 +964,57 @@ class GarminWorkoutAnalyzer:
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return chart_filename
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def reanalyze_all_workouts(self) -> None:
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"""Re-analyze all downloaded activities and generate reports."""
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data_dir = Path("data")
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if not data_dir.exists():
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print("Data directory does not exist. Nothing to re-analyze.")
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return
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# Get all activity files in data directory
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activity_files = list(data_dir.glob('*.[fF][iI][tT]')) + \
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list(data_dir.glob('*.[tT][cC][xX]')) + \
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list(data_dir.glob('*.[gG][pP][xX]'))
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if not activity_files:
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print("No activity files found in data directory")
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return
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print(f"Found {len(activity_files)} activity files to analyze")
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for file_path in activity_files:
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try:
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# Extract activity ID from filename (filename format: {activity_id}_...)
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activity_id = None
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filename_parts = file_path.stem.split('_')
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if filename_parts and filename_parts[0].isdigit():
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activity_id = int(filename_parts[0])
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print(f"\nAnalyzing: {file_path.name}")
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print("------------------------------------------------")
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# Estimate cog size
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estimated_cog = self.estimate_cog_from_cadence(str(file_path))
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print(f"Estimated cog size from file: {estimated_cog}t")
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# Run analysis
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analysis_data = self.analyze_fit_file(str(file_path), estimated_cog)
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if not analysis_data:
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print(f"Failed to analyze file: {file_path.name}")
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continue
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# Generate report (use activity ID if available, else use filename)
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report_id = activity_id if activity_id else file_path.stem
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self.generate_markdown_report(analysis_data, activity_id=report_id)
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print(f"Generated report for activity {report_id}")
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except Exception as e:
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print(f"Error processing {file_path.name}: {e}")
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import traceback
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traceback.print_exc()
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print("\nAll activities re-analyzed")
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def generate_markdown_report(self, analysis_data: Dict, activity_id: int = None, output_file: str = None):
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"""Generate comprehensive markdown report with enhanced power analysis."""
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session = analysis_data['session']
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@@ -1083,8 +1185,22 @@ import argparse
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def main():
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"""Main function to run the workout analyzer."""
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parser = argparse.ArgumentParser(description='Analyze Garmin cycling workouts with enhanced power estimation and charts')
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parser.add_argument('-w', '--workout-id', type=int, help='Specific workout ID to analyze')
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parser = argparse.ArgumentParser(
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description='Garmin Cycling Analyzer - Download and analyze workouts with enhanced power estimation',
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epilog=(
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'Examples:\n'
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' Download & analyze latest workout: python garmin_cycling_analyzer.py\n'
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' Analyze specific workout: python garmin_cycling_analyzer.py -w 123456789\n'
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' Download all cycling workouts: python garmin_cycling_analyzer.py --download-all\n'
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' Re-analyze downloaded workouts: python garmin_cycling_analyzer.py --reanalyze-all\n\n'
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'After downloading workouts, find files in data/ directory\n'
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'Generated reports are saved in reports/ directory'
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),
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formatter_class=argparse.RawTextHelpFormatter
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)
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parser.add_argument('-w', '--workout-id', type=int, help='Analyze specific workout by ID')
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parser.add_argument('--download-all', action='store_true', help='Download all cycling activities (no analysis)')
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parser.add_argument('--reanalyze-all', action='store_true', help='Re-analyze all downloaded activities')
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args = parser.parse_args()
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analyzer = GarminWorkoutAnalyzer()
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@@ -1093,56 +1209,60 @@ def main():
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if not analyzer.connect_to_garmin():
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return
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# Step 2: Download workout
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if args.workout_id:
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# Process command line arguments
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if args.download_all:
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print("Downloading all cycling workouts...")
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analyzer.download_all_workouts()
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print("\nAll downloads completed!")
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elif args.reanalyze_all:
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print("Re-analyzing all downloaded workouts...")
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analyzer.reanalyze_all_workouts()
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elif args.workout_id:
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activity_id = args.workout_id
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print(f"Processing workout ID: {activity_id}")
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fit_file_path = analyzer.download_specific_workout(activity_id)
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if not fit_file_path:
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print(f"Failed to download workout {activity_id}")
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return
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# Run analysis for specific workout
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estimated_cog = analyzer.estimate_cog_from_cadence(fit_file_path)
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confirmed_cog = analyzer.get_user_cog_confirmation(estimated_cog)
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print("Analyzing workout data with enhanced power calculations...")
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print("Analyzing workout with enhanced power calculations...")
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analysis_data = analyzer.analyze_fit_file(fit_file_path, confirmed_cog)
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if analysis_data is None:
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if not analysis_data:
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print("Error: Could not analyze workout data")
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return
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print("Generating enhanced report with charts...")
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print("Generating comprehensive report...")
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report_file = analyzer.generate_markdown_report(analysis_data, activity_id=activity_id)
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print(f"\nWorkout analysis complete!")
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print(f"Report saved as: {report_file}")
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print(f"Charts saved in report directory")
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print(f"\nAnalysis complete for workout {activity_id}!")
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print(f"Report saved: {report_file}")
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else:
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print("Processing latest cycling workout")
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fit_file_path = analyzer.download_latest_workout()
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activity_id = analyzer.last_activity_id
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if not fit_file_path:
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print("Failed to download latest workout")
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return
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# Step 3: Estimate cog size and get user confirmation
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estimated_cog = analyzer.estimate_cog_from_cadence(fit_file_path)
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confirmed_cog = analyzer.get_user_cog_confirmation(estimated_cog)
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# Step 4: Analyze workout file with enhanced processing
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print("Analyzing workout data with enhanced power calculations...")
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print("Analyzing with enhanced power model...")
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analysis_data = analyzer.analyze_fit_file(fit_file_path, confirmed_cog)
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if analysis_data is None:
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if not analysis_data:
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print("Error: Could not analyze workout data")
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return
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# Step 5: Generate enhanced markdown report with charts
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print("Generating enhanced report with charts...")
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print("Generating report with visualization...")
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report_file = analyzer.generate_markdown_report(analysis_data, activity_id=activity_id)
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print(f"\nWorkout analysis complete!")
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print(f"Report saved as: {report_file}")
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print(f"Charts saved in report directory")
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print(f"\nAnalysis complete for activity {activity_id}!")
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print(f"Report saved: {report_file}")
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if __name__ == "__main__":
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# Create example .env file if it doesn't exist
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@@ -1,6 +1,6 @@
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# Cycling Workout Analysis Report
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*Generated on 2025-08-30 19:02:07*
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*Generated on 2025-08-30 20:15:15*
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**Bike Configuration:** 38t chainring, 20t cog, 22lbs bike weight
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**Wheel Specs:** 700c wheel + 46mm tires (circumference: 2.49m)
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@@ -46,7 +46,7 @@
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## Workout Analysis Charts
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Detailed charts showing power output, heart rate, and elevation profiles:
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## Minute-by-Minute Analysis
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| Min | Dist (km) | Avg Speed (km/h) | Avg Cadence | Avg HR | Max HR | Avg Gradient (%) | Elevation Δ (m) | Est Avg Power (W) |
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