Use entity class attributes for bayesian (#52831)
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1 changed files with 7 additions and 26 deletions
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@ -129,13 +129,15 @@ async def async_setup_platform(hass, config, async_add_entities, discovery_info=
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class BayesianBinarySensor(BinarySensorEntity):
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"""Representation of a Bayesian sensor."""
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_attr_should_poll = False
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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._attr_name = name
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self._observations = observations
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self._probability_threshold = probability_threshold
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self._device_class = device_class
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self._deviation = False
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self._attr_device_class = device_class
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self._attr_is_on = False
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self._callbacks = []
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self.prior = prior
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@ -238,12 +240,12 @@ class BayesianBinarySensor(BinarySensorEntity):
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self.current_observations.update(self._initialize_current_observations())
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self.probability = self._calculate_new_probability()
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self._deviation = bool(self.probability >= self._probability_threshold)
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self._attr_is_on = bool(self.probability >= self._probability_threshold)
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@callback
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def _recalculate_and_write_state(self):
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self.probability = self._calculate_new_probability()
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self._deviation = bool(self.probability >= self._probability_threshold)
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self._attr_is_on = bool(self.probability >= self._probability_threshold)
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self.async_write_ha_state()
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def _initialize_current_observations(self):
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@ -363,30 +365,9 @@ class BayesianBinarySensor(BinarySensorEntity):
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except ConditionError:
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return False
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@property
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def name(self):
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"""Return the name of the sensor."""
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return self._name
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@property
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def is_on(self):
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"""Return true if sensor is on."""
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return self._deviation
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@property
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def should_poll(self):
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"""No polling needed."""
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return False
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@property
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def device_class(self):
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"""Return the sensor class of the sensor."""
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return self._device_class
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@property
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def extra_state_attributes(self):
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"""Return the state attributes of the sensor."""
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attr_observations_list = [
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obs.copy() for obs in self.current_observations.values() if obs is not None
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]
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