Luminescence (version 0.3.1)

plot_RadialPlot: Function to create a Radial Plot

Description

A Galbraith's radial plot is produced on a logarithmic or a linear scale.

Usage

plot_RadialPlot(data, na.exclude = TRUE, log.z = TRUE, central.value, 
    plot.ratio, bar.col, grid.col, legend.text, stats, summary = FALSE, 
    output = FALSE, ...)

Arguments

data

data.frame or RLum.Results object (required): for data.frame two columns: De (data[,1]) and De error (data[,2]). To plot

na.exclude

logical (with default): excludes NA values from the data set prior to any further operations.

log.z

logical (with default): Option to display the z-axis in logarithmic scale. Default is TRUE.

central.value

numeric: User-defined central value, primarily used for horizontal centering of the z-axis.

plot.ratio

numeric: User-defined plot area ratio (i.e. curvature of the z-axis). If omitted, the default value (4.5/5.5) is used and modified automatically to optimise the z-axis curvature. The parame

bar.col

character or numeric (with default): colour of the bar showing the 2-sigma range around the central value. To disable the bar, use "none".

grid.col

character or numeric (with default): colour of the grid lines (originating at [0,0] and stretching to the z-scale). To disable grid lines, use "

legend.text

character: optional vector with legend item names (e.g. sample ID). Legend will only be plotted if legend text is provided.

stats

character: additional labels of statistically important values in the plot. One or more out of the following: "min", "max", "median".

summary

logical (with default): Shows statistical summary of sample or sample groups below plot main header, default is FALSE.

output

logical: Optional output of numerical plot parameters. These can be useful to reproduce similar plots. Default is FALSE.

...

Further plot arguments to pass. xlab must be a vector of length 2, specifying the upper and lower x-axes labels.

Value

• Returns a plot object.

Details

Details and the theoretical background of the radial plot are given in the cited literature. This function is based on an S script of Rex Galbraith. To reduce the manual adjustments, the function has been rewritten. Thanks to Rex Galbraith for useful comments on this function. Plotting can be disabled by adding the argument plot = "FALSE", e.g. to return only numeric plot output.

References

Galbraith, R.F., 1988. Graphical Display of Estimates Having Differing Standard Errors. Technometrics, 30 (3), pp. 271-281. Galbraith, R.F., 1990. The radial plot: Graphical assessment of spread in ages. International Journal of Radiation Applications and Instrumentation. Part D. Nuclear Tracks and Radiation Measurements, 17, 3, 207-214. Galbraith, R. & Green, P., 1990. Estimating the component ages in a finite mixture. International Journal of Radiation Applications and Instrumentation. Part D. Nuclear Tracks and Radiation Measurements, 17, 3 197-206. Galbraith, R.F. & Laslett, G.M., 1993. Statistical models for mixed fission track ages. Nuclear Tracks And Radiation Measurements, 21, 4, 459-470. Galbraith, R.F., 1994. Some Applications of Radial Plots. Journal of the American Statistical Association, 89 (428), pp. 1232-1242. Galbraith, R.F., 2010. On plotting OSL equivalent doses. Ancient TL, 28 (1), 1-10. Galbraith, R.F. & Roberts, R.G., 2012. Statistical aspects of equivalent dose and error calculation and display in OSL dating: An overview and some recommendations. Quaternary Geochronology, 11, 1-27.

See Also

plot, plot_KDE, plot_Histogram

Examples

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

## plot the example data straightforward
plot_RadialPlot(data = ExampleData.DeValues)

## now with linear z-scale
plot_RadialPlot(data = ExampleData.DeValues,
                log.z = FALSE)

## now with output of the plot parameters
plot1 <- plot_RadialPlot(data = ExampleData.DeValues,
                         log.z = FALSE,
                         output = TRUE)
plot1
plot1$zlim

## now with adjusted z-scale limits
plot_RadialPlot(data = ExampleData.DeValues,
               log.z = FALSE,
               zlim = c(2000, 4000))

## now the two plots with serious but seasonally changing fun
#plot_RadialPlot(data = data.3, fun = TRUE)

## now with user-defined central value, in log-scale again
plot_RadialPlot(data = ExampleData.DeValues,
                central.value = 3500)

## now with legend, colour, different points and smaller scale
plot_RadialPlot(data = ExampleData.DeValues,
                legend.text = "Sample 1",
                col = "tomato4",
                bar.col = "peachpuff",
                pch = "R",
                cex = 0.8)

## now without 2-sigma bar, grid lines and central value line
plot_RadialPlot(data = ExampleData.DeValues,
                bar.col = "none",
                grid.col = "none",
                lwd = 0)

## now with user-defined axes labels
plot_RadialPlot(data = ExampleData.DeValues,
                xlab = c("Data error [%]",
                         "Data precision"),
                ylab = "Scatter",
                zlab = "Equivalent dose [Gy]")

## now with minimum, maximum and median value indicated
plot_RadialPlot(data = ExampleData.DeValues,
                central.value = 3500,
                stats = c("min", "max", "median"))

## now with a brief statistical summary header
plot_RadialPlot(data = ExampleData.DeValues,
                summary = TRUE)

## now the data set is split into sub-groups, one is manipulated
data.1 <- ExampleData.DeValues[1:15,]
data.2 <- ExampleData.DeValues[16:25,] * 1.3

## now a common dataset is created from the two subgroups
data.3 <- list(data.1, data.2)

## now the two data sets are plotted in one plot
plot_RadialPlot(data = data.3)

## now with some graphical modification
plot_RadialPlot(data = data.3,
                col = c("darkblue", "darkgreen"),
                bar.col = c("lightblue", "lightgreen"),
                pch = c(2, 6),
                summary = TRUE)