Skip to contents

Fit and plot a dose-response curve for luminescence data (Lx/Tx against dose)

Source: R/plot_GrowthCurve.R
plot_GrowthCurve.Rd

A dose-response curve is produced for luminescence measurements using a regenerative or additive protocol as implemented in fit_DoseResponseCurve and plot_DoseResponseCurve

Usage

plot_GrowthCurve(
  sample,
  mode = "interpolation",
  fit.method = "EXP",
  output.plot = TRUE,
  output.plotExtended = TRUE,
  plot_singlePanels = FALSE,
  cex.global = 1,
  verbose = TRUE,
  n.MC = 100,
  ...
)

Arguments

sample

data.frame (required): data frame with columns for Dose, LxTx, LxTx.Error and TnTx. The column for the test dose response is optional, but requires 'TnTx' as column name if used. For exponential fits at least three dose points (including the natural) should be provided.

mode

character (with default): selects calculation mode of the function.

  • "interpolation" (default) calculates the De by interpolation,

  • "extrapolation" calculates the equivalent dose by extrapolation (useful for MAAD measurements) and

  • "alternate" calculates no equivalent dose and just fits the data points.

Please note that for option "interpolation" the first point is considered as natural dose

fit.method

character (with default): function used for fitting. Possible options are:

  • LIN,

  • QDR,

  • EXP,

  • EXP OR LIN,

  • EXP+LIN,

  • EXP+EXP,

  • GOK,

  • LambertW

See details in fit_DoseResponseCurve.

output.plot

logical (with default): enable/disable the plot output.

output.plotExtended

logical (with default): If' TRUE, 3 plots on one plot area are provided:

  1. growth curve,

  2. histogram from Monte Carlo error simulation and

  3. a test dose response plot.

If FALSE, just the growth curve will be plotted.

plot_singlePanels

logical (with default): single plot output (TRUE/FALSE) to allow for plotting the results in single plot windows. Requires plotExtended = TRUE.

cex.global

numeric (with default): global scaling factor.

verbose

logical (with default): enable/disable output to the terminal.

n.MC

integer (with default): number of MC runs for error calculation.

...

Further arguments to fit_DoseResponseCurve (fit_weights, fit_bounds, fit.force_through_origin, fit.includingRepeatedRegPoints, fit.NumberRegPoints, fit.NumberRegPointsReal, n.MC, txtProgressBar) and graphical parameters to be passed (supported: xlim, ylim, main, xlab, ylab).

Value

Along with a plot (if wanted) the RLum.Results object produced by fit_DoseResponseCurve is returned.

Function version

1.2.1

How to cite

Kreutzer, S., Dietze, M., Colombo, M., 2025. plot_GrowthCurve(): Fit and plot a dose-response curve for luminescence data (Lx/Tx against dose). Function version 1.2.1. 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., Colombo, M., Steinbuch, L., Boer, A.d., 2025. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 1.0.1. https://r-lum.github.io/Luminescence/

References

Berger, G.W., Huntley, D.J., 1989. Test data for exponential fits. Ancient TL 7, 43-46.

Guralnik, B., Li, B., Jain, M., Chen, R., Paris, R.B., Murray, A.S., Li, S.-H., Pagonis, P., Herman, F., 2015. Radiation-induced growth and isothermal decay of infrared-stimulated luminescence from feldspar. Radiation Measurements 81, 224-231.

Pagonis, V., Kitis, G., Chen, R., 2020. A new analytical equation for the dose response of dosimetric materials, based on the Lambert W function. Journal of Luminescence 225, 117333. doi:10.1016/j.jlumin.2020.117333

See also

fit_DoseResponseCurve, plot_DoseResponseCurve

Author

Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany)
Michael Dietze, GFZ Potsdam (Germany)
Marco Colombo, Institute of Geography, Heidelberg University (Germany) , RLum Developer Team

Examples


##(1) plot growth curve for a dummy dataset
data(ExampleData.LxTxData, envir = environment())
plot_GrowthCurve(LxTxData)
#> [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07


##(1b) horizontal plot arrangement
layout(mat = matrix(c(1,1,2,3), ncol = 2))
plot_GrowthCurve(LxTxData, plot_singlePanels = TRUE)
#> [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07


##(2) plot the growth curve with pdf output - uncomment to use
##pdf(file = "~/Desktop/Growth_Curve_Dummy.pdf", paper = "special")
plot_GrowthCurve(LxTxData)
#> [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07

##dev.off()

##(3) plot the growth curve with pdf output - uncomment to use, single output
##pdf(file = "~/Desktop/Growth_Curve_Dummy.pdf", paper = "special")
temp <- plot_GrowthCurve(LxTxData, plot_singlePanels = TRUE)
#> [fit_DoseResponseCurve()] Fit: EXP (interpolation) | De = 1737.88 | D01 = 1766.07
##dev.off()

##(4) plot resulting function for given interval x
x <- seq(1,10000, by = 100)
plot(
 x = x,
 y = eval(temp$Formula),
 type = "l"
)


##(5) plot using the 'extrapolation' mode
LxTxData[1,2:3] <- c(0.5, 0.001)
print(plot_GrowthCurve(LxTxData, mode = "extrapolation"))
#> [fit_DoseResponseCurve()] Fit: EXP (extrapolation) | De = 109.74 | D01 = 2624.06

#> 
#>  [RLum.Results-class]
#> 	 originator: fit_DoseResponseCurve()
#> 	 data: 5
#>  	 .. $De : data.frame
#> 	 .. $De.MC : numeric
#> 	 .. $Fit : nls
#> 	 .. $Fit.Args : list
#> 	 .. $Formula : expression
#> 	 additional info elements:  1 

##(6) plot using the 'alternate' mode
LxTxData[1,2:3] <- c(0.5, 0.001)
print(plot_GrowthCurve(LxTxData, mode = "alternate"))

#> 
#>  [RLum.Results-class]
#> 	 originator: fit_DoseResponseCurve()
#> 	 data: 5
#>  	 .. $De : data.frame
#> 	 .. $De.MC : logical
#> 	 .. $Fit : nls
#> 	 .. $Fit.Args : list
#> 	 .. $Formula : expression
#> 	 additional info elements:  1