docs-v2/content/flux/v0/stdlib/universe/doubleema.md

title	description	menu	weight	flux/v0/tags	introduced
doubleEMA() function	`doubleEMA()` returns the double exponential moving average (DEMA) of values in the `_value` column grouped into `n` number of points, giving more weight to recent data.	flux_v0_ref name parent identifier doubleEMA universe universe/doubleEMA	101	transformations	0.38.0

doubleEMA() returns the double exponential moving average (DEMA) of values in the _value column grouped into n number of points, giving more weight to recent data.

Double exponential moving average rules

• A double exponential moving average is defined as doubleEMA = 2 * EMA_N - EMA of EMA_N.
  • EMA is an exponential moving average.
  • N = n is the period used to calculate the EMA.
• A true double exponential moving average requires at least 2 * n - 1 values. If not enough values exist to calculate the double EMA, it returns a NaN value.
• doubleEMA() inherits all exponentialMovingAverage() rules.

Function type signature

(<-tables: stream[{A with _value: B}], n: int) => stream[C] where B: Numeric, C: Record

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Parameters

n

({{< req >}}) Number of points to average.

tables

Input data. Default is piped-forward data (<-).

Examples

Calculate a three point double exponential moving average

import "sampledata"

sampledata.int()
    |> doubleEMA(n: 3)

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Input data

_time	_value	*tag
2021-01-01T00:00:00Z	-2	t1
2021-01-01T00:00:10Z	10	t1
2021-01-01T00:00:20Z	7	t1
2021-01-01T00:00:30Z	17	t1
2021-01-01T00:00:40Z	15	t1
2021-01-01T00:00:50Z	4	t1

_time	_value	*tag
2021-01-01T00:00:00Z	19	t2
2021-01-01T00:00:10Z	4	t2
2021-01-01T00:00:20Z	-3	t2
2021-01-01T00:00:30Z	19	t2
2021-01-01T00:00:40Z	13	t2
2021-01-01T00:00:50Z	1	t2

Output data

_time	_value	*tag
2021-01-01T00:00:40Z	16.333333333333336	t1
2021-01-01T00:00:50Z	7.916666666666668	t1

_time	_value	*tag
2021-01-01T00:00:40Z	15.027777777777779	t2
2021-01-01T00:00:50Z	5.034722222222221	t2

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