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Add user-configurable option to choose between median and arithmetic mean as the displayed value for all 14 average price sensors, with the alternate value exposed as attribute. BREAKING CHANGE: Average sensor default changed from arithmetic mean to median. Users who rely on arithmetic mean behavior may use the price_mean attribue now, or must manually reconfigure via Settings → Devices & Services → Tibber Prices → Configure → General Settings → "Average Sensor Display" → Select "Arithmetic Mean" to get this as sensor state. Affected sensors (14 total): - Daily averages: average_price_today, average_price_tomorrow - 24h windows: trailing_price_average, leading_price_average - Rolling hour: current_hour_average_price, next_hour_average_price - Future forecasts: next_avg_3h, next_avg_6h, next_avg_9h, next_avg_12h Implementation: - All average calculators now return (mean, median) tuples - User preference controls which value appears in sensor state - Alternate value automatically added to attributes - Period statistics (best_price/peak_price) extended with both values Technical changes: - New config option: CONF_AVERAGE_SENSOR_DISPLAY (default: "median") - Calculator functions return tuples: (avg, median) - Attribute builders: add_alternate_average_attribute() helper function - Period statistics: price_avg → price_mean + price_median - Translations: Updated all 5 languages (de, en, nb, nl, sv) - Documentation: AGENTS.md, period-calculation.md, recorder-optimization.md Migration path: Users can switch back to arithmetic mean via: Settings → Integrations → Tibber Prices → Configure → General Settings → "Average Sensor Display" → "Arithmetic Mean" Impact: Median is more resistant to price spikes, providing more stable automation triggers. Statistical analysis from coordinator still uses arithmetic mean (e.g., trailing_avg_24h for rating calculations). Co-developed-with: GitHub Copilot <copilot@github.com> |
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| .. | ||
| __init__.py | ||
| base.py | ||
| daily_stat.py | ||
| interval.py | ||
| lifecycle.py | ||
| metadata.py | ||
| rolling_hour.py | ||
| timing.py | ||
| trend.py | ||
| volatility.py | ||
| window_24h.py | ||