BayLum (version 0.3.2)

plot_Scatterplots: Display Scatter Plot Matrix of the Bayesian Age Results

Description

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

Usage

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

Value

A scatter plot based on hexbin::hexplom

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.

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 , RLum Developer Team

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

See Also

Age_Computation, AgeS_Computation, AgeC14_Computation, and rjags packages.

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")