buzeraandClaude Opus 5.5
2a0a94c640
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>
428 lines
21 KiB
Python
428 lines
21 KiB
Python
"""Offline HA boundary doubles; these do not validate the HA runtime itself."""
|
|
import importlib.util
|
|
import sys
|
|
import types
|
|
import unittest
|
|
from datetime import datetime, timedelta, timezone
|
|
from math import exp, pi, sin
|
|
from pathlib import Path
|
|
from unittest.mock import AsyncMock, Mock, patch
|
|
|
|
ROOT = Path(__file__).resolve().parents[1] / 'custom_components' / 'heating_mpc'
|
|
|
|
|
|
class CoordinatorBase:
|
|
@classmethod
|
|
def __class_getitem__(cls, item):
|
|
return cls
|
|
|
|
def __init__(self, hass, *args, **kwargs):
|
|
self.hass = hass
|
|
|
|
async def async_config_entry_first_refresh(self):
|
|
self.data = await self._async_update_data()
|
|
|
|
|
|
class Store:
|
|
def __init__(self, *args):
|
|
self.async_load = AsyncMock(return_value=None)
|
|
self.async_save = AsyncMock()
|
|
self.async_remove = AsyncMock()
|
|
|
|
|
|
def load_integration():
|
|
modules = {name: types.ModuleType(name) for name in (
|
|
'homeassistant', 'homeassistant.const', 'homeassistant.core',
|
|
'homeassistant.config_entries', 'homeassistant.helpers',
|
|
'homeassistant.helpers.storage', 'homeassistant.helpers.update_coordinator',
|
|
'homeassistant.helpers.entity_registry')}
|
|
modules['homeassistant.const'].Platform = types.SimpleNamespace(SENSOR='sensor', BINARY_SENSOR='binary_sensor')
|
|
modules['homeassistant.core'].HomeAssistant = object
|
|
modules['homeassistant.config_entries'].ConfigEntry = object
|
|
modules['homeassistant.helpers.storage'].Store = Store
|
|
modules['homeassistant.helpers.update_coordinator'].DataUpdateCoordinator = CoordinatorBase
|
|
registry = modules['homeassistant.helpers.entity_registry']
|
|
registry.async_get = lambda hass: hass.registry
|
|
registry.async_entries_for_config_entry = lambda reg, entry: reg.entries
|
|
name = 'audit_heating_mpc'
|
|
spec = importlib.util.spec_from_file_location(name, ROOT / '__init__.py', submodule_search_locations=[str(ROOT)])
|
|
module = importlib.util.module_from_spec(spec)
|
|
sys.modules[name] = module
|
|
with patch.dict(sys.modules, modules):
|
|
spec.loader.exec_module(module)
|
|
return module, sys.modules[name + '.coordinator']
|
|
|
|
|
|
integration, coordinator = load_integration()
|
|
|
|
|
|
class BoundaryTests(unittest.IsolatedAsyncioTestCase):
|
|
def setUp(self):
|
|
self.now = datetime.now(timezone.utc)
|
|
self.states = {}
|
|
self.hass = types.SimpleNamespace(
|
|
data={}, states=types.SimpleNamespace(get=self.states.get),
|
|
config=types.SimpleNamespace(units=types.SimpleNamespace(temperature_unit='°C')),
|
|
services=types.SimpleNamespace(async_call=Mock(side_effect=AssertionError('No service calls permitted'))),
|
|
registry=types.SimpleNamespace(entries=[], async_remove=Mock()),
|
|
config_entries=types.SimpleNamespace(
|
|
async_forward_entry_setups=AsyncMock(), async_unload_platforms=AsyncMock(return_value=True),
|
|
async_reload=AsyncMock(), async_update_entry=Mock()),
|
|
)
|
|
async def execute(job):
|
|
return job()
|
|
self.hass.async_add_executor_job = execute
|
|
self.entry = types.SimpleNamespace(entry_id='entry', version=2,
|
|
data={'room_entities': ['sensor.room'], 'heater_entity': 'switch.boiler',
|
|
'climate_entity': 'climate.reference', 'outside_temperature_sources': ['sensor.outside'],
|
|
'horizon_minutes': 60}, options={}, async_on_unload=Mock(), add_update_listener=Mock())
|
|
self.set_state('sensor.room', '20', unit_of_measurement='°C')
|
|
self.set_state('sensor.outside', '5', unit_of_measurement='°C')
|
|
self.set_state('switch.boiler', 'off')
|
|
self.set_state('climate.reference', 'heat', temperature=22)
|
|
self.c = coordinator.HeatingMPCCoordinator(self.hass, self.entry)
|
|
|
|
def set_state(self, entity, value, **attrs):
|
|
self.states[entity] = types.SimpleNamespace(state=value, attributes=attrs,
|
|
last_changed=self.now - timedelta(hours=1), last_reported=self.now)
|
|
|
|
async def sample(self, seconds=300):
|
|
with patch.object(coordinator, 'datetime') as clock:
|
|
clock.now.return_value = self.now
|
|
data = await self.c._async_update_data()
|
|
self.now += timedelta(seconds=seconds)
|
|
return data
|
|
|
|
def switch(self, state, seconds_before_next_sample):
|
|
"""Change the relay between polls; `self.now` is already the next poll time."""
