- Updated the `_correlate_energy_weight` function to streamline the unpacking of the `best` variable, removing unnecessary tuple elements for improved clarity and efficiency in the correlation logic.
- Updated `calculate_lag_correlation` to include detailed interpretations and lag details for energy balance vs. weight change, protein vs. lean mass, and load vs. vital metrics.
- Improved handling of insufficient data scenarios in correlation charts, providing clearer messages and metadata for user insights.
- Refactored chart functions to utilize best lag values and correlation data more effectively, enhancing the visualization of relationships between metrics.
- Refactored the `calculate_lag_correlation` function to normalize lag payloads and improve correlation calculations for various nutrition metrics.
- Introduced a new function `build_nutrition_correlation_heuristic_items` to generate heuristic insights based on merged nutrition data, enhancing user understanding of dietary impacts on weight and body composition.
- Updated the `get_nutrition_history_viz_bundle` function to include daily calorie balance and protein vs. lean mass data, providing a comprehensive view of nutrition trends.
- Enhanced the frontend to visualize calorie balance and protein vs. lean mass insights, improving the user experience with clear graphical representations of dietary correlations.
Critical bug fix: In-function imports were still referencing calculations/ module.
This caused all calculated placeholders to fail silently.
Fixed imports in:
- activity_metrics.py: calculate_activity_score (scores import)
- recovery_metrics.py: calculate_recent_load_balance_3d (activity_metrics import)
- scores.py: 12 function imports (body/nutrition/activity/recovery metrics)
- correlations.py: 11 function imports (scores, body, nutrition, activity, recovery metrics)
All data_layer modules now reference each other correctly.
Placeholders should resolve properly now.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
