Detrend ADAFs


Remove trends from timeseries data


Auto generated list version of Detrend ADAF.

In this version, the following ports from the original nodes have been changed to lists which the node loops over:

Looped Inputs


Looped Outputs


For details see the original node.


Input ports



Input ADAF

Output ports



Output ADAF with detrended data

Detrend function (detrend_function)

Function used to detrend data

Timebasis (tb)

Choose a raster to select timeseries columns from

Timeseries columns to detrend (ts)

Choose one or many timeseries columns to detrend

Signal to preview (y_axis)

Y axis combobox

To identify and remove trends in data is an important tool in the work of data analysis. For example, large background values can be reduced in order to obtain a better view of variations in the data.

In the considered node, trends of polynomial nature are identified and removed from the data arrays in the timeseries container of ADAF objects. The method used to identify the trend is an ordinary least square polynomial fit, where an upper limit with polynomial of 4th order is introduced. The detrended result is achieved by subtracting the identified polynomial from the considered timeseries.

For the node several timeseries belonging to a selected timebasis can be selected for detrending. Keep in mind that the same order of the detrend polynomials will be used even when several timeseries have been selected.

The selected timeseries arrays are overwritten by the detrended result in the outgoing file.

class node_detrend.DetrendADAFs[source]

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