Post filtering

General overview

After irradiance quality check, it is possible that some scattered valid flags are left in the dataset. These individual flags often don't provide much value, and we want to remove them. Automatic post-filtering provides the user the possibility to remove such flags.

Component	Description
Heatmap flag plot	Area where flagged data are visualized as series of yearly heatmaps or one big heatmap plot showing the overall data picture, with post-filtered data highlighted.
Time series flag plot	Visualization of irradiance flagged data as time series and bar plot. One plot per one irrad. component. Post-filtered data are highlighted.
Quality control tab	Text summary of flags for the given dataset.
Dataset	Dataset on which to perform post-filtering control.
Irradiation columns	List of irradiation columns on which to perform post-filtering.
Central hours of the day	Minimum required size of a continuous group of values. For example, if value is 3, all groups of flags with size 3 or less will be filtered.
Morning hours	Minimum required size of a continuous group of morning values. For example, if value is 3, all groups of flags with size 3 or less will be filtered.
Evening hours	Minimum required size of a continuous group of evening values. For example, if value is 3, all groups of flags with size 3 or less will be filtered.
Minimum required valid flags	Percentage of daytime records of valid flags, that will be filtered out.
Run between	If checked, run post-filtering control between custom dates.
Plot settings	Column to plot in graphs.
Split heatmap by year	If checked, plots are split by years.
View in time zone	If checked, data are shown in UTC chosen.
Run	Will start the process of postfiltering. The result of the procedure is flagging for every record of data. Preview dialog (Quality report) is provided to let users review the results.
Save flags	Save flags and QC status “POST_FILTERING_CHECK” will be assign to the dataset.
Cancel	Close Postfiltering window.