CW2pLM {Luminescence} | R Documentation |
Transform a CW-OSL curve into a pLM-OSL curve
Description
Transforms a conventionally measured continuous-wave (CW) curve into a pseudo linearly modulated (pLM) curve using the equations given in Bulur (2000).
Usage
CW2pLM(values)
Arguments
values |
RLum.Data.Curve or data.frame (required):
|
Details
According to Bulur (2000) the curve data are transformed by introducing two
new parameters P
(stimulation period) and u
(transformed time):
P=2*max(t)
u=\sqrt{(2*t*P)}
The new count values are then calculated by
ctsNEW = cts(u/P)
and the returned data.frame
is produced by: data.frame(u,ctsNEW)
The output of the function can be further used for LM-OSL fitting.
Value
The function returns the same data type as the input data type with the transformed curve values (data.frame or RLum.Data.Curve).
Function version
0.4.1
How to cite
Kreutzer, S., 2024. CW2pLM(): Transform a CW-OSL curve into a pLM-OSL curve. Function version 0.4.1. 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., 2024. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.24. https://CRAN.R-project.org/package=Luminescence
Note
The transformation is recommended for curves recorded with a channel resolution of at least 0.05 s/channel.
Author(s)
Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany) , RLum Developer Team
References
Bulur, E., 2000. A simple transformation for converting CW-OSL curves to LM-OSL curves. Radiation Measurements, 32, 141-145.
Further Reading
Bulur, E., 1996. An Alternative Technique For Optically Stimulated Luminescence (OSL) Experiment. Radiation Measurements, 26, 701-709.
See Also
CW2pHMi, CW2pLMi, CW2pPMi, fit_LMCurve, lm, RLum.Data.Curve
Examples
##read curve from CWOSL.SAR.Data transform curve and plot values
data(ExampleData.BINfileData, envir = environment())
##read id for the 1st OSL curve
id.OSL <- CWOSL.SAR.Data@METADATA[CWOSL.SAR.Data@METADATA[,"LTYPE"] == "OSL","ID"]
##produce x and y (time and count data for the data set)
x<-seq(CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"]/CWOSL.SAR.Data@METADATA[id.OSL[1],"NPOINTS"],
CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"],
by = CWOSL.SAR.Data@METADATA[id.OSL[1],"HIGH"]/CWOSL.SAR.Data@METADATA[id.OSL[1],"NPOINTS"])
y <- unlist(CWOSL.SAR.Data@DATA[id.OSL[1]])
values <- data.frame(x,y)
##transform values
values.transformed <- CW2pLM(values)
##plot
plot(values.transformed)