Accept more than 1 state for numeric entities in Bayesian (#119281)
* test driven delevopment * test driven development - multi numeric state * better multi-state processing * when state==below return true * adds test for a bad state * improve codecov * value error already handled in async_numeric_state * remove whitespace * remove async_get * linting * test_driven dev for error handling * make tests fail correctly * ensure tests fail correctly * prevent bad numeric entries * ensure no overlapping ranges * fix tests, as error caught in validation * remove redundant er call * remove reddundant arg * improves code coverage * filter for numeric states before testing overlap * adress code review * skip non numeric configs but continue * wait to avoid race condition * Better tuples name and better guard clause * better test description * more accurate description * Add comments to calculations * using typing not collections as per ruff * Apply suggestions from code review Co-authored-by: Erik Montnemery <erik@montnemery.com> * follow on from suggestions * Lazy evaluation Co-authored-by: Erik Montnemery <erik@montnemery.com> * update error text in tests * fix broken tests * move validation function call * fixes return type of above_greater_than_below. * improves codecov * fixes validation --------- Co-authored-by: Erik Montnemery <erik@montnemery.com>
This commit is contained in:
HarvsG
GitHub
parent
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commit
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4 changed files with 464 additions and 87 deletions
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@ -5,7 +5,8 @@ from __future__ import annotations
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from collections import OrderedDict
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from collections.abc import Callable
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import logging
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from typing import Any
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import math
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from typing import TYPE_CHECKING, Any, NamedTuple
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from uuid import UUID
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import voluptuous as vol
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@ -50,6 +51,7 @@ from .const import (
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ATTR_OCCURRED_OBSERVATION_ENTITIES,
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ATTR_PROBABILITY,
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ATTR_PROBABILITY_THRESHOLD,
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CONF_NUMERIC_STATE,
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CONF_OBSERVATIONS,
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CONF_P_GIVEN_F,
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CONF_P_GIVEN_T,
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@ -66,18 +68,74 @@ from .issues import raise_mirrored_entries, raise_no_prob_given_false
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_LOGGER = logging.getLogger(__name__)
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NUMERIC_STATE_SCHEMA = vol.Schema(
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{
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CONF_PLATFORM: "numeric_state",
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vol.Required(CONF_ENTITY_ID): cv.entity_id,
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vol.Optional(CONF_ABOVE): vol.Coerce(float),
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vol.Optional(CONF_BELOW): vol.Coerce(float),
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vol.Required(CONF_P_GIVEN_T): vol.Coerce(float),
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vol.Optional(CONF_P_GIVEN_F): vol.Coerce(float),
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},
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required=True,
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def _above_greater_than_below(config: dict[str, Any]) -> dict[str, Any]:
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if config[CONF_PLATFORM] == CONF_NUMERIC_STATE:
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above = config.get(CONF_ABOVE)
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below = config.get(CONF_BELOW)
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if above is None and below is None:
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_LOGGER.error(
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"For bayesian numeric state for entity: %s at least one of 'above' or 'below' must be specified",
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config[CONF_ENTITY_ID],
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)
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raise vol.Invalid(
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"For bayesian numeric state at least one of 'above' or 'below' must be specified."
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)
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if above is not None and below is not None:
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if above > below:
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_LOGGER.error(
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"For bayesian numeric state 'above' (%s) must be less than 'below' (%s)",
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above,
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below,
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)
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raise vol.Invalid("'above' is greater than 'below'")
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return config
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NUMERIC_STATE_SCHEMA = vol.All(
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vol.Schema(
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{
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CONF_PLATFORM: CONF_NUMERIC_STATE,
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vol.Required(CONF_ENTITY_ID): cv.entity_id,
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vol.Optional(CONF_ABOVE): vol.Coerce(float),
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vol.Optional(CONF_BELOW): vol.Coerce(float),
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vol.Required(CONF_P_GIVEN_T): vol.Coerce(float),
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vol.Optional(CONF_P_GIVEN_F): vol.Coerce(float),
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},
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required=True,
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),
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_above_greater_than_below,
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)
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def _no_overlapping(configs: list[dict]) -> list[dict]:
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numeric_configs = [
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config for config in configs if config[CONF_PLATFORM] == CONF_NUMERIC_STATE
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]
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if len(numeric_configs) < 2:
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return configs
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class NumericConfig(NamedTuple):
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above: float
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below: float
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d: dict[str, list[NumericConfig]] = {}
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for _, config in enumerate(numeric_configs):
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above = config.get(CONF_ABOVE, -math.inf)
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below = config.get(CONF_BELOW, math.inf)
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entity_id: str = str(config[CONF_ENTITY_ID])
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d.setdefault(entity_id, []).append(NumericConfig(above, below))
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for ent_id, intervals in d.items():
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intervals = sorted(intervals, key=lambda tup: tup.above)
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for i, tup in enumerate(intervals):
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if len(intervals) > i + 1 and tup.below > intervals[i + 1].above:
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raise vol.Invalid(
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f"Ranges for bayesian numeric state entities must not overlap, but {ent_id} has overlapping ranges, above:{tup.above}, below:{tup.below} overlaps with above:{intervals[i+1].above}, below:{intervals[i+1].below}."
