Description Details Slots Objects from the Class Extends Note Author(s) References See Also Examples

Log transformation as parameterized in Gating-ML 2.0.

logtGml2 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.

`.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.

Objects can be created by calls to the constructor

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

Class `singleParameterTransform`

, directly.

Class `transform`

, by class singleParameterTransform, distance 2.

Class `transformation`

, by class singleParameterTransform, distance 3.

Class `characterOrTransformation`

, by class singleParameterTransform, distance 4.

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`

Other mathematical transform classes:
`EHtrans-class`

,
`asinht-class`

,
`asinhtGml2-class`

,
`dg1polynomial-class`

,
`exponential-class`

,
`hyperlog-class`

,
`hyperlogtGml2-class`

,
`invsplitscale-class`

,
`lintGml2-class`

,
`logarithm-class`

,
`logicletGml2-class`

,
`quadratic-class`

,
`ratio-class`

,
`ratiotGml2-class`

,
`sinht-class`

,
`splitscale-class`

,
`squareroot-class`

,
`unitytransform-class`

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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