|
|
heater = self.states['switch.boiler']
|
|
heater.state = state
|
|
heater.last_changed = self.now - timedelta(seconds=seconds_before_next_sample)
|
|
|
|
def ready(self):
|
|
m = self.c.learners['sensor.room']
|
|
m.count, m.on_count, m.off_count = 200, 100, 100
|
|
self.c._update_counts()
|
|
|
|
async def test_learning_persistence_and_restart(self):
|
|
await self.sample()
|
|
await self.sample()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 1)
|
|
payload = self.c._store.async_save.call_args.args[0]
|
|
self.assertEqual(payload['schema_version'], 2)
|
|
new = coordinator.HeatingMPCCoordinator(self.hass, self.entry)
|
|
new._store.async_load.return_value = payload
|
|
await new.async_restore_model()
|
|
self.assertEqual(new._off_samples, 1)
|
|
self.assertIsNone(new._previous)
|
|
|
|
async def test_transition_and_round_trip_switch_are_skipped(self):
|
|
for new_state in ('on', 'off'):
|
|
self.c._previous = None
|
|
await self.sample()
|
|
self.states['switch.boiler'].state = new_state
|
|
self.states['switch.boiler'].last_changed = self.now - timedelta(seconds=60)
|
|
await self.sample()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 0)
|
|
|
|
async def test_gaps_backward_clock_and_excessive_jitter_skipped(self):
|
|
for seconds in (0, -300, 100, 420, 3600):
|
|
self.c._previous = None
|
|
await self.sample(seconds)
|
|
await self.sample()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 0)
|
|
|
|
async def test_missing_sensor_breaks_training_continuity(self):
|
|
await self.sample()
|
|
self.states['sensor.room'].state = 'unavailable'
|
|
self.assertEqual((await self.sample())['status'], 'waiting_for_sensors')
|
|
self.states['sensor.room'].state = '20'
|
|
await self.sample()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 0)
|
|
|
|
async def test_weather_fallback_skips_transition(self):
|
|
await self.sample()
|
|
self.c.config['outside_temperature_sources'].append('sensor.alternate')
|
|
self.set_state('sensor.alternate', '7', unit_of_measurement='°C')
|
|
self.states['sensor.outside'].state = 'unavailable'
|
|
data = await self.sample()
|
|
self.assertEqual(data['outside_temperature'], 7)
|
|
self.assertEqual(data['samples'], 0)
|
|
|
|
async def test_outlier_does_not_count_towards_readiness(self):
|
|
await self.sample()
|
|
self.states['sensor.room'].state = '25'
|
|
data = await self.sample()
|
|
self.assertEqual(data['samples'], 0)
|
|
self.assertEqual(data['off_samples'], 0)
|
|
|
|
async def test_fahrenheit_target_and_manual_off(self):
|
|
self.ready()
|
|
self.hass.config.units.temperature_unit = '°F'
|
|
self.states['climate.reference'].attributes['temperature'] = 71.6
|
|
data = await self.sample()
|
|
self.assertEqual(data['target'], 22)
|
|
self.assertEqual(data['status'], 'ready')
|
|
self.states['climate.reference'].state = 'off'
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'paused')
|
|
self.assertIsNone(data['proposal'])
|
|
self.assertEqual(self.states['climate.reference'].attributes['temperature'], 71.6)
|
|
self.hass.services.async_call.assert_not_called()
|
|
|
|
async def test_invalid_target_and_optimizer_failure(self):
|
|
self.ready()
|
|
self.states['climate.reference'].attributes['temperature'] = 'nan'
|
|
self.assertEqual((await self.sample())['status'], 'waiting_for_target')
|
|
self.states['climate.reference'].attributes['temperature'] = 22
|
|
with patch.object(coordinator, 'optimize', side_effect=RuntimeError('test')):
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'prediction_error')
|
|
self.assertIsNone(data['proposal'])
|
|
|
|
async def test_corrupt_storage_and_legacy_counters(self):
|
|
for payload in ([], 'broken', {'schema_version': 999}, {'learners': []},
|
|
{'on_samples': 'bad', 'off_samples': float('inf')}):
|
|
self.c._store.async_load.return_value = payload
|
|
await self.c.async_restore_model()
|
|
self.assertEqual(self.c._on_samples, 0)
