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Add repair for missing Bayesian prob_given_false
(#79303)
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@ -3,6 +3,7 @@ from __future__ import annotations
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from collections import OrderedDict
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import logging
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from typing import Any
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import voluptuous as vol
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@ -34,7 +35,7 @@ from homeassistant.helpers.template import result_as_boolean
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from homeassistant.helpers.typing import ConfigType, DiscoveryInfoType
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from . import DOMAIN, PLATFORMS
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from .repairs import raise_mirrored_entries
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from .repairs import raise_mirrored_entries, raise_no_prob_given_false
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ATTR_OBSERVATIONS = "observations"
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ATTR_OCCURRED_OBSERVATION_ENTITIES = "occurred_observation_entities"
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@ -62,7 +63,7 @@ NUMERIC_STATE_SCHEMA = vol.Schema(
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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.Required(CONF_P_GIVEN_F): 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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@ -73,7 +74,7 @@ STATE_SCHEMA = vol.Schema(
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vol.Required(CONF_ENTITY_ID): cv.entity_id,
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vol.Required(CONF_TO_STATE): cv.string,
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vol.Required(CONF_P_GIVEN_T): vol.Coerce(float),
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vol.Required(CONF_P_GIVEN_F): 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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@ -83,7 +84,7 @@ TEMPLATE_SCHEMA = vol.Schema(
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CONF_PLATFORM: CONF_TEMPLATE,
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vol.Required(CONF_VALUE_TEMPLATE): cv.template,
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vol.Required(CONF_P_GIVEN_T): vol.Coerce(float),
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vol.Required(CONF_P_GIVEN_F): 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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@ -128,6 +129,16 @@ async def async_setup_platform(
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probability_threshold = config[CONF_PROBABILITY_THRESHOLD]
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device_class = config.get(CONF_DEVICE_CLASS)
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# Should deprecate in some future version (2022.10 at time of writing) & make prob_given_false required in schemas.
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broken_observations: list[dict[str, Any]] = []
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for observation in observations:
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if CONF_P_GIVEN_F not in observation:
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text: str = f"{name}/{observation.get(CONF_ENTITY_ID,'')}{observation.get(CONF_VALUE_TEMPLATE,'')}"
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raise_no_prob_given_false(hass, observation, text)
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_LOGGER.error("Missing prob_given_false YAML entry for %s", text)
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broken_observations.append(observation)
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observations = [x for x in observations if x not in broken_observations]
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async_add_entities(
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[
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BayesianBinarySensor(
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@ -31,9 +31,24 @@ def raise_mirrored_entries(hass: HomeAssistant, observations, text: str = "") ->
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"mirrored_entry/" + text,
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breaks_in_ha_version="2022.10.0",
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is_fixable=False,
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is_persistent=False,
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severity=issue_registry.IssueSeverity.WARNING,
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translation_key="manual_migration",
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translation_placeholders={"entity": text},
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learn_more_url="https://github.com/home-assistant/core/pull/67631",
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)
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# Should deprecate in some future version (2022.10 at time of writing) & make prob_given_false required in schemas.
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def raise_no_prob_given_false(hass: HomeAssistant, observation, text: str) -> None:
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"""In previous 2022.9 and earlier, prob_given_false was optional and had a default version."""
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issue_registry.async_create_issue(
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hass,
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DOMAIN,
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f"no_prob_given_false/{text}",
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breaks_in_ha_version="2022.10.0",
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is_fixable=False,
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severity=issue_registry.IssueSeverity.ERROR,
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translation_key="no_prob_given_false",
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translation_placeholders={"entity": text},
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learn_more_url="https://github.com/home-assistant/core/pull/67631",
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)
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12
homeassistant/components/bayesian/strings.json
Normal file
12
homeassistant/components/bayesian/strings.json
Normal file
@ -0,0 +1,12 @@
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{
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"issues": {
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"manual_migration": {
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"description": "The Bayesian integration now also updates the probability if the observed `to_state`, `above`, `below`, or `value_template` evaluates to `False` rather than only `True`. So it is no longer required to have duplicate, complementary entries for each binary state. Please remove the mirrored entry for `{entity}`.",
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"title": "Manual YAML fix required for Bayesian"
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},
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"no_prob_given_false": {
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"description": "In the Bayesian integration `prob_given_false` is now a required configuration variable as there was no mathematical rationale for the previous default value. Please add this to your `configuration.yml` for `bayesian/{entity}`. These observations will be ignored until you do.",
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"title": "Manual YAML addition required for Bayesian"
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}
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}
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}
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@ -3,6 +3,10 @@
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"manual_migration": {
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"description": "The Bayesian integration now also updates the probability if the observed `to_state`, `above`, `below`, or `value_template` evaluates to `False` rather than only `True`. So it is no longer required to have duplicate, complementary entries for each binary state. Please remove the mirrored entry for `{entity}`.",
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"title": "Manual YAML fix required for Bayesian"
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},
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"no_prob_given_false": {
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"description": "In the Bayesian integration `prob_given_false` is now a required configuration variable as there was no mathematical rationale for the previous default value. Please add this to your `configuration.yml` for `bayesian/{entity}`. These observations will be ignored until you do.",
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"title": "Manual YAML addition required for Bayesian"
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}
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}
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}
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@ -587,6 +587,50 @@ async def test_mirrored_observations(hass):
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)
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async def test_missing_prob_given_false(hass):
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"""Test whether missing prob_given_false are detected and appropriate issues are created."""
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config = {
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"binary_sensor": {
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"platform": "bayesian",
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"name": "missingpgf",
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"observations": [
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{
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"platform": "state",
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"entity_id": "binary_sensor.test_monitored",
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"to_state": "on",
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"prob_given_true": 0.8,
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},
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{
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"platform": "template",
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"value_template": "{{states('sensor.test_monitored2') == 'off'}}",
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"prob_given_true": 0.79,
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},
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{
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"platform": "numeric_state",
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"entity_id": "sensor.test_monitored1",
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"above": 5,
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"prob_given_true": 0.7,
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},
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],
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"prior": 0.1,
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}
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}
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assert len(async_get(hass).issues) == 0
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assert await async_setup_component(hass, "binary_sensor", config)
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await hass.async_block_till_done()
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hass.states.async_set("sensor.test_monitored2", "on")
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await hass.async_block_till_done()
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assert len(async_get(hass).issues) == 3
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assert (
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async_get(hass).issues[
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("bayesian", "no_prob_given_false/missingpgf/sensor.test_monitored1")
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]
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is not None
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)
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async def test_probability_updates(hass):
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"""Test probability update function."""
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prob_given_true = [0.3, 0.6, 0.8]
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