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https://github.com/sstent/Garmin_Analyser.git
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131 lines
4.0 KiB
Python
131 lines
4.0 KiB
Python
"""Data models for workout analysis."""
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from dataclasses import dataclass
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from typing import List, Optional, Dict, Any
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from datetime import datetime
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import pandas as pd
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@dataclass
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class WorkoutMetadata:
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"""Metadata for a workout session."""
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activity_id: str
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activity_name: str
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start_time: datetime
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duration_seconds: float
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distance_meters: Optional[float] = None
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avg_heart_rate: Optional[float] = None
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max_heart_rate: Optional[float] = None
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avg_power: Optional[float] = None
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max_power: Optional[float] = None
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avg_speed: Optional[float] = None
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max_speed: Optional[float] = None
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elevation_gain: Optional[float] = None
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elevation_loss: Optional[float] = None
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calories: Optional[float] = None
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sport: str = "cycling"
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sub_sport: Optional[str] = None
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is_indoor: bool = False
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@dataclass
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class PowerData:
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"""Power-related data for a workout."""
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power_values: List[float]
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estimated_power: List[float]
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power_zones: Dict[str, int]
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normalized_power: Optional[float] = None
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intensity_factor: Optional[float] = None
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training_stress_score: Optional[float] = None
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power_distribution: Dict[str, float] = None
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@dataclass
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class HeartRateData:
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"""Heart rate data for a workout."""
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heart_rate_values: List[float]
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hr_zones: Dict[str, int]
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avg_hr: Optional[float] = None
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max_hr: Optional[float] = None
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hr_distribution: Dict[str, float] = None
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@dataclass
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class SpeedData:
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"""Speed and distance data for a workout."""
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speed_values: List[float]
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distance_values: List[float]
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avg_speed: Optional[float] = None
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max_speed: Optional[float] = None
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total_distance: Optional[float] = None
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@dataclass
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class ElevationData:
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"""Elevation and gradient data for a workout."""
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elevation_values: List[float]
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gradient_values: List[float]
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elevation_gain: Optional[float] = None
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elevation_loss: Optional[float] = None
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max_gradient: Optional[float] = None
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min_gradient: Optional[float] = None
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@dataclass
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class GearData:
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"""Gear-related data for a workout."""
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series: pd.Series # Per-sample gear selection with columns: chainring_teeth, cog_teeth, gear_ratio, confidence
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summary: Dict[str, Any] # Time-in-gear distribution, top N gears by time, unique gears count
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@dataclass
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class WorkoutData:
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"""Complete workout data structure."""
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metadata: WorkoutMetadata
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power: Optional[PowerData] = None
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heart_rate: Optional[HeartRateData] = None
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speed: Optional[SpeedData] = None
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elevation: Optional[ElevationData] = None
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gear: Optional[GearData] = None
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raw_data: Optional[pd.DataFrame] = None
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@property
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def has_power_data(self) -> bool:
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"""Check if actual power data is available."""
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return self.power is not None and any(p > 0 for p in self.power.power_values)
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@property
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def duration_minutes(self) -> float:
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"""Get duration in minutes."""
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return self.metadata.duration_seconds / 60
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@property
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def distance_km(self) -> Optional[float]:
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"""Get distance in kilometers."""
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if self.metadata.distance_meters is None:
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return None
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return self.metadata.distance_meters / 1000
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def get_summary(self) -> Dict[str, Any]:
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"""Get a summary of the workout."""
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return {
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"activity_id": self.metadata.activity_id,
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"activity_name": self.metadata.activity_name,
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"start_time": self.metadata.start_time.isoformat(),
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"duration_minutes": round(self.duration_minutes, 1),
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"distance_km": round(self.distance_km, 2) if self.distance_km else None,
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"avg_heart_rate": self.metadata.avg_heart_rate,
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"max_heart_rate": self.metadata.max_heart_rate,
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"avg_power": self.metadata.avg_power,
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"max_power": self.metadata.max_power,
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"elevation_gain": self.metadata.elevation_gain,
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"is_indoor": self.metadata.is_indoor,
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"has_power_data": self.has_power_data
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} |