Detrend ADAF¶
Remove trends from timeseries data
Documentation¶
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.
Definition¶
Input ports¶
- port1 adaf
Input ADAF
Output ports¶
- port1 adaf
Output ADAF with detrended data
Configuration¶
- 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
Examples¶
Implementation¶
- class node_detrend.DetrendADAF[source]
