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Paulus Schoutsen
parent
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2676 changed files with 163166 additions and 140084 deletions
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@ -3,66 +3,87 @@ from collections import OrderedDict
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import voluptuous as vol
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from homeassistant.components.binary_sensor import (
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PLATFORM_SCHEMA, BinarySensorDevice)
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from homeassistant.components.binary_sensor import PLATFORM_SCHEMA, BinarySensorDevice
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from homeassistant.const import (
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CONF_ABOVE, CONF_BELOW, CONF_DEVICE_CLASS, CONF_ENTITY_ID, CONF_NAME,
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CONF_PLATFORM, CONF_STATE, CONF_VALUE_TEMPLATE, STATE_UNKNOWN)
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CONF_ABOVE,
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CONF_BELOW,
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CONF_DEVICE_CLASS,
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CONF_ENTITY_ID,
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CONF_NAME,
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CONF_PLATFORM,
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CONF_STATE,
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CONF_VALUE_TEMPLATE,
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STATE_UNKNOWN,
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)
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from homeassistant.core import callback
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from homeassistant.helpers import condition
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import homeassistant.helpers.config_validation as cv
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from homeassistant.helpers.event import async_track_state_change
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ATTR_OBSERVATIONS = 'observations'
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ATTR_PROBABILITY = 'probability'
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ATTR_PROBABILITY_THRESHOLD = 'probability_threshold'
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ATTR_OBSERVATIONS = "observations"
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ATTR_PROBABILITY = "probability"
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ATTR_PROBABILITY_THRESHOLD = "probability_threshold"
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CONF_OBSERVATIONS = 'observations'
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CONF_PRIOR = 'prior'
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CONF_OBSERVATIONS = "observations"
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CONF_PRIOR = "prior"
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CONF_TEMPLATE = "template"
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CONF_PROBABILITY_THRESHOLD = 'probability_threshold'
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CONF_P_GIVEN_F = 'prob_given_false'
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CONF_P_GIVEN_T = 'prob_given_true'
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CONF_TO_STATE = 'to_state'
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CONF_PROBABILITY_THRESHOLD = "probability_threshold"
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CONF_P_GIVEN_F = "prob_given_false"
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CONF_P_GIVEN_T = "prob_given_true"
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CONF_TO_STATE = "to_state"
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DEFAULT_NAME = "Bayesian Binary Sensor"
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DEFAULT_PROBABILITY_THRESHOLD = 0.5
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NUMERIC_STATE_SCHEMA = vol.Schema({
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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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}, required=True)
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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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)
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STATE_SCHEMA = vol.Schema({
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CONF_PLATFORM: CONF_STATE,
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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.Optional(CONF_P_GIVEN_F): vol.Coerce(float)
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}, required=True)
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STATE_SCHEMA = vol.Schema(
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{
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CONF_PLATFORM: CONF_STATE,
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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.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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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.Optional(CONF_P_GIVEN_F): vol.Coerce(float)
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}, required=True)
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TEMPLATE_SCHEMA = vol.Schema(
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{
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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.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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PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend({
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vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
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vol.Optional(CONF_DEVICE_CLASS): cv.string,
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vol.Required(CONF_OBSERVATIONS):
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vol.Schema(vol.All(cv.ensure_list,
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[vol.Any(NUMERIC_STATE_SCHEMA, STATE_SCHEMA,
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TEMPLATE_SCHEMA)])),
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vol.Required(CONF_PRIOR): vol.Coerce(float),
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vol.Optional(CONF_PROBABILITY_THRESHOLD,
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default=DEFAULT_PROBABILITY_THRESHOLD): vol.Coerce(float),
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})
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PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend(
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{
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vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,
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vol.Optional(CONF_DEVICE_CLASS): cv.string,
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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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)
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),
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vol.Required(CONF_PRIOR): vol.Coerce(float),
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vol.Optional(
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CONF_PROBABILITY_THRESHOLD, default=DEFAULT_PROBABILITY_THRESHOLD
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): vol.Coerce(float),
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}
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)
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def update_probability(prior, prob_true, prob_false):
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@ -73,8 +94,7 @@ def update_probability(prior, prob_true, prob_false):
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return probability
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async def async_setup_platform(hass, config, async_add_entities,
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discovery_info=None):
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async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
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"""Set up the Bayesian Binary sensor."""
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name = config.get(CONF_NAME)
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observations = config.get(CONF_OBSERVATIONS)
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@ -82,17 +102,20 @@ async def async_setup_platform(hass, config, async_add_entities,
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probability_threshold = config.get(CONF_PROBABILITY_THRESHOLD)
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device_class = config.get(CONF_DEVICE_CLASS)
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async_add_entities([
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BayesianBinarySensor(
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name, prior, observations, probability_threshold, device_class)
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], True)
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async_add_entities(
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[
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BayesianBinarySensor(
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name, prior, observations, probability_threshold, device_class
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)
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],
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True,
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)
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class BayesianBinarySensor(BinarySensorDevice):
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"""Representation of a Bayesian sensor."""
