Julian Pawlowski 325d855997 feat(utils): add coefficient of variation (CV) calculation ... Add calculate_coefficient_of_variation() as central utility function: - CV = (std_dev / mean) * 100 as standardized volatility measure - calculate_volatility_with_cv() returns both level and numeric CV - Volatility sensors now expose CV in attributes for transparency Used as foundation for quality gates, adaptive smoothing, and period statistics. Impact: Volatility sensors show numeric CV percentage alongside categorical level, enabling users to see exact price variation.		2025-12-22 23:21:38 +00:00
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__init__.py	feat(sensor): add data lifecycle diagnostic sensor with push updates	2025-11-20 15:12:41 +00:00
base.py	refactor(price_info): price data handling to use unified interval retrieval	2025-11-24 10:49:34 +00:00
daily_stat.py	refactor(currency)!: rename major/minor to base/subunit currency terminology	2025-12-11 08:26:30 +00:00
interval.py	refactor(currency)!: rename major/minor to base/subunit currency terminology	2025-12-11 08:26:30 +00:00
lifecycle.py	refactor: simplify needs_tomorrow_data() - remove tomorrow_date parameter	2025-11-24 16:26:08 +00:00
metadata.py	refactor(naming): complete class naming convention alignment	2025-11-20 11:22:53 +00:00
rolling_hour.py	feat(sensors): always show both mean and median in average sensor attributes	2025-12-18 15:12:30 +00:00
timing.py	refactor: migrate from multi-home to single-home-per-coordinator architecture	2025-11-24 16:24:37 +00:00
trend.py	feat(sensors): always show both mean and median in average sensor attributes	2025-12-18 15:12:30 +00:00
volatility.py	feat(utils): add coefficient of variation (CV) calculation	2025-12-22 23:21:38 +00:00
window_24h.py	feat(sensors): always show both mean and median in average sensor attributes	2025-12-18 15:12:30 +00:00