derivative platform creates a sensor that estimates the derivative of the values provided by a source sensor.
Derivative sensors are updated upon changes of the source.
To enable Derivative Sensor in your installation, add the following to your
# Example configuration.yaml entry sensor: - platform: derivative source: sensor.current_speed
The entity ID of the sensor providing numeric readings
Name to use in the frontend.
source entity ID meter
Round the calculated derivative value to at most N decimal places.
Metric unit to prefix the derivative result (Wikipedia]). Available symbols are “n” (1e-9), “µ” (1e-6), “m” (1e-3), “k” (1e3), “M” (1e6), “G” (1e9), “T” (1e12).
SI unit of time to integrate over. Available units are s, min, h, d.
Unit of Measurement to be used for the derivative.
The time window in which to calculate the derivative. This is useful for sensor that output discrete values. By default the derivative is calculated between two consecutive updates.
For example, you have a temperature sensor
sensor.temperature that outputs a value every few seconds, but rounds to the nearest half number.
That means that two consecutive output values might be the same (so the derivative is
However, the temperature might actually be changing over time.
In order to capture this, you should use a
time_window, such that immediate jumps don’t result in high derivatives and that after the next sensor update, the derivatives doesn’t vanish to zero.
An example configuration that uses
sensor: - platform: derivative source: sensor.temperature name: Temperature change per hour round: 1 unit_time: h time_window: "00:30:00" # we look at the change over the last half hour