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

Linear transformation as parameterized in Gating-ML 2.0.

lintGml2 is defined by the following function:

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

where

*f(parameter, T, A) = (parameter + A) / (T + A)*

This transformation provides a linear display that maps scale values from
the *[-A, T]* interval to the *[0, 1]* interval. However, it is
defined for all *x in R* including outside of the *[-A, T]*
interval.

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).`A`

Object of class

`numeric`

– non-negative constant that is less than or equal to T; it is determining the bottom end of the transformation.`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

`lintGml2(parameter, T, A, 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 linear 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

`linearTransform`

, `transform-class`

,
`transform`

Other mathematical transform classes:
`EHtrans-class`

,
`asinht-class`

,
`asinhtGml2-class`

,
`dg1polynomial-class`

,
`exponential-class`

,
`hyperlog-class`

,
`hyperlogtGml2-class`

,
`invsplitscale-class`

,
`logarithm-class`

,
`logicletGml2-class`

,
`logtGml2-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"))
myLinTr1 <- lintGml2(parameters = "FSC-H", T = 1000, A = 0,
transformationId="myLinTr1")
transOut <- eval(myLinTr1)(exprs(myDataIn))
``` |

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