Display Scatter Plot Matrix of the Bayesian Age Results

Create a hexbin plot matrix (hexbin::hexplom) of age results returned by the Bayesian age calculation.

plot_Scatterplots(
  object,
  variables = c("A"),
  sample_names = NULL,
  sample_selection = NULL,
  n.chains = NULL,
  plot_type = "hexbin",
  plot_mode = "matrix",
  ...
)

ScatterSamples(...)

Arguments

object: coda::mcmc.list or a data.frame (required): mcmc list objects generated by rjags::jags.model in AgeS_Computation, AgeC14_Computation or Age_OSLC14. If a data.frame is provided, only the first two columns are taken and NA values are automatically removed. The function can also handle BayLum.list objects directly for certain functions
variables: character (with default): variable to be selected for the scatter plot, e.g., "A". Please note that you can only select one variable at the time
sample_names: character (optional): sample names shown in the plot matrix
sample_selection: numeric (with default): vector of samples to be plotted in the scatter matrix, e.g., c(1,2) will plot the first two samples, c(1,3) will plot samples 1 and 3 and c(1:3) will plot the first three samples
n.chains: integer (with default): allows to limit the number of chains shown, by default the results of all chains are plotted.
plot_type: character (with default): switch between different plot types, "hexbin" (the default), based on the function hexbin::hexplom and smoothScatter (the alternative) based on a highly customised plot function using the function graphics::smoothScatter
plot_mode: character (with default): switch between a matrix plot mode and a single plot mode. The plot mode single only works for plot_type = smoothScatter and creates a single plot panel for each sample. Please note that this cannot be further combined with other par settings.
...: further arguments to control the plot output, standard plot arguments supported are main, xlab, ylab, xlim, ylim, cex. For additional arguments supporting a fine tuning of the plot, see details.

Value

A scatter plot based on hexbin::hexplom

Details

Additional supported plot arguments

The following table lists additional arguments supported by the function in order to fine tune the graphical output. Such arguments, can just be added in the function call. Example, for disabling the graphics::rug in the plot mode smoothScatter you can type plot_Scatterplots(..., rug = FALSE) Please note that not all arguments are supported by all plot types.

ARGUMENT	SUPPORTED BY PLOT TYPE	DESCRIPTION
`colramp`	`hexbin` and `smoothScatter`	Option to define an own colour ramp, by defining an own function, e.g., `function(n) heat.colors(n, alpha = 1)`.
`pscales`	`hexbin` and `smoothScatter`	Controls the number of ticks shown on the plot axes, please note that the number works proportionally.
`bw_smoothScatter`	`smoothScatter`	Controls the bandwidth of the smooth scatter, cf. graphics::smoothScatter
`rug`	`smoothScatter`	enables/disables rugs
`nlevels`	`smoothScatter`	controls the number of isolines shown (cf. graphics::contour)
`nrpoints`	`smoothScatter`	defines the number of `nrpoints` to be plotted graphics::smoothScatter
`col_contour`	`smoothScatter`	defines the colour of the contour lines
`col_nrpoints`	`smoothScatter`	sets colour of the `nrpoints` in the scatter plot

Function version

0.3.2

Author

Sebastian Kreutzer, Institute of Geography, Ruprecht-Karl University of Heidelberg (Germany) , based on the function 'ScatterSamples()' by Claire Christophe, Anne Philippe, Guillaume Guérin

How to cite

Kreutzer, S., Christophe, C., Philippe, A., Guérin, G., 2024. plot_Scatterplots(): Display Scatter Plot Matrix of the Bayesian Age Results. Function version 0.3.2. In: Christophe, C., Philippe, A., Kreutzer, S., Guérin, G., Baumgarten, F.H., Frerebeau, N., 2024. BayLum: Chronological Bayesian Models Integrating Optically Stimulated. R package version 0.3.2. https://CRAN.r-project.org/package=BayLum

Examples

data(AgeS,envir = environment())

##hexbin
plot_Scatterplots(
   object = AgeS$Sampling,
   sample_names = c("GDB5", "GDB3"),
   sample_selection = c(1,2)
 )


##scatter smooth (matrix)
plot_Scatterplots(
   object = AgeS$Sampling,
   sample_names = c("GDB5", "GDB3"),
   sample_selection = c(1,2),
   plot_type = "smoothScatter")



##scatter smooth (single)
plot_Scatterplots(
   object = AgeS$Sampling,
   sample_names = c("GDB5", "GDB3"),
   sample_selection = c(1,2),
   plot_type = "smoothScatter",
   plot_mode = "single")