Normalisation of RLum-class objects

The function provides a generalised access point for specific RLum objects. Depending on the input object, the corresponding function will be selected. The normalisation is performed in the internal function .normalise_curve().

Usage

normalise_RLum(object, norm = TRUE, ...)

# S4 method for class 'list'
normalise_RLum(object, norm = TRUE, ...)

# S4 method for class 'RLum.Analysis'
normalise_RLum(object, norm = TRUE, ...)

# S4 method for class 'RLum.Data.Curve'
normalise_RLum(object, norm)

# S4 method for class 'RLum.Data.Image'
normalise_RLum(object, norm = TRUE, global = TRUE)

# S4 method for class 'RLum.Data.Spectrum'
normalise_RLum(object, norm = TRUE)

Arguments

object

RLum (required): S4 object of class RLum

norm

logical character (required): if logical, whether curve normalisation should occur; alternatively, one of "max" (used with TRUE), "min", "first", "last", "huot", "intensity" or a positive number (e.g., 2.2).

...

further arguments passed to the specific class method

global

logical (*with default): this defines whether the normalisation is applied globally (same to all) or locally, in which case each frame has its own normalisation. If global = TRUE the arguments for norm = 'first' and norm = 'last' work as expected and consider either the first or the last frame for the normalisation.

Normalise RLum.Data.Image objects to value set via the argument norm

Value

An object of the same type as the input object provided.

Details

The norm argument normalises all count values. The following options are supported:

norm = TRUE or norm = "max": Curve values are normalised to the highest count value in the curve

norm = "min": Curve values are normalised to the smallest count value in the curve

norm = "first": Curve values are normalised to the first count value.

norm = "last": Curve values are normalised to the last count value (this can be useful in particular for radiofluorescence curves)

norm = "huot": Curve values are normalised as suggested by Sébastien Huot via GitHub: $$ y = (observed - median(background)) / (max(observed) - median(background)) $$

The background of the curve is defined as the last 20% of the count values of a curve.

norm = "intensity": Curve values are normalised to the channel length.

norm = 2.2: Curve values are normalised to a positive number (e.g., 2.2).

Functions

• normalise_RLum(list): Returns a list of RLum.Data objects that had been passed to normalise_RLum

• normalise_RLum(RLum.Analysis): Normalisation of RLum.Data records contained in the input object.

• normalise_RLum(RLum.Data.Curve): Normalise RLum.Data.Curve objects to value set via the argument norm

• normalise_RLum(RLum.Data.Image): Normalise RLum.Data.Image objects to value set via the argument norm.

• normalise_RLum(RLum.Data.Spectrum): Normalise RLum.Data.Spectrum objects to value set via the argument norm

Function version

0.1.2

See also

RLum.Data.Curve, RLum.Analysis, RLum.Data.Spectrum, RLum.Data.Image

Author

Sebastian Kreutzer, F2.1 Geophysical Parametrisation/Regionalisation, LIAG - Institute for Applied Geophysics (Germany) , RLum Developer Team

How to cite

Kreutzer, S., 2026. normalise_RLum(): Normalisation of RLum-class objects. Function version 0.1.2. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Philippe, A., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., Galharret, J., Colombo, M., Steinbuch, L., Boer, A.d., Bluszcz, A., 2026. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 1.2.0. https://r-lum.github.io/Luminescence/

Examples

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

## create RLum.Data.Curve object from this example
curve <-
  set_RLum(
      class = "RLum.Data.Curve",
      recordType = "OSL",
      data = as.matrix(ExampleData.CW_OSL_Curve)
  )

## plot data without and with smoothing
plot_RLum(curve)

plot_RLum(normalise_RLum(curve))