CStats:Class Description

CStats Class

The CStats class computes statistics or estimator values for numeric data. The data may be in the form of a Lua Table or an object of class CImage, CArray, or CMatrix. For the CImage and CMatrix classes, you can optionally specify a rectangle that bounds the data region. For a CImage, the data may have multiple channels, as for an RGB image. This class uses the same algorithms as the CImCombine class.

Some of the methods in this class have equivalent non-class functions that do not use the CStats class; see Table Functions.

Usage

Construction	Object = CStats:new()
Destruction	Object:delete()

Properties (Variables)

This class has no exposed properties.

Construction & Destruction

new	Creates a new instance of the CImage class.
delete	Deletes the CStats object from memory.

Accessing and Initializing Properties

SetImage

Attaches an image and rectangle to the CStats object for measurements. You can use this method if you want to measure only CImage objects.

(Deprecated - do not use in new scripts)

GetErrMsg

Returns the error message for a method failed.

GetStatus

Returns a non-zero error code if a method failed.

Standard Estimators

ContraMean	Computes the contra-power mean and standard deviation.
GeomMean	Computes the geometric mean and standard deviation.
Mean	Computes the mean and standard deviation.
Median	Computes the median and standard deviation.
Sdev	Computes the standard deviation.
SdevValue	Computes the standard deviation about the specified value.
YpMean	Computes the Y-power Mean and standard deviation.

Data Rejection Methods

AlphaClipMean	Computes the alpha-clipped mean and standard deviation after clipping nHigh and nLow values from the distribution.
MaxClipMean	Computes the mean value with the maximum data value discarded, plus the standard deviation.
MinClipMean	Computes the mean value with the minimum data value discarded, plus the standard deviation.
MinMaxClipMean	Computes the mean value with its minimum and maximum data values discarded, plus the standard deviation.
MtmSigmaClipMean	Computes the Modified Trimmed Mean and standard deviation.
RankClipMean	Computes the rank percentile clipped mean and the standard deviation.
SigmaClipMean	Computes the sigma clipped mean and standard deviation.
SdevClip	Computes the standard deviation after clipping the nHigh highest and nLow lowest values from the distribution.
SdevClipValue	Computes the standard deviation about a specified mean, after clipping the nHigh highest and nLow lowest values from the sample.

Characterising the Distribution

Kurtosis	Computes the kurtosis parameter for assessing the peakiness of the data distribution.
Max	Computes the maximum value and its coordinate.
MaxPix	Computes the coordinate of the maximum value.
Min	Computes the minimum value and its coordinate.
MinPix	Computes the coordinate of the minimum value.
Moment	Computs the n-th moment of the data distribution.
Rank	Computes the percentile rank value and standard deviation.
Skewness	Computes the skewness parameter for assessing the symmetry of the data distribution.
Sdev	Computes the standard deviation.
SdevValue	Computes the standard deviation about the specified value.