buzeraandClaude Opus 5.5
d2bd398a0f
During a first test the Status entity only said "learning" for the first half hour (the radiator-lag wait after a restart), and the attributes explaining why were hard to find. Add two sensors: - Learning Progress (%): for the least trained room, the mean of its three readiness requirements (200 samples, 30 ON, 30 OFF), each capped at 100 %; 100 % means ready. Attributes show the counts. - Last Sample: an enum of the last poll's learning outcome, with English and Romanian state names (e.g. "Waiting for radiators to settle"). Its history shows when learning happens. Polls blocked by missing shared inputs now report waiting_for_inputs. Readiness thresholds move to const.py. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
269 lines
14 KiB
Python
269 lines
14 KiB
Python
"""Run the observer through real HA lifecycle and storage APIs."""
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from datetime import timedelta
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from unittest.mock import patch
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import pytest
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from homeassistant.util import dt as dt_util
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from pytest_homeassistant_custom_component.common import async_fire_time_changed
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from homeassistant.helpers import entity_registry as er
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from homeassistant.helpers.storage import Store
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from custom_components.heating_mpc.const import DOMAIN
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async def setup(hass, entry):
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entry.add_to_hass(hass)
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assert await hass.config_entries.async_setup(entry.entry_id)
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await hass.async_block_till_done()
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return hass.data[DOMAIN][entry.entry_id]
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async def test_setup_reload_unload(hass, entry, inputs):
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coordinator = await setup(hass, entry)
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assert coordinator.config_entry is entry
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registry = er.async_get(hass)
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entities = er.async_entries_for_config_entry(registry, entry.entry_id)
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assert len(entities) == 11 # 7 core + 4 forecast-error sensors
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ids = {e.unique_id: e.entity_id for e in entities}
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assert coordinator.data["status"] == "learning"
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status = hass.states.get(ids[f"{entry.entry_id}_status"])
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assert status.attributes["input_quality"]["rooms"]["sensor.room"]["max_age_seconds_24h"] == 0
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# Volatile diagnostics stay visible but are not written to the Recorder.
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assert {"input_quality", "weather_comparison"} <= status.state_info["unrecorded_attributes"]
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assert "models" not in status.state_info["unrecorded_attributes"]
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proposal_id = registry.async_get_entity_id("binary_sensor", DOMAIN, f"{entry.entry_id}_proposal")
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assert hass.states.get(proposal_id).state == "unavailable"
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assert await hass.config_entries.async_reload(entry.entry_id)
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await hass.async_block_till_done()
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assert hass.data[DOMAIN][entry.entry_id] is not coordinator
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assert ids == {e.unique_id: e.entity_id for e in er.async_entries_for_config_entry(registry, entry.entry_id)}
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assert await hass.config_entries.async_unload(entry.entry_id)
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await hass.async_block_till_done()
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assert entry.entry_id not in hass.data[DOMAIN]
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assert not coordinator._listeners
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assert coordinator._unsub_refresh is None
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async def test_options_reload_removes_only_old_room(hass, entry, inputs):
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await setup(hass, entry)
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registry = er.async_get(hass)
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old = registry.async_get_entity_id("sensor", DOMAIN, f"{entry.entry_id}_sensor.room_predicted_60min")
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hass.states.async_set("sensor.new", "21", {"unit_of_measurement": "°C"})
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hass.config_entries.async_update_entry(entry, options={"room_entities": ["sensor.new"]})
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await hass.async_block_till_done()
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assert hass.data[DOMAIN][entry.entry_id].rooms == ["sensor.new"]
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assert registry.async_get(old) is None
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assert registry.async_get_entity_id("sensor", DOMAIN, f"{entry.entry_id}_sensor.new_predicted_60min")
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assert len(er.async_entries_for_config_entry(registry, entry.entry_id)) == 11
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async def test_storage_restore_and_remove(hass, entry, inputs):
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coordinator = await setup(hass, entry)
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model = coordinator.learners["sensor.room"]
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model.count, model.on_count, model.off_count = 250, 125, 125
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await coordinator._store.async_save({"schema_version": 2, "heater_entity": "switch.boiler",
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"learners": {"sensor.room": model.as_dict()}})
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assert await hass.config_entries.async_reload(entry.entry_id)
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await hass.async_block_till_done()
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restored = hass.data[DOMAIN][entry.entry_id]
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assert restored.learners["sensor.room"].count == 250
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assert restored.data["status"] == "ready"
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forecast_id = er.async_get(hass).async_get_entity_id(
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"sensor", DOMAIN, f"{entry.entry_id}_sensor.room_predicted_60min")
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forecast = hass.states.get(forecast_id)
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assert len(forecast.attributes["forecast_15min"]) == len(forecast.attributes["plan_15min"]) == 4
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assert forecast.attributes["forecast_15min"][3] == float(forecast.state)
