docs-v2/content/flux/v0/stdlib/experimental/integral.md

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title description menu weight flux/v0/tags introduced
experimental.integral() function `experimental.integral()` computes the area under the curve per unit of time of subsequent non-null records.
flux_v0_ref
name parent identifier
experimental.integral experimental experimental/integral
101
transformations
aggregates
0.106.0

experimental.integral() computes the area under the curve per unit of time of subsequent non-null records.

The curve is defined using _time as the domain and record values as the range.

Input tables must have _start, _stop, _time, and _valuecolumns._startand_stop` must be part of the group key.

Function type signature
(<-tables: stream[{A with _value: B, _time: time}], ?interpolate: string, ?unit: duration) => stream[{A with _value: B}]

{{% caption %}} For more information, see Function type signatures. {{% /caption %}}

Parameters

unit

Time duration used to compute the integral.

interpolate

Type of interpolation to use. Default is "" (no interpolation).

Use one of the following interpolation options:

  • empty string ("") for no interpolation
  • linear

tables

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

Examples

Calculate the integral

import "experimental"
import "sampledata"

data =
    sampledata.int()
        |> range(start: sampledata.start, stop: sampledata.stop)

data
    |> experimental.integral(unit: 20s)

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

*_start *_stop _time _value *tag
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:00Z -2 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:10Z 10 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:20Z 7 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:30Z 17 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:40Z 15 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:50Z 4 t1
*_start *_stop _time _value *tag
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:00Z 19 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:10Z 4 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:20Z -3 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:30Z 19 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:40Z 13 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:50Z 1 t2

Output data

*_start *_stop *tag _value
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z t1 25
*_start *_stop *tag _value
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z t2 21.5

{{% /expand %}} {{< /expand-wrapper >}}

Calculate the integral with linear interpolation

import "experimental"
import "sampledata"

data =
    sampledata.int()
        |> range(start: sampledata.start, stop: sampledata.stop)

data
    |> experimental.integral(unit: 20s, interpolate: "linear")

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

*_start *_stop _time _value *tag
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:00Z -2 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:10Z 10 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:20Z 7 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:30Z 17 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:40Z 15 t1
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:50Z 4 t1
*_start *_stop _time _value *tag
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:00Z 19 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:10Z 4 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:20Z -3 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:30Z 19 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:40Z 13 t2
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z 2021-01-01T00:00:50Z 1 t2

Output data

*_start *_stop *tag _value
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z t1 24.25
*_start *_stop *tag _value
2021-01-01T00:00:00Z 2021-01-01T00:01:00Z t2 19

{{% /expand %}} {{< /expand-wrapper >}}