5 Commits

Include renames

Author	SHA1	Message	Date
buzeraandClaude Opus 5.5	387929b01b	Bound learner covariance to stop RLS windup ... With forgetting 0.999 and no heat excitation (summer, long OFF periods), the heat-coefficient variance grew by 1/0.999 per sample without limit: about 8.7e12 after 104 simulated OFF days. The first ON samples could then swing coefficients to their bounds, and accumulated asymmetry approached the absolute 1e-8 restore tolerance, past which a restart silently reset the whole model. Symmetrize P and bound its diagonal by the prior after every update (row/column scaling keeps it positive definite). Restore uses a relative round-off tolerance and applies the same bound, so wound-up v0.2.1 models load instead of being discarded. Payload schema is unchanged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>	2026-10-26 21:20:50 +02:00
buzera	c771bc360a	Add HA lifecycle tests and CI	2026-10-26 18:21:18 +02:00
buzera	cea79b6b48	Add sensor freshness checks	2026-10-26 18:13:00 +02:00
buzera	c434f3995d	Fix shadow observer lifecycle, learning and prediction correctness	2026-10-26 17:50:20 +02:00
buzera	2b9a10979b	initial commit v0.2.1	2026-10-26 17:34:32 +02:00