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assert {"forecast_15min", "plan_15min"} <= forecast.state_info["unrecorded_attributes"]
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assert await hass.config_entries.async_remove(entry.entry_id)
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await hass.async_block_till_done()
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assert await Store(hass, 1, f"{DOMAIN}.{entry.entry_id}").async_load() is None
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assert not er.async_entries_for_config_entry(er.async_get(hass), entry.entry_id)
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async def test_missing_sensor_manual_off_and_target(hass, entry, inputs):
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coordinator = await setup(hass, entry)
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hass.states.async_set("sensor.room", "unavailable")
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await coordinator.async_refresh()
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assert coordinator.data["status"] == "waiting_for_sensors"
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hass.states.async_set("sensor.room", "20", {"unit_of_measurement": "°C"})
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hass.states.async_set("climate.reference", "off", {"temperature": 19, "preset_mode": "away"})
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await coordinator.async_refresh()
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assert coordinator.data["status"] == "paused"
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assert coordinator.data["proposal"] is None
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assert hass.states.get("climate.reference").attributes["preset_mode"] == "away"
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hass.states.async_set("climate.reference", "heat", {"temperature": 21, "preset_mode": "sleep"})
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await coordinator.async_refresh()
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assert coordinator.data["target"] == 21
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assert hass.states.get("switch.boiler").state == "off"
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async def test_optimizer_failure_is_unavailable(hass, entry, inputs):
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coordinator = await setup(hass, entry)
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model = coordinator.learners["sensor.room"]
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model.count, model.on_count, model.off_count = 250, 125, 125
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coordinator._update_counts()
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with patch("custom_components.heating_mpc.coordinator.optimize", side_effect=RuntimeError("test")):
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await coordinator.async_refresh()
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assert coordinator.data["status"] == "prediction_error"
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assert coordinator.data["proposal"] is None
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async def test_scheduled_sample_saves_and_unload_stops_polling(hass, entry, inputs, freezer, hass_storage):
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coordinator = await setup(hass, entry)
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future = dt_util.utcnow() + timedelta(minutes=5, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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assert coordinator.learners["sensor.room"].count == 1
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payload = hass_storage[f"{DOMAIN}.{entry.entry_id}"]["data"]
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assert payload["learners"]["sensor.room"]["off_count"] == 1
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assert await hass.config_entries.async_unload(entry.entry_id)
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future += timedelta(minutes=5)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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assert coordinator.learners["sensor.room"].count == 1
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@pytest.mark.parametrize("payload", ["broken", {"learners": []}, {"learners": {"sensor.room": {"theta": []}}}])
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async def test_corrupt_saved_payload_starts_learning(hass, entry, inputs, hass_storage, payload):
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hass_storage[f"{DOMAIN}.{entry.entry_id}"] = {"version": 1, "data": payload}
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coordinator = await setup(hass, entry)
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assert coordinator.data["status"] == "learning"
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assert coordinator.data["samples"] == 0
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async def test_startup_preserves_manual_off_with_trained_model(hass, entry, inputs, hass_storage):
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from custom_components.heating_mpc.physics import Learner
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model = Learner(count=250, on_count=125, off_count=125)
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hass_storage[f"{DOMAIN}.{entry.entry_id}"] = {"version": 1, "data": {
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"schema_version": 2, "heater_entity": "switch.boiler",
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"learners": {"sensor.room": model.as_dict()}}}
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hass.states.async_set("climate.reference", "off", {"temperature": 19, "preset_mode": "away"})
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coordinator = await setup(hass, entry)
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assert coordinator.data["status"] == "paused"
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assert coordinator.data["proposal"] is None
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assert hass.states.get("climate.reference").state == "off"
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assert hass.states.get("climate.reference").attributes["temperature"] == 19
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async def test_startup_missing_inputs_then_recovery(hass, entry):
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coordinator = await setup(hass, entry)
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assert coordinator.data["status"] == "waiting_for_sensors"
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hass.states.async_set("sensor.room", "20", {"unit_of_measurement": "°C"})
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hass.states.async_set("sensor.outside", "5", {"unit_of_measurement": "°C"})
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hass.states.async_set("switch.boiler", "off")
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hass.states.async_set("climate.reference", "heat", {"temperature": 22})
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await coordinator.async_refresh()
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assert coordinator.data["status"] == "learning"
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assert coordinator.data["samples"] == 0
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async def test_freshly_written_relay_state_defers_learning(hass, entry, inputs, freezer):
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"""After an HA restart the relay's last_changed is new, so radiator lag is unknown."""
