Detrend ADAF

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.DetrendADAFNode

Detrend timeseries in an ADAF.

Ref. nodes:

Detrend ADAFs

Inputs:

port1 : adaf

Input ADAF

Outputs:

port1 : adaf

Output ADAF with detrended data

Configuration:

Time basis column

Choose a raster to select timeseries columns from

Timeseries columns

Choose one or many timeseries columns to detrend

Detrend function

Function used to detrend data

X axis

X axis combobox

Y axis

Y axis combobox