Detrend ADAF


Remove trends from timeseries data


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

In this node, trends of polynomial nature can be identified and removed from the timeseries of the input ADAF. The method used to identify the trend is an ordinary least square fit of the selected order of polynomial. The polynomial trend is then subtracted from the 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 replaced by the detrended result in the output.


Input ports

port1 adaf

Input ADAF

Output ports

port1 adaf

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



class node_detrend.DetrendADAF[source]