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+---
+layout: page
+title: "Filter Sensor"
+description: "Instructions how to integrate Data Filter Sensors into Home Assistant."
+date: 2018-02-20
+sidebar: true
+comments: false
+sharing: true
+footer: true
+ha_category: Sensor
+ha_release: 0.65
+ha_iot_class: "Local Push"
+logo: home-assistant.png
+---
+
+The `filter` platform enables sensors that process the states of other entities.
+
+`filter` applies a signal processing algorithm to a sensor, previous and current states, and generates a `new state` given the chosen algorithm.
+
+
+
+
+
+To enable Filter Sensors in your installation, add the following to your `configuration.yaml` file:
+
+
+```yaml
+# Example configuration.yaml entry
+sensor:
+ - platform: filter
+ name: "filtered realistic humidity"
+ entity_id: sensor.realistic_humidity
+ filters:
+ - filter: outlier
+ window_size: 4
+ radius: 4.0
+ - filter: lowpass
+ time_constant: 10
+ precision: 2
+```
+
+Filters can be chained and are applied according to the order present in the configuration file.
+
+{% configuration %}
+entity_id:
+ description: The entity ID of the sensor to be filtered.
+ required: true
+ type: string
+name:
+ description: Name to use in the frontend.
+ required: false
+ type: string
+filters:
+ description: Filters to be used.
+ required: true
+ type: map
+ keys:
+ filter:
+ description: Algorithm to be used to filter data. Available filters are `lowpass`, `outlier` and `throttle`.
+ required: true
+ type: string
+ window_size:
+ description: Size of the window of previous states.
+ required: false
+ type: int
+ default: 5
+ precision:
+ description: See [_lowpass_](#low-pass) filter. Defines the precision of the filtered state, through the argument of round().
+ required: false
+ type: int
+ default: None
+ time_constant:
+ description: See [_lowpass_](#low-pass) filter. Loosely relates to the amount of time it takes for a state to influence the output.
+ required: false
+ type: int
+ default: 10
+ radius:
+ description: See [_outlier_](#outlier) filter. Band radius from median of previous states.
+ required: false
+ type: float
+ default: 2.0
+{% endconfiguration %}
+
+## {% linkable_title Filters %}
+
+### {% linkable_title Low-pass %}
+
+The Low-pass filter (`lowpass`) is one of signal processing most common filters, as it smooths data by shortcuting peaks and valleys.
+
+The included Low-pass filter is very basic and is based on a moving average, in which the previous data point is weighted with the new data point.
+
+```python
+B = 1.0 / time_constant
+A = 1.0 - B
+LowPass(state) = A * previous_state + B * state
+```
+
+The returned value is rounded to the number of decimals defined in (`precision`).
+
+### {% linkable_title Outlier %}
+
+The Outlier filter (`outlier`) is a basic Band-stop filter, as it cuts out any value outside a specific range.
+
+The included Outlier filter will discard any value beyond a band centered on the median of the previous values, replacing it with the median value of the previous values. If inside the band, the
+
+```python
+distance = abs(state - median(previous_states))
+
+if distance > radius:
+ median(previous_states)
+else:
+ state
+```
+
+### {% linkable_title Throttle %}
+
+The Throttle filter (`throttle`) will only update the state of the sensor for the first state in the window. This means the filter will skip all other values.
+
+To adjust the rate you need to set the window_size. To throttle a sensor down to 10%, the `window_size` should be set to 10, for 50% should be set to 2.
+
+This filter is relevant when you have a sensor which produces states at a very high-rate, which you might want to throttle down for storing or visualization purposes.
+
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