mitai-jinkendo/backend/calculations/__init__.py
Lars 09e6a5fbfb feat: Phase 0b - Calculation Engine for 120+ Goal-Aware Placeholders
- body_metrics.py: K1-K5 calculations (weight trend, FM/LBM, circumferences, recomposition, body score)
- nutrition_metrics.py: E1-E5 calculations (energy balance, protein adequacy, macro consistency, nutrition score)
- activity_metrics.py: A1-A8 calculations (training volume, intensity, quality, ability balance, load monitoring)
- recovery_metrics.py: Improved Recovery Score v2 (HRV, RHR, sleep, regularity, load balance)
- correlation_metrics.py: C1-C7 calculations (lagged correlations, plateau detection, driver panel)
- scores.py: Meta-scores with Dynamic Focus Areas v2.0 integration

All calculations include:
- Data quality assessment
- Confidence levels
- Dynamic weighting by user's focus area priorities
- Support for custom goals via goal_utils integration

Next: Placeholder integration in placeholder_resolver.py
2026-03-28 07:20:40 +01:00

49 lines
1.2 KiB
Python

"""
Calculation Engine for Phase 0b - Goal-Aware Placeholders
This package contains all metric calculation functions for:
- Body metrics (K1-K5 from visualization concept)
- Nutrition metrics (E1-E5)
- Activity metrics (A1-A8)
- Recovery metrics (S1)
- Correlations (C1-C7)
- Scores (Goal Progress Score with Dynamic Focus Areas)
All calculations are designed to work with Dynamic Focus Areas v2.0.
"""
from .body_metrics import *
from .nutrition_metrics import *
from .activity_metrics import *
from .recovery_metrics import *
from .correlation_metrics import *
from .scores import *
__all__ = [
# Body
'calculate_weight_7d_median',
'calculate_weight_28d_slope',
'calculate_fm_28d_change',
'calculate_lbm_28d_change',
'calculate_body_progress_score',
# Nutrition
'calculate_energy_balance_7d',
'calculate_protein_g_per_kg',
'calculate_nutrition_score',
# Activity
'calculate_training_minutes_week',
'calculate_activity_score',
# Recovery
'calculate_recovery_score_v2',
# Correlations
'calculate_lag_correlation',
# Meta Scores
'calculate_goal_progress_score',
'calculate_data_quality_score',
]