CStats:MinClipMean

The MinClipMean method computes the minimum-clipped mean value of a data sample. This method calculates the mean after rexcluding the minimum value from the sample. Use this method to avoid a biased result when the region is known to contain one deviant, low pixel value. The sample may be a Lua table or a class object of type CImage, CArray, or CMatrix. For CImage and CMatrix objects, an optional CRect object can be used to define the points used in the calculation.

Syntax

nMean, nStdDev = CStats:MinClipMean( table )

nMean, nStdDev = CStats:MinClipMean( CImage )

nMean, nStdDev = CStats:MinClipMean( CImage, CRect )

nMean, nStdDev = CStats:MinClipMean( CArray )

nMean, nStdDev = CStats:MinClipMean( CArray, CRect )

nMean, nStdDev = CStats:MinClipMean( CMatrix )

where

table is a lua table containing the data.

CImage, CArray, and CMatrix are class objects containing the data to measure,

CRect is a CRect rectangle object that defines the region to measure.

nMean and nStdDev are the min-clipped mean and standard deviation of the data. On failure, 0,0 is returned.

Examples

Suppose that CImage object I and CRect object R exist. The following script returns the mean value inside a rectangle on the image, discarding the 1 lowest pixel value:

nMean = S:MinClipMean( I, R )	-- returns the mean value for this CImage and CRect
Printf("mean=%lg\n", nMean )	-- list the results
S:delete()	-- when done with S, remove it from memory

The following script returns the min-clipped mean value for a table of data:

S = CStats:new()	-- create a CStats object
t = { 4, 4, 2, 5, 6.4, -1.42, -12, 3.4 }	-- create some data in a table
Printf("mean=%lg\n", S:MinClipMean(t) )	-- list the result