logarithm-class: Class "logarithm"

In RGLab/flowCore: flowCore: Basic structures for flow cytometry data

Class "logarithm"

Description

Logartithmic transform class, which represents a transformation defined by the function

Details

f(parameter,a,b)= ln(a*prarameter)*b ~~~~a*parameter>0

0 ~~~~a*parameter<=0

Slots

.Data

Object of class "function"

a

Object of class "numeric" – non-zero multiplicative constant.

b

Object of class "numeric" – non-zero multiplicative constant.

parameters

Object of class "transformation" – flow parameters to be transformed.

transformationId

Object of class "character" – unique ID to reference the transformation.

Objects from the Class

Objects can be created by calls to the constructor logarithm(parameters,a,b,transformationId)

Extends

Class "singleParameterTransform", directly.

Class "transform", by class "singleParameterTransform", distance 2.

Class "transformation", by class "singleParameterTransform", distance 3.

Class "characterOrTransformation", by class "singleParameterTransform", distance 4.

Note

The logarithm transformation object can be evaluated using the eval method by passing the data frame as an argument.The transformed parameters are returned as a matrix with a single column. (See example below)

Author(s)

Gopalakrishnan N, F.Hahne

References

Gating-ML Candidate Recommendation for Gating Description in Flow Cytometry V 1.5

See Also

exponential, quadratic

Other mathematical transform classes: EHtrans-class, asinht-class, asinhtGml2-class, dg1polynomial-class, exponential-class, hyperlog-class, hyperlogtGml2-class, invsplitscale-class, lintGml2-class, logicletGml2-class, logtGml2-class, quadratic-class, ratio-class, ratiotGml2-class, sinht-class, splitscale-class, squareroot-class, unitytransform-class

Examples

 dat <- read.FCS(system.file("extdata","0877408774.B08",
  package="flowCore"))
  lg1<-logarithm(parameters="FSC-H",a=2,b=1,transformationId="lg1")
  transOut<-eval(lg1)(exprs(dat))

RGLab/flowCore documentation built on Aug. 26, 2024, 8:52 a.m.