- Introduced a single TDEE calculation based on current weight, replacing the fixed 2500 kcal value.
- Updated `get_energy_balance_data` to use daily totals for intake calculations and improved energy balance logic.
- Enhanced `get_nutrition_average_data` to calculate averages over calendar days instead of raw log entries.
- Adjusted placeholder resolution to ensure consistent metadata usage across requests.
- Fixed issues in the charts router to reflect the new energy balance logic and TDEE calculations.
These changes improve the accuracy of nutritional assessments and streamline data handling in the application.
Fixes calculate_protein_g_per_kg and calculate_protein_days_in_target:
**Problem:**
Both functions were treating individual nutrition_log entries as days,
causing incorrect calculations when multiple entries exist per day
(e.g., from CSV imports: 233 entries across 7 days).
**Solution:**
1. calculate_protein_g_per_kg:
- Added GROUP BY date, SUM(protein_g) to aggregate by day
- Now averages daily totals, not individual entries
- Correct: 7 days → 7 values, not 233 entries → 233 values
2. calculate_protein_days_in_target:
- Added GROUP BY date, SUM(protein_g) to aggregate by day
- Calculates target range in absolute grams (not g/kg per entry)
- Counts unique DAYS in range, not entries
- Correct format: "5/7" (5 of 7 days), not "150/233" (entries)
**Impact:**
- protein_g_per_kg: was returning "nicht verfügbar" → now returns correct value
- protein_days_in_target: was returning "nicht verfügbar" → now returns correct format
**Root Cause:**
Functions expected 7 unique dates but got 233 entries.
With export date 2026-04-02 and last data 2026-03-26,
the 7-day window had insufficient unique dates.
Issue reported by user: Part B placeholders not showing correct values
in extended export (registry metadata was correct, but computed values failed).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- 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>
Data Layer:
- get_nutrition_average_data() - all macros in one call
- get_nutrition_days_data() - coverage tracking
- get_protein_targets_data() - 1.6g/kg and 2.2g/kg targets
- get_energy_balance_data() - deficit/surplus/maintenance
- get_protein_adequacy_data() - 0-100 score
- get_macro_consistency_data() - 0-100 score
Placeholder Layer:
- get_nutrition_avg() - refactored to use data layer
- get_nutrition_days() - refactored to use data layer
- get_protein_ziel_low() - refactored to use data layer
- get_protein_ziel_high() - refactored to use data layer
All 6 nutrition data functions + 4 placeholder refactors complete.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
