A finished plan was discarded whenever any watched State object changed
during the save or calculation, including diagnostic-only weather
sensors and the thermostat's current_temperature/hvac_action. The
proposed-heat entity then went unavailable for five minutes without
cause. Compare only the values the prediction uses: room and outdoor
temperature states and units, thermostat mode and target, and relay
state and last change.
Also pass config_entry to the coordinator explicitly instead of relying
on HA's ContextVar fallback, which HA reports as deprecated usage.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The lag proxy was reset to the new relay command at every relay change
and after any skipped interval, so it read 1.0 straight after ON and 0.0
straight after OFF. This disabled the lag model around every boiler
cycle: on a synthetic lagged plant cycled by a hysteresis thermostat the
learner's heat gain came out 34% low (0.079 vs 0.12) and the loss term
43% low, and the optimizer started post-transition plans from the wrong
lag.
Track the lag at every poll with a valid relay state, independently of
room sensors. Integrate a single change between polls at its
last_changed time. For ambiguous cases (round trip between polls, relay
outage, restart, clock jump) restart from time-in-state with an explicit
error half-width, and learn only once it is at most 0.1 (about 32 min
after an HA restart). The same synthetic test now learns 0.1195/0.00389
(true 0.12/0.004).
Expose heat_lag, heat_lag_uncertainty and sample_result on Status so
users can see why a poll was or was not learned. The HA test fixture
relay now has an hour-old timestamp; a new test covers a freshly
written relay state.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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>
buzeraandClaude Opus 5.5