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methods_RLum

Source: R/methods_RLum.R
methods_RLum.Rd

Methods for S3-generics implemented for the package 'Luminescence'. This document summarises all implemented S3-generics. The name of the function is given before the first dot, after the dot the name of the object that is supported by this method is given, e.g. plot.RLum.Data.Curve can be called by plot(object, ...), where object is the RLum.Data.Curve object.

Usage

# S3 method for class 'list'
plot(x, y, ...)

# S3 method for class 'RLum.Results'
plot(x, y, ...)

# S3 method for class 'RLum.Analysis'
plot(x, y, ...)

# S3 method for class 'RLum.Data.Curve'
plot(x, y, ...)

# S3 method for class 'RLum.Data.Spectrum'
plot(x, y, ...)

# S3 method for class 'RLum.Data.Image'
plot(x, y, ...)

# S3 method for class 'Risoe.BINfileData'
plot(x, y, ...)

# S3 method for class 'RLum.Results'
hist(x, ...)

# S3 method for class 'RLum.Data.Image'
hist(x, ...)

# S3 method for class 'RLum.Data.Curve'
hist(x, ...)

# S3 method for class 'RLum.Analysis'
hist(x, ...)

# S3 method for class 'RLum.Results'
summary(object, ...)

# S3 method for class 'RLum.Analysis'
summary(object, ...)

# S3 method for class 'RLum.Data.Image'
summary(object, ...)

# S3 method for class 'RLum.Data.Curve'
summary(object, ...)

# S3 method for class 'Risoe.BINfileData'
subset(x, subset, records.rm = TRUE, ...)

# S3 method for class 'RLum.Analysis'
subset(x, subset = NULL, ...)

bin(x, ...)

# S3 method for class 'RLum.Data.Curve'
bin(x, bin_size = 2, ...)

# S3 method for class 'RLum.Data.Spectrum'
bin(x, bin_size.row = 1, bin_size.col = 1, ...)

# S3 method for class 'RLum.Results'
length(x, ...)

# S3 method for class 'RLum.Analysis'
length(x, ...)

# S3 method for class 'RLum.Data.Curve'
length(x, ...)

# S3 method for class 'Risoe.BINfileData'
length(x, ...)

# S3 method for class 'RLum.Data.Curve'
dim(x)

# S3 method for class 'RLum.Data.Spectrum'
dim(x)

# S3 method for class 'RLum'
rep(x, ...)

# S3 method for class 'RLum.Data.Curve'
names(x, ...)

# S3 method for class 'RLum.Data.Spectrum'
names(x, ...)

# S3 method for class 'RLum.Data.Image'
names(x, ...)

# S3 method for class 'RLum.Analysis'
names(x, ...)

# S3 method for class 'RLum.Results'
names(x, ...)

# S3 method for class 'Risoe.BINfileData'
names(x)

# S3 method for class 'RLum.Data.Spectrum'
row.names(x, ...)

# S3 method for class 'RLum.Data.Curve'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for class 'RLum.Data.Spectrum'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for class 'Risoe.BINfileData'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for class 'RLum.Results'
as.list(x, ...)

# S3 method for class 'RLum.Data.Curve'
as.list(x, ...)

# S3 method for class 'RLum.Data.Image'
as.list(x, ...)

# S3 method for class 'RLum.Analysis'
as.list(x, ...)

# S3 method for class 'RLum.Data.Curve'
as.matrix(x, ...)

# S3 method for class 'RLum.Data.Spectrum'
as.matrix(x, ...)

# S3 method for class 'RLum.Data.Image'
as.matrix(x, ...)

is.RLum(x, ...)

is.RLum.Data(x, ...)

is.RLum.Data.Curve(x, ...)

is.RLum.Data.Spectrum(x, ...)

is.RLum.Data.Image(x, ...)

is.RLum.Analysis(x, ...)

is.RLum.Results(x, ...)

