R/CW2pLMi.R
CW2pLMi.Rd
Transforms a conventionally measured continuous-wave (CW) OSL-curve into a pseudo linearly modulated (pLM) curve under linear modulation conditions using the interpolation procedure described by Bos & Wallinga (2012).
CW2pLMi(values, P)
values | RLum.Data.Curve or data.frame (required):
RLum.Data.Curve or |
---|---|
P | vector (optional): stimulation time in seconds. If no value is given the optimal value is estimated automatically (see details). Greater values of P produce more points in the rising tail of the curve. |
The function returns the same data type as the input data type with the transformed curve values.
RLum.Data.Curve
$CW2pLMi.x.t | : transformed time values |
$CW2pLMi.method | : used method for the production of the new data points |
The complete procedure of the transformation is given in Bos & Wallinga
(2012). The input data.frame
consists of two columns: time (t) and
count values (CW(t))
Nomenclature
P = stimulation time (s)
1/P = stimulation rate (1/s)
Internal transformation steps
(1) log(CW-OSL) values
(2) Calculate t' which is the transformed time: $$t' = 1/2*1/P*t^2$$
(3)
Interpolate CW(t'), i.e. use the log(CW(t)) to obtain the count values
for the transformed time (t'). Values beyond min(t)
and max(t)
produce NA
values.
(4)
Select all values for t' < min(t)
, i.e. values beyond the time resolution
of t. Select the first two values of the transformed data set which contain
no NA
values and use these values for a linear fit using lm.
(5)
Extrapolate values for t' < min(t)
based on the previously obtained
fit parameters.
(6) Transform values using $$pLM(t) = t/P*CW(t')$$
(7)
Combine values and truncate all values for t' > max(t)
NOTE:
The number of values for t' < min(t)
depends on the stimulation
period (P) and therefore on the stimulation rate 1/P. To avoid the
production of too many artificial data at the raising tail of the determined
pLM curves it is recommended to use the automatic estimation routine for
P
, i.e. provide no own value for P
.
According to Bos & Wallinga (2012) the number of extrapolated points
should be limited to avoid artificial intensity data. If P
is
provided manually and more than two points are extrapolated, a warning
message is returned.
0.3.1
Kreutzer, S., 2021. CW2pLMi(): Transform a CW-OSL curve into a pLM-OSL curve via interpolation under linear modulation conditions. Function version 0.3.1. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., 2021. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.11. https://CRAN.R-project.org/package=Luminescence
Bos, A.J.J. & Wallinga, J., 2012. How to visualize quartz OSL signal components. Radiation Measurements, 47, 752-758.
Further Reading
Bulur, E., 1996. An Alternative Technique For Optically Stimulated Luminescence (OSL) Experiment. Radiation Measurements, 26, 701-709.
Bulur, E., 2000. A simple transformation for converting CW-OSL curves to LM-OSL curves. Radiation Measurements, 32, 141-145.
Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)
Based on comments and suggestions from:
Adrie J.J. Bos, Delft University of Technology, The Netherlands
, RLum Developer Team
##(1) ##load CW-OSL curve data data(ExampleData.CW_OSL_Curve, envir = environment()) ##transform values values.transformed <- CW2pLMi(ExampleData.CW_OSL_Curve) ##plot plot(values.transformed$x, values.transformed$y.t, log = "x")##(2) - produce Fig. 4 from Bos & Wallinga (2012) ##load data data(ExampleData.CW_OSL_Curve, envir = environment()) values <- CW_Curve.BosWallinga2012 ##open plot area plot(NA, NA, xlim = c(0.001,10), ylim = c(0,8000), ylab = "pseudo OSL (cts/0.01 s)", xlab = "t [s]", log = "x", main = "Fig. 4 - Bos & Wallinga (2012)")values.t <- CW2pLMi(values, P = 1/20) lines(values[1:length(values.t[,1]),1],CW2pLMi(values, P = 1/20)[,2], col = "red", lwd = 1.3)#> Warning: 56 values have been found and replaced the mean of the nearest values.#> Warning: 56 values have been found and replaced the mean of the nearest values.#> Warning: t' is beyond the time resolution. Only two data points have been extrapolated, the first 3 points have been set to 0!#> Warning: t' is beyond the time resolution. Only two data points have been extrapolated, the first 3 points have been set to 0!