2024.11.3
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Derivative

The derivative (Wikipedia) integration creates a sensor that estimates the derivative of the values provided by another sensor (the source sensor). Derivative sensors are updated upon changes of the source sensor.

For sensors that reset to zero after a power interruption and need a “non-negative derivative”, such as bandwidth counters in routers, or rain gauges, you can now use this integration directly. Ensure that the input sensor has a total_increasing state class, as this is necessary for the integration to handle resets correctly without registering significant changes in the derivative sensor.

Configuration

To add the Derivative helper to your Home Assistant instance, use this My button:

Manual configuration steps

If the above My button doesn’t work, you can also perform the following steps manually:

  • Browse to your Home Assistant instance.

  • Go to Settings > Devices & Services.

  • At the top of the screen, select the tab: Helpers.

  • In the bottom right corner, select the Create helper button.

  • From the list, select Derivative.

  • Follow the instructions on screen to complete the setup.

Name

The name the sensor should have. You can change it again later.

Input sensor

The entity providing numeric readings to create the derivative of.

Precision

Round the calculated derivative value to at most N decimal places.

Time window

The time window in which to calculate the derivative. Derivatives in this window will be averaged with a simple moving average algorithm (SMA) weighted by time. This is for instance useful for a sensor that outputs discrete values, or to filter out short duration noise. By default the derivative is calculated between two consecutive updates without any smoothing.

Metric Prefix

Metric unit to prefix the derivative result (Wikipedia).

Time unit

SI unit of time of the derivative. If this parameter is set, the unit of measurement will be set to x/y where x is the unit of the source sensor and y is the value of this parameter.

YAML configuration

Alternatively, this integration can be configured and set up manually via YAML instead. To enable the Derivative sensor in your installation, add the following to your configuration.yaml file:

# Example configuration.yaml entry
sensor:
  - platform: derivative
    source: sensor.current_speed

Configuration Variables

Looking for your configuration file?
source string Required

The entity ID of the sensor providing numeric readings

name string (Optional)

Name to use in the frontend.

Default:

source entity ID derivative

round integer (Optional, default: 3)

Round the calculated derivative value to at most N decimal places.

unit_prefix string (Optional, default: None)

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).

unit_time string (Optional, default: h)

SI unit of time of the derivative. Available units are s, min, h, d. If this parameter is set, the attribute unit_of_measurement will be set like x/y where x is the unit of the sensor given via the source parameter and y is the value given here.

unit string (Optional)

Unit of Measurement to be used for the derivative. This will overwrite the automatically set unit_of_measurement as explained above.

time_window time (Optional, default: 0)

The time window in which to calculate the derivative. Derivatives in this window will be averaged with a Simple Moving Average algorithm weighted by time. This is for instance useful for a sensor that outputs discrete values, or to filter out short duration noise. By default the derivative is calculated between two consecutive updates without any smoothing.

Temperature example

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 Δy/Δx=0 because Δy=0 !) 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 YAML configuration that uses time_window is

sensor:
  - platform: derivative
    source: sensor.temperature
    name: Temperature change per hour
    round: 1
    unit_time: h # the resulting "unit_of_measurement" will be °C/h if the sensor.temperate has set °C as its unit
    time_window: "00:30:00"  # we look at the change over the last half hour