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title description menu weight flux/v0/tags
polyline.rdp() function `polyline.rdp()` applies the Ramer Douglas Peucker (RDP) algorithm to input data to downsample curves composed of line segments into visually indistinguishable curves with fewer points.
flux_v0_ref
name parent identifier
polyline.rdp experimental/polyline experimental/polyline/rdp
201
transformations

polyline.rdp() applies the Ramer Douglas Peucker (RDP) algorithm to input data to downsample curves composed of line segments into visually indistinguishable curves with fewer points.

Function type signature
(
    <-tables: stream[A],
    ?epsilon: float,
    ?retention: float,
    ?timeColumn: string,
    ?valColumn: string,
) => stream[B] where A: Record, B: Record

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

Parameters

valColumn

Column with Y axis values of the given curve. Default is _value.

timeColumn

Column with X axis values of the given curve. Default is _time.

epsilon

Maximum tolerance value that determines the amount of compression.

Epsilon should be greater than 0.0.

retention

Percentage of points to retain after downsampling.

Retention rate should be between 0.0 and 100.0.

tables

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

Examples

Downsample data using the RDP algorithm

When using polyline.rdp(), leave both epsilon and retention unspecified to automatically calculate the maximum tolerance for producing a visually indistinguishable curve.

import "experimental/polyline"

data
    |> polyline.rdp()

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

Input data

_time _value
2023-04-06T14:59:30Z 10.56555566168836
2023-04-06T14:59:40Z -29.76098586714259
2023-04-06T14:59:50Z -67.50435038579738
2023-04-06T15:00:00Z -16.758669047964453
2023-04-06T15:00:10Z -47.25865245658065
2023-04-06T15:00:20Z 66.16082461651365
2023-04-06T15:00:30Z -0.9179216017921821
2023-04-06T15:00:40Z -56.89169240573004
2023-04-06T15:00:50Z 11.358605472976624
2023-04-06T15:01:00Z 28.71147881415803
2023-04-06T15:01:10Z -30.928830759588756
2023-04-06T15:01:20Z -22.411848631056067
2023-04-06T15:01:30Z 17.05503606764129
2023-04-06T15:01:40Z 9.834382683760559
2023-04-06T15:01:50Z -12.62058579127679
2023-04-06T15:02:00Z -44.44668391211515

Output data

_time _value
2023-04-06T14:59:30Z 10.56555566168836
2023-04-06T14:59:40Z -29.76098586714259
2023-04-06T14:59:50Z -67.50435038579738
2023-04-06T15:00:00Z -16.758669047964453
2023-04-06T15:00:10Z -47.25865245658065
2023-04-06T15:00:20Z 66.16082461651365
2023-04-06T15:00:30Z -0.9179216017921821
2023-04-06T15:00:40Z -56.89169240573004
2023-04-06T15:00:50Z 11.358605472976624
2023-04-06T15:01:00Z 28.71147881415803
2023-04-06T15:01:10Z -30.928830759588756
2023-04-06T15:01:20Z -22.411848631056067
2023-04-06T15:01:30Z 17.05503606764129
2023-04-06T15:01:40Z 9.834382683760559
2023-04-06T15:01:50Z -12.62058579127679
2023-04-06T15:02:00Z -44.44668391211515

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

Downsample data using the RDP algorithm with an epsilon of 1.5

import "experimental/polyline"

data
    |> polyline.rdp(epsilon: 1.5)

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

Input data

_time _value
2023-04-06T14:59:40Z 10.56555566168836
2023-04-06T14:59:50Z -29.76098586714259
2023-04-06T15:00:00Z -67.50435038579738
2023-04-06T15:00:10Z -16.758669047964453
2023-04-06T15:00:20Z -47.25865245658065
2023-04-06T15:00:30Z 66.16082461651365
2023-04-06T15:00:40Z -0.9179216017921821
2023-04-06T15:00:50Z -56.89169240573004
2023-04-06T15:01:00Z 11.358605472976624
2023-04-06T15:01:10Z 28.71147881415803
2023-04-06T15:01:20Z -30.928830759588756
2023-04-06T15:01:30Z -22.411848631056067
2023-04-06T15:01:40Z 17.05503606764129
2023-04-06T15:01:50Z 9.834382683760559
2023-04-06T15:02:00Z -12.62058579127679
2023-04-06T15:02:10Z -44.44668391211515

Output data

_time _value
2023-04-06T14:59:40Z 10.56555566168836
2023-04-06T15:00:00Z -67.50435038579738
2023-04-06T15:00:10Z -16.758669047964453
2023-04-06T15:00:20Z -47.25865245658065
2023-04-06T15:00:30Z 66.16082461651365
2023-04-06T15:00:40Z -0.9179216017921821
2023-04-06T15:00:50Z -56.89169240573004
2023-04-06T15:01:00Z 11.358605472976624
2023-04-06T15:01:10Z 28.71147881415803
2023-04-06T15:01:20Z -30.928830759588756
2023-04-06T15:01:30Z -22.411848631056067
2023-04-06T15:01:40Z 17.05503606764129
2023-04-06T15:01:50Z 9.834382683760559
2023-04-06T15:02:00Z -12.62058579127679
2023-04-06T15:02:10Z -44.44668391211515

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

Downsample data using the RDP algorithm with a retention rate of 90%

import "experimental/polyline"

data
    |> polyline.rdp(retention: 90.0)

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

Input data

_time _value
2023-04-06T14:59:40Z 10.56555566168836
2023-04-06T14:59:50Z -29.76098586714259
2023-04-06T15:00:00Z -67.50435038579738
2023-04-06T15:00:10Z -16.758669047964453
2023-04-06T15:00:20Z -47.25865245658065
2023-04-06T15:00:30Z 66.16082461651365
2023-04-06T15:00:40Z -0.9179216017921821
2023-04-06T15:00:50Z -56.89169240573004
2023-04-06T15:01:00Z 11.358605472976624
2023-04-06T15:01:10Z 28.71147881415803
2023-04-06T15:01:20Z -30.928830759588756
2023-04-06T15:01:30Z -22.411848631056067
2023-04-06T15:01:40Z 17.05503606764129
2023-04-06T15:01:50Z 9.834382683760559
2023-04-06T15:02:00Z -12.62058579127679
2023-04-06T15:02:10Z -44.44668391211515

Output data

_time _value
2023-04-06T14:59:40Z 10.56555566168836
2023-04-06T15:00:00Z -67.50435038579738
2023-04-06T15:00:10Z -16.758669047964453
2023-04-06T15:00:20Z -47.25865245658065
2023-04-06T15:00:30Z 66.16082461651365
2023-04-06T15:00:40Z -0.9179216017921821
2023-04-06T15:00:50Z -56.89169240573004
2023-04-06T15:01:00Z 11.358605472976624
2023-04-06T15:01:10Z 28.71147881415803
2023-04-06T15:01:20Z -30.928830759588756
2023-04-06T15:01:30Z -22.411848631056067
2023-04-06T15:01:40Z 17.05503606764129
2023-04-06T15:01:50Z 9.834382683760559
2023-04-06T15:02:10Z -44.44668391211515

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