|
|
old = self.c.learners['sensor.room'].as_dict()
|
|
old.update(count=500)
|
|
old.pop('on_count'); old.pop('off_count')
|
|
self.c._store.async_load.return_value = {'learners': {'sensor.room': old}, 'on_samples': 250}
|
|
await self.c.async_restore_model()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 500)
|
|
self.assertEqual(self.c._on_samples, 0)
|
|
|
|
async def test_replaced_heater_invalidates_model(self):
|
|
self.c._store.async_load.return_value = {'heater_entity': 'switch.other',
|
|
'learners': {'sensor.room': {'count': 999}}}
|
|
await self.c.async_restore_model()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 0)
|
|
|
|
async def test_setup_reload_unload_and_registry_cleanup(self):
|
|
obsolete = types.SimpleNamespace(platform='heating_mpc', unique_id='entry_sensor.old_predicted_60min', entity_id='sensor.old_forecast')
|
|
kept = types.SimpleNamespace(platform='heating_mpc', unique_id='entry_sensor.room_predicted_60min', entity_id='sensor.forecast')
|
|
self.hass.registry.entries = [obsolete, kept]
|
|
self.assertTrue(await integration.async_setup_entry(self.hass, self.entry))
|
|
self.hass.registry.async_remove.assert_called_once_with('sensor.old_forecast')
|
|
await integration.async_reload_entry(self.hass, self.entry)
|
|
self.hass.config_entries.async_reload.assert_awaited_once_with('entry')
|
|
self.hass.config_entries.async_unload_platforms.return_value = False
|
|
self.assertFalse(await integration.async_unload_entry(self.hass, self.entry))
|
|
self.assertIn('entry', self.hass.data['heating_mpc'])
|
|
self.hass.config_entries.async_unload_platforms.return_value = True
|
|
self.assertTrue(await integration.async_unload_entry(self.hass, self.entry))
|
|
self.assertNotIn('entry', self.hass.data['heating_mpc'])
|
|
self.hass.services.async_call.assert_not_called()
|
|
|
|
async def test_failed_platform_setup_removes_coordinator(self):
|
|
self.hass.config_entries.async_forward_entry_setups.side_effect = RuntimeError('test')
|
|
with self.assertRaises(RuntimeError):
|
|
await integration.async_setup_entry(self.hass, self.entry)
|
|
self.assertNotIn('entry', self.hass.data['heating_mpc'])
|
|
|
|
async def test_uninstall_removes_storage(self):
|
|
store = Store()
|
|
with patch.object(integration, 'Store', return_value=store):
|
|
await integration.async_remove_entry(self.hass, self.entry)
|
|
store.async_remove.assert_awaited_once()
|
|
|
|
async def test_config_migration_preserves_options_precedence(self):
|
|
self.entry.version = 1
|
|
self.entry.data['outside_entity'] = 'sensor.old'
|
|
self.entry.options = {'outside_entity': 'sensor.override'}
|
|
self.assertTrue(await integration.async_migrate_entry(self.hass, self.entry))
|
|
kwargs = self.hass.config_entries.async_update_entry.call_args.kwargs
|
|
self.assertEqual(kwargs['options']['outside_temperature_sources'], ['sensor.override'])
|
|
self.assertEqual(kwargs['data']['outside_temperature_sources'], ['sensor.outside'])
|
|
self.assertNotIn('outside_entity', kwargs['data'])
|
|
self.assertEqual(kwargs['version'], 2)
|
|
self.entry.version = 3
|
|
self.assertFalse(await integration.async_migrate_entry(self.hass, self.entry))
|
|
|
|
async def test_changed_inputs_during_optimization_discard_result(self):
|
|
self.ready()
|
|
async def changed(job):
|
|
output = job()
|
|
self.set_state('climate.reference', 'off', temperature=22)
|
|
return output
|
|
self.hass.async_add_executor_job = changed
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'inputs_changed')
|
|
self.assertIsNone(data['proposal'])
|
|
|
|
async def test_invalid_weights_do_not_publish_proposal(self):
|
|
for weight in (0, -1, 'bad', float('nan'), float('inf')):
|
|
self.c.config['weights'] = {'sensor.room': weight}
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'invalid_weights')
|
|
self.assertIsNone(data['proposal'])
|
|
|
|
