Lars
7ede0e3fe8
- Migrated all 16 calculation functions from calculations/nutrition_metrics.py to data_layer/nutrition_metrics.py - Functions: Energy balance (7d calculation, deficit/surplus classification) - Functions: Protein adequacy (g/kg, days in target, 28d score) - Functions: Macro consistency (score, intake volatility) - Functions: Nutrition scoring (main score with focus weights, calorie/macro adherence helpers) - Functions: Energy availability warning (with severity levels and recommendations) - Functions: Data quality assessment - Functions: Fiber/sugar averages (TODO stubs) - Updated data_layer/__init__.py with 12 new exports - Refactored placeholder_resolver.py to import nutrition_metrics from data_layer Module 2/6 complete. Single Source of Truth for nutrition metrics established. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
108 lines
3.1 KiB
Python
108 lines
3.1 KiB
Python
"""
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Data Layer - Pure Data Retrieval & Calculation Logic
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This module provides structured data functions for all metrics.
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NO FORMATTING. NO STRINGS WITH UNITS. Only structured data.
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Usage:
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from data_layer.body_metrics import get_weight_trend_data
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data = get_weight_trend_data(profile_id="123", days=28)
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# Returns: {"slope_28d": 0.23, "confidence": "high", ...}
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Modules:
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- body_metrics: Weight, body fat, lean mass, circumferences
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- nutrition_metrics: Calories, protein, macros, adherence
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- activity_metrics: Training volume, quality, abilities
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- recovery_metrics: Sleep, RHR, HRV, recovery score
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- health_metrics: Blood pressure, VO2Max, health stability
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- goals: Active goals, progress, projections
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- correlations: Lag-analysis, plateau detection
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- utils: Shared functions (confidence, baseline, outliers)
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Phase 0c: Multi-Layer Architecture
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Version: 1.0
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Created: 2026-03-28
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"""
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# Core utilities
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from .utils import *
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# Metric modules
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from .body_metrics import *
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from .nutrition_metrics import *
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from .activity_metrics import *
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from .recovery_metrics import *
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from .health_metrics import *
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# Future imports (will be added as modules are created):
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# from .goals import *
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# from .correlations import *
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__all__ = [
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# Utils
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'calculate_confidence',
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'serialize_dates',
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# Body Metrics (Basic)
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'get_latest_weight_data',
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'get_weight_trend_data',
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'get_body_composition_data',
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'get_circumference_summary_data',
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# Body Metrics (Calculated)
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'calculate_weight_7d_median',
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'calculate_weight_28d_slope',
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'calculate_weight_90d_slope',
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'calculate_goal_projection_date',
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'calculate_goal_progress_pct',
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'calculate_fm_28d_change',
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'calculate_lbm_28d_change',
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'calculate_waist_28d_delta',
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'calculate_hip_28d_delta',
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'calculate_chest_28d_delta',
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'calculate_arm_28d_delta',
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'calculate_thigh_28d_delta',
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'calculate_waist_hip_ratio',
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'calculate_recomposition_quadrant',
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'calculate_body_progress_score',
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'calculate_body_data_quality',
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# Nutrition Metrics (Basic)
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'get_nutrition_average_data',
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'get_nutrition_days_data',
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'get_protein_targets_data',
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'get_energy_balance_data',
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'get_protein_adequacy_data',
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'get_macro_consistency_data',
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# Nutrition Metrics (Calculated)
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'calculate_energy_balance_7d',
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'calculate_energy_deficit_surplus',
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'calculate_protein_g_per_kg',
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'calculate_protein_days_in_target',
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'calculate_protein_adequacy_28d',
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'calculate_macro_consistency_score',
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'calculate_intake_volatility',
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'calculate_nutrition_score',
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'calculate_energy_availability_warning',
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'calculate_fiber_avg_7d',
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'calculate_sugar_avg_7d',
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'calculate_nutrition_data_quality',
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# Activity Metrics
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'get_activity_summary_data',
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'get_activity_detail_data',
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'get_training_type_distribution_data',
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# Recovery Metrics
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'get_sleep_duration_data',
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'get_sleep_quality_data',
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'get_rest_days_data',
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# Health Metrics
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'get_resting_heart_rate_data',
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'get_heart_rate_variability_data',
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'get_vo2_max_data',
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]
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