RLum.Results or data.frame,
(required): input values containing at least De and De error. To plot
more than one data set in one figure, a list of the individual data
sets must be provided (e.g. list(dataset.1, dataset.2)).
given.dose
numeric (optional): given dose used for the
dose recovery test to normalise data. If only one given dose is provided
this given dose is valid for all input data sets (i.e., values is a
list). Otherwise a given dose for each input data set has to be provided
(e.g., given.dose = c(100,200)). If no given.dose values are
plotted without normalisation (might be useful for preheat plateau tests).
Note: Unit has to be the same as from the input values (e.g., Seconds or
Gray).
error.range
numeric: symmetric error range in percent
will be shown as dashed lines in the plot. Set error.range to 0 to
void plotting of error ranges.
preheat
numeric: optional vector of preheat
temperatures to be used for grouping the De values. If specified, the
temperatures are assigned to the x-axis.
boxplot
logical: optionally plot values, that are
grouped by preheat temperature as boxplots. Only possible when
preheat vector is specified.
mtext
character: additional text below the plot title.
summary
character (optional): adds numerical output to
the plot. Can be one or more out of: "n" (number of samples),
"mean" (mean De value), "mean.weighted" (error-weighted mean),
"median" (median of the De values), "sdrel" (relative standard
deviation in percent), "sdabs" (absolute standard deviation),
"serel" (relative standard error) and "seabs" (absolute
standard error).
summary.pos
numeric or character (with
default): optional position coordinates or keyword (e.g. "topright")
for the statistical summary. Alternatively, the keyword "sub" may be
specified to place the summary below the plot header. However, this latter
option in only possible if mtext is not used.
legend
character vector (optional): legend content to
be added to the plot.
legend.pos
numeric or character (with
default): optional position coordinates or keyword (e.g. "topright")
for the legend to be plotted.
par.local
logical (with default): use local graphical
parameters for plotting, e.g. the plot is shown in one column and one row.
If par.local = FALSE, global parameters are inherited.
na.rm
logical: indicating wether NA values are
removed before plotting from the input data set
...
further arguments and graphical parameters passed to
plot.
Details
Procedure to test the accuracy of a measurement protocol to reliably
determine the dose of a specific sample. Here, the natural signal is erased
and a known laboratory dose administered which is treated as unknown. Then
the De measurement is carried out and the degree of congruence between
administered and recovered dose is a measure of the protocol's accuracy for
this sample. In the plot the normalised De is shown on the y-axis, i.e.
obtained De/Given Dose.
Value
A plot is returned.
Function version
0.1.10 (2016-05-02 09:36:06)
Note
Further data and plot arguments can be added by using the appropiate R
commands.
Author(s)
Sebastian Kreutzer, IRAMAT-CRP2A, Universite Bordeaux Montaigne
(France), Michael Dietze, GFZ Potsdam (Germany)
R Luminescence Package Team
References
Wintle, A.G., Murray, A.S., 2006. A review of quartz optically
stimulated luminescence characteristics and their relevance in
single-aliquot regeneration dating protocols. Radiation Measurements, 41,
369-391.
See Also
plot
Examples
## read example data set and misapply them for this plot type
data(ExampleData.DeValues, envir = environment())
## plot values
plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
given.dose = 2800, mtext = "Example data")
## plot values with legend
plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
given.dose = 2800,
legend = "Test data set")
## create and plot two subsets with randomised values
x.1 <- ExampleData.DeValues$BT998[7:11,]
x.2 <- ExampleData.DeValues$BT998[7:11,] * c(runif(5, 0.9, 1.1), 1)
plot_DRTResults(values = list(x.1, x.2),
given.dose = 2800)
## some more user-defined plot parameters
plot_DRTResults(values = list(x.1, x.2),
given.dose = 2800,
pch = c(2, 5),
col = c("orange", "blue"),
xlim = c(0, 8),
ylim = c(0.85, 1.15),
xlab = "Sample aliquot")
## plot the data with user-defined statistical measures as legend
plot_DRTResults(values = list(x.1, x.2),
given.dose = 2800,
summary = c("n", "mean.weighted", "sd"))
## plot the data with user-defined statistical measures as sub-header
plot_DRTResults(values = list(x.1, x.2),
given.dose = 2800,
summary = c("n", "mean.weighted", "sd"),
summary.pos = "sub")
## plot the data grouped by preheat temperatures
plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
given.dose = 2800,
preheat = c(200, 200, 200, 240, 240))
## read example data set and misapply them for this plot type
data(ExampleData.DeValues, envir = environment())
## plot values
plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
given.dose = 2800, mtext = "Example data")
## plot two data sets grouped by preheat temperatures
plot_DRTResults(values = list(x.1, x.2),
given.dose = 2800,
preheat = c(200, 200, 200, 240, 240))
## plot the data grouped by preheat temperatures as boxplots
plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
given.dose = 2800,
preheat = c(200, 200, 200, 240, 240),
boxplot = TRUE)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(Luminescence)
Welcome to the R package Luminescence version 0.6.0 [Built: 2016-05-30 16:47:30 UTC]
A common luminescence reader customer: 'If anything can go wrong, it will.'
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Luminescence/plot_DRTResults.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot_DRTResults
> ### Title: Visualise dose recovery test results
> ### Aliases: plot_DRTResults
> ### Keywords: dplot
>
> ### ** Examples
>
>
>
> ## read example data set and misapply them for this plot type
> data(ExampleData.DeValues, envir = environment())
>
> ## plot values
> plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
+ given.dose = 2800, mtext = "Example data")
>
> ## plot values with legend
> plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
+ given.dose = 2800,
+ legend = "Test data set")
>
> ## create and plot two subsets with randomised values
> x.1 <- ExampleData.DeValues$BT998[7:11,]
> x.2 <- ExampleData.DeValues$BT998[7:11,] * c(runif(5, 0.9, 1.1), 1)
>
> plot_DRTResults(values = list(x.1, x.2),
+ given.dose = 2800)
>
> ## some more user-defined plot parameters
> plot_DRTResults(values = list(x.1, x.2),
+ given.dose = 2800,
+ pch = c(2, 5),
+ col = c("orange", "blue"),
+ xlim = c(0, 8),
+ ylim = c(0.85, 1.15),
+ xlab = "Sample aliquot")
>
> ## plot the data with user-defined statistical measures as legend
> plot_DRTResults(values = list(x.1, x.2),
+ given.dose = 2800,
+ summary = c("n", "mean.weighted", "sd"))
>
> ## plot the data with user-defined statistical measures as sub-header
> plot_DRTResults(values = list(x.1, x.2),
+ given.dose = 2800,
+ summary = c("n", "mean.weighted", "sd"),
+ summary.pos = "sub")
>
> ## plot the data grouped by preheat temperatures
> plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
+ given.dose = 2800,
+ preheat = c(200, 200, 200, 240, 240))
> ## read example data set and misapply them for this plot type
> data(ExampleData.DeValues, envir = environment())
>
> ## plot values
> plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
+ given.dose = 2800, mtext = "Example data")
> ## plot two data sets grouped by preheat temperatures
> plot_DRTResults(values = list(x.1, x.2),
+ given.dose = 2800,
+ preheat = c(200, 200, 200, 240, 240))
>
> ## plot the data grouped by preheat temperatures as boxplots
> plot_DRTResults(values = ExampleData.DeValues$BT998[7:11,],
+ given.dose = 2800,
+ preheat = c(200, 200, 200, 240, 240),
+ boxplot = TRUE)
>
>
>
>
>
>
> dev.off()
null device
1
>