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def __init__(self, name, prior, observations, probability_threshold,
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device_class):
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def __init__(self, name, prior, observations, probability_threshold, device_class):
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"""Initialize the Bayesian sensor."""
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self._name = name
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self._observations = observations
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@ -106,32 +129,31 @@ class BayesianBinarySensor(BinarySensorDevice):
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to_observe = set()
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for obs in self._observations:
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if 'entity_id' in obs:
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to_observe.update(set([obs.get('entity_id')]))
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if 'value_template' in obs:
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to_observe.update(
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set(obs.get(CONF_VALUE_TEMPLATE).extract_entities()))
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if "entity_id" in obs:
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to_observe.update(set([obs.get("entity_id")]))
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if "value_template" in obs:
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to_observe.update(set(obs.get(CONF_VALUE_TEMPLATE).extract_entities()))
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self.entity_obs = dict.fromkeys(to_observe, [])
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for ind, obs in enumerate(self._observations):
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obs['id'] = ind
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if 'entity_id' in obs:
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self.entity_obs[obs['entity_id']].append(obs)
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if 'value_template' in obs:
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obs["id"] = ind
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if "entity_id" in obs:
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self.entity_obs[obs["entity_id"]].append(obs)
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if "value_template" in obs:
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for ent in obs.get(CONF_VALUE_TEMPLATE).extract_entities():
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self.entity_obs[ent].append(obs)
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self.watchers = {
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'numeric_state': self._process_numeric_state,
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'state': self._process_state,
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'template': self._process_template
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"numeric_state": self._process_numeric_state,
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"state": self._process_state,
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"template": self._process_template,
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}
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async def async_added_to_hass(self):
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"""Call when entity about to be added."""
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@callback
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def async_threshold_sensor_state_listener(entity, old_state,
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new_state):
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def async_threshold_sensor_state_listener(entity, old_state, new_state):
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"""Handle sensor state changes."""
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if new_state.state == STATE_UNKNOWN:
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return
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@ -139,33 +161,32 @@ class BayesianBinarySensor(BinarySensorDevice):
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entity_obs_list = self.entity_obs[entity]
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for entity_obs in entity_obs_list:
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platform = entity_obs['platform']
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platform = entity_obs["platform"]
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self.watchers[platform](entity_obs)
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prior = self.prior
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for obs in self.current_obs.values():
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prior = update_probability(
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prior, obs['prob_true'], obs['prob_false'])
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prior = update_probability(prior, obs["prob_true"], obs["prob_false"])
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self.probability = prior
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self.hass.async_add_job(self.async_update_ha_state, True)
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async_track_state_change(
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self.hass, self.entity_obs, async_threshold_sensor_state_listener)
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self.hass, self.entity_obs, async_threshold_sensor_state_listener
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)
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def _update_current_obs(self, entity_observation, should_trigger):
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"""Update current observation."""
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obs_id = entity_observation['id']
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obs_id = entity_observation["id"]
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if should_trigger:
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prob_true = entity_observation['prob_given_true']
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prob_false = entity_observation.get(
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'prob_given_false', 1 - prob_true)
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prob_true = entity_observation["prob_given_true"]
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prob_false = entity_observation.get("prob_given_false", 1 - prob_true)
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self.current_obs[obs_id] = {
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'prob_true': prob_true,
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'prob_false': prob_false
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"prob_true": prob_true,
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"prob_false": prob_false,
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}
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else:
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@ -173,21 +194,26 @@ class BayesianBinarySensor(BinarySensorDevice):
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def _process_numeric_state(self, entity_observation):
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"""Add entity to current_obs if numeric state conditions are met."""
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entity = entity_observation['entity_id']
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entity = entity_observation["entity_id"]
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should_trigger = condition.async_numeric_state(
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self.hass, entity,
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entity_observation.get('below'),
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entity_observation.get('above'), None, entity_observation)
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self.hass,
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entity,
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entity_observation.get("below"),
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entity_observation.get("above"),
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None,
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entity_observation,
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)
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self._update_current_obs(entity_observation, should_trigger)
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def _process_state(self, entity_observation):
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"""Add entity to current observations if state conditions are met."""
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entity = entity_observation['entity_id']
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entity = entity_observation["entity_id"]
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should_trigger = condition.state(
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self.hass, entity, entity_observation.get('to_state'))
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self.hass, entity, entity_observation.get("to_state")
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)
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self._update_current_obs(entity_observation, should_trigger)
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@ -196,7 +222,8 @@ class BayesianBinarySensor(BinarySensorDevice):
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template = entity_observation.get(CONF_VALUE_TEMPLATE)
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template.hass = self.hass
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should_trigger = condition.async_template(
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self.hass, template, entity_observation)
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self.hass, template, entity_observation
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)
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self._update_current_obs(entity_observation, should_trigger)
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@property
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