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)
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return configs
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STATE_SCHEMA = vol.Schema(
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{
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CONF_PLATFORM: CONF_STATE,
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@ -107,7 +165,8 @@ PLATFORM_SCHEMA = BINARY_SENSOR_PLATFORM_SCHEMA.extend(
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vol.Required(CONF_OBSERVATIONS): vol.Schema(
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vol.All(
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cv.ensure_list,
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[vol.Any(NUMERIC_STATE_SCHEMA, STATE_SCHEMA, TEMPLATE_SCHEMA)],
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[vol.Any(TEMPLATE_SCHEMA, STATE_SCHEMA, NUMERIC_STATE_SCHEMA)],
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_no_overlapping,
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)
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),
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vol.Required(CONF_PRIOR): vol.Coerce(float),
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@ -211,10 +270,11 @@ class BayesianBinarySensor(BinarySensorEntity):
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self.observations_by_entity = self._build_observations_by_entity()
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self.observations_by_template = self._build_observations_by_template()
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self.observation_handlers: dict[str, Callable[[Observation], bool | None]] = {
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self.observation_handlers: dict[
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str, Callable[[Observation, bool], bool | None]
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] = {
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"numeric_state": self._process_numeric_state,
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"state": self._process_state,
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"multi_state": self._process_multi_state,
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}
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async def async_added_to_hass(self) -> None:
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@ -342,8 +402,9 @@ class BayesianBinarySensor(BinarySensorEntity):
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for observation in self.observations_by_entity[entity]:
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platform = observation.platform
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observation.observed = self.observation_handlers[platform](observation)
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observation.observed = self.observation_handlers[platform](
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observation, observation.multi
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)
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local_observations[observation.id] = observation
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return local_observations
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@ -408,9 +469,7 @@ class BayesianBinarySensor(BinarySensorEntity):
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if len(entity_observations) == 1:
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continue
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for observation in entity_observations:
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if observation.platform != "state":
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continue
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observation.platform = "multi_state"
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observation.multi = True
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return observations_by_entity
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@ -437,14 +496,23 @@ class BayesianBinarySensor(BinarySensorEntity):
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return observations_by_template
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def _process_numeric_state(self, entity_observation: Observation) -> bool | None:
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def _process_numeric_state(
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self, entity_observation: Observation, multi: bool = False
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) -> bool | None:
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"""Return True if numeric condition is met, return False if not, return None otherwise."""
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entity = entity_observation.entity_id
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entity_id = entity_observation.entity_id
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# if we are dealing with numeric_state observations entity_id cannot be None
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if TYPE_CHECKING:
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assert entity_id is not None
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entity = self.hass.states.get(entity_id)
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if entity is None:
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return None
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try:
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if condition.state(self.hass, entity, [STATE_UNKNOWN, STATE_UNAVAILABLE]):
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return None
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return condition.async_numeric_state(
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result = condition.async_numeric_state(
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self.hass,
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entity,
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entity_observation.below,
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@ -452,10 +520,24 @@ class BayesianBinarySensor(BinarySensorEntity):
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None,
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entity_observation.to_dict(),
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)
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if result:
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return True
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if multi:
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state = float(entity.state)
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if (
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entity_observation.below is not None
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and state == entity_observation.below
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):
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return True
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return None
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except ConditionError:
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return None
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else:
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return False
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def _process_state(self, entity_observation: Observation) -> bool | None:
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def _process_state(
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self, entity_observation: Observation, multi: bool = False
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) -> bool | None:
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"""Return True if state conditions are met, return False if they are not.
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Returns None if the state is unavailable.
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@ -467,24 +549,13 @@ class BayesianBinarySensor(BinarySensorEntity):
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if condition.state(self.hass, entity, [STATE_UNKNOWN, STATE_UNAVAILABLE]):
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return None
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return condition.state(self.hass, entity, entity_observation.to_state)
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result = condition.state(self.hass, entity, entity_observation.to_state)
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if multi and not result:
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return None
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except ConditionError:
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return None
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def _process_multi_state(self, entity_observation: Observation) -> bool | None:
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"""Return True if state conditions are met, otherwise return None.
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Never return False as all other states should have their own probabilities configured.
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"""
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entity = entity_observation.entity_id
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try:
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if condition.state(self.hass, entity, entity_observation.to_state):
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return True
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except ConditionError:
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return None
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return None
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else:
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return result
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@property
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def extra_state_attributes(self) -> dict[str, Any]:
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