async def test_added_room_needs_its_own_excitation_evidence(self):
|
|
model = coordinator.Learner(count=500, on_count=250, off_count=250)
|
|
self.entry.options['room_entities'] = ['sensor.room', 'sensor.new']
|
|
self.c = coordinator.HeatingMPCCoordinator(self.hass, self.entry)
|
|
self.c._store.async_load.return_value = {'learners': {'sensor.room': model.as_dict()}}
|
|
await self.c.async_restore_model()
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 500)
|
|
self.assertEqual(self.c._on_samples, 0)
|
|
self.assertEqual(self.c._off_samples, 0)
|
|
|
|
async def test_changed_inputs_during_save_discard_result(self):
|
|
self.ready()
|
|
await self.sample()
|
|
async def changed(payload):
|
|
self.set_state('climate.reference', 'off', temperature=22)
|
|
self.c._store.async_save.side_effect = changed
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'inputs_changed')
|
|
self.assertIsNone(data['proposal'])
|
|
|
|
async def test_stale_room_pauses_and_recovery_skips_gap(self):
|
|
await self.sample()
|
|
self.states['sensor.room'].last_reported = self.now - timedelta(minutes=31)
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'waiting_for_sensors')
|
|
self.assertEqual(data['input_quality']['rooms']['sensor.room']['status'], 'stale')
|
|
self.assertIsNone(data['proposal'])
|
|
self.set_state('sensor.room', '20', unit_of_measurement='°C')
|
|
data = await self.sample()
|
|
self.assertEqual(data['samples'], 0)
|
|
self.assertEqual(data['status'], 'learning')
|
|
|
|
async def test_stale_weather_fallback_and_optional_outage(self):
|
|
self.c.config['outside_temperature_sources'].append('sensor.alternate')
|
|
self.set_state('sensor.alternate', '7', unit_of_measurement='°C')
|
|
self.states['sensor.outside'].last_reported = self.now - timedelta(minutes=121)
|
|
self.c.config['outside_wind_sources'] = ['sensor.missing']
|
|
data = await self.sample()
|
|
self.assertEqual(data['outside_temperature'], 7)
|
|
self.assertEqual(data['status'], 'learning')
|
|
quality = data['input_quality']['weather']
|
|
self.assertEqual(quality['temperature']['sensor.outside']['status'], 'stale')
|
|
self.assertEqual(quality['wind']['sensor.missing']['status'], 'missing')
|
|
|
|
async def test_fresh_unchanged_reading_is_valid(self):
|
|
self.states['sensor.room'].last_changed = self.now - timedelta(days=2)
|
|
self.assertEqual((await self.sample())['status'], 'learning')
|
|
|
|
async def test_configured_age_limit_applied(self):
|
|
self.c.config['room_max_age_minutes'] = 5
|
|
self.states['sensor.room'].last_reported = self.now - timedelta(minutes=6)
|
|
self.assertEqual((await self.sample())['status'], 'waiting_for_sensors')
|
|
|
|
async def test_invalid_unit_diagnosed_by_metric(self):
|
|
self.states['sensor.outside'].attributes['unit_of_measurement'] = 'km/h'
|
|
data = await self.sample()
|
|
self.assertEqual(data['input_quality']['weather']['temperature']['sensor.outside']['status'],
|
|
'invalid_value_or_unit')
|
|
|
|
async def test_lag_is_continuous_across_relay_transitions(self):
|
|
advance = coordinator.advance_lag
|
|
await self.sample()
|
|
lag = self.c._lag['lag']
|
|
self.switch('on', 150)
|
|
data = await self.sample()
|
|
lag = advance(advance(lag, False, 150), True, 150)
|
|
self.assertEqual(data['sample_result'], 'relay_changed')
|
|
self.assertAlmostEqual(self.c._lag['lag'], lag)
|
|
self.assertLess(lag, 0.2) # radiators have only started warming, not 1.0
|
|
data = await self.sample()
|
|
lag = advance(lag, True, 300)
|
|
self.assertEqual(data['sample_result'], 'learned')
|
|
self.assertAlmostEqual(self.c._lag['lag'], lag)
|
|
self.switch('off', 100)
|
|
await self.sample()
|
|
lag = advance(advance(lag, True, 200), False, 100)
|
|
self.assertAlmostEqual(self.c._lag['lag'], lag)
|
|
self.assertGreater(lag, 0.3) # residual radiator heat is kept, not 0.0
|
|
|
|
async def test_prediction_starts_from_tracked_lag(self):
|
|
