Log transformation as parameterized in Gating-ML 2.0 is defined by the following function:

*bound(f, boundMin, boundMax) = max(min(f,boundMax),boundMin))*

where

*f(parameter, T, M) = (1/M) * log10(x/T) + 1*

This transformation provides a logarithmic display that maps scale values from the *(0, T]* interval to the
*(-Inf, 1]* interval such that the data value T is mapped to 1 and M decades of data are mapped into the interval.
Also, the limit for x going to 0 is -Inf.

In addition, if a boundary is defined by the boundMin and/or boundMax parameters, then the result of this transformation is restricted to the [boundMin,boundMax] interval. Specifically, should the result of the f function be less than boundMin, then let the result of this transformation be boundMin. Analogically, should the result of the f function be more than boundMax, then let the result of this transformation be boundMax. The boundMin parameter shall not be greater than the boundMax parameter.

Objects can be created by calls to the constructor

`logtGml2(parameter, T, M, transformationId, boundMin, boundMax)`

`.Data`

:Object of class

`function`

~~`T`

:Object of class

`numeric`

-positive constant (top of scale value)`M`

:Object of class

`numeric`

-positive constant (number of decades)`parameters`

:Object of class

`"transformation"`

-flow parameter to be transformed`transformationId`

:Object of class

`"character"`

-unique ID to reference the transformation`boundMin`

:Object of class

`numeric`

-lower bound of the transformation, default -Inf`boundMax`

:Object of class

`numeric`

-upper bound of the transformation, default Inf

Class `singleParameterTransform`

, directly.
Class `transform`

, by class singleParameterTransform, distance 2.
Class `transformation`

, by class singleParameterTransform, distance 3.
Class `characterOrTransformation`

, by class singleParameterTransform, distance 4.

No methods defined with class logtGml2 in the signature.

The log 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)

Spidlen, J.

Gating-ML 2.0: International Society for Advancement of Cytometry (ISAC) standard for representing gating descriptions in flow cytometry. http://flowcyt.sourceforge.net/gating/20141009.pdf

`logTransform`

, `transform-class`

, `transform`

1 2 3 4 5 | ```
myDataIn <- read.FCS(system.file("extdata", "0877408774.B08",
package="flowCore"))
myLogTr1 <- logtGml2(parameters = "FSC-H", T = 1023, M = 4.5,
transformationId="myLogTr1")
transOut <- eval(myLogTr1)(exprs(myDataIn))
``` |

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