# S3 method for class 'RLum'
merge(x, y, ...)

# S3 method for class 'RLum.Analysis'
unlist(x, recursive = TRUE, ...)

# S3 method for class 'RLum.Data.Curve'
x + y

# S3 method for class 'RLum.Data.Curve'
x - y

# S3 method for class 'RLum.Data.Curve'
x * y

# S3 method for class 'RLum.Data.Curve'
x/y

# S3 method for class 'RLum.Data.Curve'
x[y, z, drop = TRUE]

# S3 method for class 'RLum.Data.Spectrum'
x[y, z, drop = TRUE]

# S3 method for class 'RLum.Data.Image'
x[y, z, drop = TRUE]

# S3 method for class 'RLum.Analysis'
x[i, drop = FALSE]

# S3 method for class 'RLum.Results'
x[i, drop = TRUE]

# S3 method for class 'RLum.Data.Curve'
x[i, j] <- value

# S3 method for class 'RLum.Analysis'
x[[i]]

# S3 method for class 'RLum.Results'
x[[i]]

# S3 method for class 'RLum.Data.Curve'
x$i

# S3 method for class 'RLum.Analysis'
x$i

# S3 method for class 'RLum.Results'
x$i

Arguments

x

RLum or Risoe.BINfileData (required): input object

y

integer (optional): the row index of the matrix, data.frame

...

further arguments that can be passed to the method

object

RLum (required): input object

subset

[subset] expression (required): logical expression indicating elements or rows to keep, this function works in Risoe.BINfileData objects like subset.data.frame, but takes care of the object structure. Works also on RLum.Analysis objects.

records.rm

subset logical (with default): remove records from data set, can be disabled, to just set the column SET to TRUE or FALSE

row.names

logical (with default): enables or disables row names (as.data.frame)

optional

logical (with default): logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional (see base::as.data.frame)

recursive

logical (with default): enables or disables further sub-setting (unlist)

z

integer (optional): the column index of the matrix, data.frame

drop

logical (with default): keep object structure or drop it

i

character (optional): name of the wanted record type or data object or row in the RLum.Data.Curve object

j

integer (optional): column of the data matrix in the RLum.Data.Curve object

value

numeric (required): numeric value which replace the value in the RLum.Data.Curve object

Details

The term S3-generics sounds complicated, however, it just means that something has been implemented in the package to increase the usability for users new in R and who are not familiar with the underlying RLum-object structure of the package. The practical outcome is that operations and functions presented in standard books on R can be used without knowing the specifics of the R package 'Luminescence'. For examples see the example section.

Note

methods_RLum are not really new functions, everything given here are mostly just surrogates for existing functions in the package.

Examples


##load example data
data(ExampleData.RLum.Analysis, envir = environment())


##combine curve is various ways
curve1 <- IRSAR.RF.Data[[1]]
curve2 <-  IRSAR.RF.Data[[1]]
curve1 + curve2
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: merged
#> 	 measured values: 5
#> 	 .. range of x-values: 0.1747448 6.311132
#> 	 .. range of y-values: 2846.3 2875.6 
#> 	 additional info elements: 0 
curve1 - curve2
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: merged
#> 	 measured values: 5
#> 	 .. range of x-values: 0.1747448 6.311132
#> 	 .. range of y-values: 0 0 
#> 	 additional info elements: 0 
curve1 / curve2
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: merged
#> 	 measured values: 5
#> 	 .. range of x-values: 0.1747448 6.311132
#> 	 .. range of y-values: 1 1 
#> 	 additional info elements: 0 
curve1 * curve2
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: merged
#> 	 measured values: 5
#> 	 .. range of x-values: 0.1747448 6.311132
#> 	 .. range of y-values: 2025356 2067269 
#> 	 additional info elements: 0 


##`$` access curves
IRSAR.RF.Data$RF
#> [[1]]
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: NA
#> 	 measured values: 5
#> 	 .. range of x-values: 0.1747448 6.311132
#> 	 .. range of y-values: 1423.15 1437.8 
#> 	 additional info elements: 0 
#> 
#> [[2]]
#> 
#>  [RLum.Data.Curve-class]
#> 	 recordType: RF
#> 	 curveType: NA
#> 	 measured values: 524
#> 	 .. range of x-values: 0.3768403 715.4821
#> 	 .. range of y-values: 1379.947 2103.4 
#> 	 additional info elements: 0 
#>