sstent/Garmin_Analyser
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sstent
2025-09-01 05:34:10 -07:00
parent 83c4fd9909
commit e194ff2ffb
1 changed files with 19 additions and 7 deletions
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garmin_cycling_analyzer.py
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@@ -744,6 +744,7 @@ class GarminWorkoutAnalyzer:
'distance': self.get_value_safely(record, 'distance'),
'altitude': self.get_value_safely(record, 'enhanced_altitude'),
'temperature': self.get_value_safely(record, 'temperature'),
'power': self.get_value_safely(record, 'power'), # ADD POWER FIELD
}
records.append(record_data)
@@ -1079,13 +1080,17 @@ class GarminWorkoutAnalyzer:
if 'heart_rate' in df.columns:
df['heart_rate'] = df['heart_rate'].clip(lower=0, upper=250)
# Check for real power data availability with validation
# Enhanced power data validation
if 'power' in df.columns:
valid_power = df['power'].dropna()
self.power_data_available = len(valid_power) > 10 and valid_power.mean() > 0
if self.power_data_available:
df['power'] = pd.to_numeric(df['power'], errors='coerce').fillna(0)
df['power'] = df['power'].clip(lower=0, upper=2000)
# Convert to numeric and handle missing values
df['power'] = pd.to_numeric(df['power'], errors='coerce').fillna(0)
# Check if we have sufficient valid power data
valid_power = df[df['power'] > 0]
self.power_data_available = len(valid_power) > 10 and valid_power['power'].mean() > 0
# Clip values regardless of availability
df['power'] = df['power'].clip(lower=0, upper=2000)
if len(df) > 0:
if 'speed' in df.columns:
@@ -1237,7 +1242,8 @@ class GarminWorkoutAnalyzer:
('cadence', 'avg_cadence'),
('heart_rate', 'avg_hr'),
('gradient', 'avg_gradient'),
('power_estimate', 'avg_power_estimate')
('power_estimate', 'avg_power_estimate'),
('power', 'avg_real_power')
]:
if col in minute_df.columns and not minute_df[col].isna().all():
minute_stats[stat_key] = minute_df[col].mean()
@@ -1252,6 +1258,12 @@ class GarminWorkoutAnalyzer:
alt_end = minute_df['altitude'].iloc[-1]
minute_stats['elevation_change'] = alt_end - alt_start
# Add real power average if available
if 'power' in minute_df.columns and not minute_df['power'].isna().all():
minute_stats['avg_real_power'] = minute_df['power'].mean()
else:
minute_stats['avg_real_power'] = 0
minute_data.append(minute_stats)
return minute_data