FilterOutliersTComputePhasorValue Class

Returns a series of values that represent the core data around the mean, excluding outliers, using Z-score. The confidence parameter, optional, is a floating-point value, suffixed with '%' representing a percentage, that must be greater than zero and less than one-hundred, that specifies the amount of data to retain around the mean, representing the central portion of the dataset - defaults to 95%. Second parameter, invertFilter, optional, is a boolean flag that determines if outliers should be rejected or retained - default is false, i.e., keep core data rejecting outliers; otherwise, true excludes core data and retains only outliers. Third parameter, minSamples, optional, is an integer value that specifies the minimum number of samples required for outlier detection - defaults to 20 for single series temporal analysis and 3 for multi-series slice analysis; if fewer samples are provided, the function returns the entire dataset unfiltered to ensure improved statistical validity of the Z-score calculations, or no data when invertFilter is true. If all values are considered identical, i.e., the standard deviation is zero, function will return the entire dataset unfiltered, or no data when invertFilter is true, since this represents a uniform distribution. The confidence parameter value can either be a constant value or a named target available from the expression. Any target values that fall between 0 and 1 will be treated as a percentage.

public class ComputePhasorValue : FilterOutliers<PhasorValue>

Public Class ComputePhasorValue
	Inherits FilterOutliers(Of PhasorValue)

public ref class ComputePhasorValue : public FilterOutliers<PhasorValue>

type ComputePhasorValue = 
    class
        inherit FilterOutliers<PhasorValue>
    end

GrafanaAdapters.Functions.BuiltIn.ComputePhasorValue = function();

Type.createClass(
	'GrafanaAdapters.Functions.BuiltIn.ComputePhasorValue',
	GrafanaAdapters.Functions.BuiltIn.FilterOutliers`1);