Detrend ADAFs

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.DetrendADAFsNode[source]

Elementwise detrend timeseries in ADAFs.

Inputs:
port1
: ADAFs

ADAFs with data.

Outputs:
port1
: ADAFs

ADAFs with detrended data.

Configuration:
Detrend function

Choose order of detrend polynomial.

Time basis column

Choose a raster to select time series columns from.

Time series columns

Choose one or many time series columns to detrend.

Opposite node:
Ref. nodes:

Detrend ADAF