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hass.states.async_set("switch.boiler", "on")
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coordinator = await setup(hass, entry)
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assert coordinator.data["heat_lag"] == 0.5
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assert coordinator.data["heat_lag_uncertainty"] == 0.5
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future = dt_util.utcnow() + timedelta(minutes=5, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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assert coordinator.data["sample_result"] == "lag_uncertain"
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assert coordinator.learners["sensor.room"].count == 0
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async def test_relay_listener_integrates_changes_between_polls(hass, entry, inputs, freezer):
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coordinator = await setup(hass, entry)
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start = dt_util.utcnow()
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for offset, state in ((60, "on"), (200, "off")): # on/off round trip inside one poll
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freezer.move_to(start + timedelta(seconds=offset))
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hass.states.async_set("switch.boiler", state)
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await hass.async_block_till_done()
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for minutes, expected in ((5, "relay_changed"), (10, "learned")):
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future = start + timedelta(minutes=minutes, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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assert coordinator.data["sample_result"] == expected
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# Without the listener this round trip would restart the estimate (about 0.46).
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assert coordinator.data["heat_lag_uncertainty"] < 0.05
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assert await hass.config_entries.async_unload(entry.entry_id)
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hass.states.async_set("switch.boiler", "on")
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await hass.async_block_till_done()
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assert not coordinator._relay_events
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async def test_removed_room_model_survives_options_round_trip(hass, entry, inputs, hass_storage, freezer):
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from custom_components.heating_mpc.physics import Learner
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key = f"{DOMAIN}.{entry.entry_id}"
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hass_storage[key] = {"version": 1, "data": {
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"schema_version": 2, "heater_entity": "switch.boiler",
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"learners": {"sensor.room": Learner(count=250, on_count=125, off_count=125).as_dict()}}}
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hass.states.async_set("sensor.new", "21", {"unit_of_measurement": "°C"})
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await setup(hass, entry)
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hass.config_entries.async_update_entry(entry, options={"room_entities": ["sensor.new"]})
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await hass.async_block_till_done()
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future = dt_util.utcnow() + timedelta(minutes=5, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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saved = hass_storage[key]["data"]
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assert set(saved["learners"]) == {"sensor.new"}
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assert saved["retired_learners"]["sensor.room"]["count"] == 250
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hass.config_entries.async_update_entry(
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entry, options={"room_entities": ["sensor.room", "sensor.new"]})
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await hass.async_block_till_done()
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assert hass.data[DOMAIN][entry.entry_id].learners["sensor.room"].count == 250
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async def test_forecast_error_sensors_score_scheduled_polls(hass, entry, inputs, freezer):
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coordinator = await setup(hass, entry)
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registry = er.async_get(hass)
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ids = {horizon: registry.async_get_entity_id("sensor", DOMAIN, f"{entry.entry_id}_forecast_error_{horizon}min")
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for horizon in (15, 30, 60, 120)}
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assert all(hass.states.get(entity).state == "unknown" for entity in ids.values())
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future = dt_util.utcnow()
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for _ in range(3): # 15 minutes of regular polls
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future += timedelta(minutes=5, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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state = hass.states.get(ids[15])
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assert coordinator.data["forecast_accuracy"][15]["samples"] == 1
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assert float(state.state) == coordinator.data["forecast_accuracy"][15]["mae"] > 0
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assert state.attributes["samples"] == 1
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assert state.attributes["rooms"]["sensor.room"]["samples"] == 1
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assert state.attributes["unit_of_measurement"] == "°C"
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assert "rooms" in state.state_info["unrecorded_attributes"]
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assert hass.states.get(ids[30]).state == "unknown"
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async def test_learning_progress_and_last_sample_sensors(hass, entry, inputs, freezer):
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await setup(hass, entry)
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registry = er.async_get(hass)
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progress_id = registry.async_get_entity_id("sensor", DOMAIN, f"{entry.entry_id}_learning_progress")
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last_id = registry.async_get_entity_id("sensor", DOMAIN, f"{entry.entry_id}_last_sample")
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assert hass.states.get(progress_id).state == "0.0"
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last = hass.states.get(last_id)
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assert last.state == "first_sample"
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assert "lag_uncertain" in last.attributes["options"]
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future = dt_util.utcnow() + timedelta(minutes=5, seconds=1)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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assert hass.states.get(last_id).state == "learned"
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# One OFF sample: (1/200 + 0/30 + 1/30) / 3
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assert float(hass.states.get(progress_id).state) == 1.3
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progress = hass.states.get(progress_id).attributes
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assert (progress["samples"], progress["off_samples"], progress["required"]["samples"]) == (1, 1, 200)
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hass.states.async_set("switch.boiler", "unavailable")
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future += timedelta(minutes=5)
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freezer.move_to(future)
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async_fire_time_changed(hass, future)
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await hass.async_block_till_done()
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last = hass.states.get(last_id)
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assert last.state == "waiting_for_inputs"
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assert last.attributes["counts_since_start"] == {"first_sample": 1, "learned": 1, "waiting_for_inputs": 1}
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