self.ready()
|
|
self.set_state('switch.boiler', 'on')
|
|
await self.sample()
|
|
self.switch('off', 60)
|
|
with patch.object(coordinator, 'optimize', wraps=coordinator.optimize) as spy:
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'ready')
|
|
self.assertAlmostEqual(spy.call_args.args[2], self.c._lag['lag'])
|
|
self.assertGreater(spy.call_args.args[2], 0.9)
|
|
|
|
async def test_round_trip_between_polls_restarts_lag_estimate(self):
|
|
await self.sample()
|
|
self.switch('off', 60) # off -> on -> off; only the last change is visible
|
|
data = await self.sample()
|
|
self.assertEqual(data['sample_result'], 'relay_changed')
|
|
self.assertEqual(data['heat_lag_uncertainty'], round(exp(-60 / 1200) / 2, 3))
|
|
data = await self.sample()
|
|
self.assertEqual(data['sample_result'], 'lag_uncertain')
|
|
self.assertEqual(self.c.learners['sensor.room'].count, 0)
|
|
|
|
async def test_learning_waits_until_lag_settles_after_restart(self):
|
|
self.states['switch.boiler'].last_changed = self.now # HA restart resets last_changed
|
|
results = []
|
|
for _ in range(8):
|
|
for entity in ('sensor.room', 'sensor.outside'):
|
|
self.states[entity].last_reported = self.now
|
|
results.append((await self.sample())['sample_result'])
|
|
self.assertEqual(results[0], 'first_sample')
|
|
self.assertEqual(results[1:7], ['lag_uncertain'] * 6)
|
|
self.assertEqual(results[7], 'learned')
|
|
|
|
async def test_room_outage_keeps_relay_lag_tracking(self):
|
|
await self.sample()
|
|
self.switch('on', 150)
|
|
self.states['sensor.room'].state = 'unavailable'
|
|
data = await self.sample()
|
|
self.assertEqual(data['status'], 'waiting_for_sensors')
|
|
self.assertLess(data['heat_lag'], 0.2)
|
|
|
|
async def test_relay_outage_restarts_lag_estimate(self):
|
|
await self.sample()
|
|
self.states['switch.boiler'].state = 'unavailable'
|
|
data = await self.sample()
|
|
self.assertNotIn('heat_lag', data)
|
|
self.switch('off', 30)
|
|
data = await self.sample()
|
|
self.assertEqual(data['sample_result'], 'first_sample')
|
|
self.assertGreater(data['heat_lag_uncertainty'], 0.4)
|
|
|
|
async def test_diagnostic_input_changes_do_not_discard_prediction(self):
|
|
self.ready()
|
|
self.c.config['outside_pressure_sources'] = ['sensor.pressure']
|
|
self.set_state('sensor.pressure', '1010', unit_of_measurement='hPa')
|
|
self.set_state('climate.reference', 'heat', temperature=22, current_temperature=20.0)
|
|
async def changed(job):
|
|
output = job()
|
|
self.set_state('sensor.pressure', '1011', unit_of_measurement='hPa')
|
|
self.set_state('climate.reference', 'heat', temperature=22, current_temperature=20.1)
|
|
return output
|
|
self.hass.async_add_executor_job = changed
|
|
self.assertEqual((await self.sample())['status'], 'ready')
|
|
|
|
async def test_heat_gain_identified_with_mid_interval_switching(self):
|
|
"""Synthetic plant with radiator lag, cycled by a hysteresis thermostat."""
|
|
a, b, c = 0.004, 0.12, 0.0005
|
|
advance = coordinator.advance_lag
|
|
self.states['climate.reference'].state = 'off' # learn only
|
|
temp, lag, on = 21.0, 0.0, False
|
|
for k in range(1500):
|
|
outside = 5 + 5 * sin(2 * pi * k / 288)
|
|
for entity, value in (('sensor.room', temp), ('sensor.outside', outside)):
|
|
self.states[entity].state = f'{value:.5f}'
|
|
self.states[entity].last_reported = self.now
|
|
await self.sample()
|
|
command = temp < 20.7 or (on and temp < 21.3)
|
|
if command != on: # relay switches 120 s after this poll
|
|
self.switch('on' if command else 'off', 180)
|
|
lag = advance(advance(lag, on, 120), command, 180)
|
|
else:
|
|
lag = advance(lag, on, 300)
|
|
on = command
|
|
temp += a * (outside - temp) + b * lag + c
|
|
model = self.c.learners['sensor.room']
|
|
self.assertGreater(model.on_count, 100)
|
|
self.assertAlmostEqual(model.theta[1], b, delta=0.1 * b)
|
|
self.assertAlmostEqual(model.theta[0], a, delta=0.25 * a)
|