Running examples in 'Luminescence-Ex.R' failed
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> ### Name: plot_AbanicoPlot
> ### Title: Function to create an Abanico Plot.
> ### Aliases: plot_AbanicoPlot
> 
> ### ** Examples
> 
> 
> ## load example data and recalculate to Gray
> data(ExampleData.DeValues, envir = environment())
> ExampleData.DeValues <- ExampleData.DeValues$CA1
> 
> ## plot the example data straightforward
> plot_AbanicoPlot(data = ExampleData.DeValues)
> 
> ## now with linear z-scale
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  log.z = FALSE)
> 
> ## now with output of the plot parameters
> plot1 <- plot_AbanicoPlot(data = ExampleData.DeValues,
+                           output = TRUE)
> str(plot1)
List of 10
 $ xlim         : num [1:2] 0 16.1
 $ ylim         : num [1:2] -36.8 15.9
 $ zlim         : num [1:2] 17.4 132.9
 $ polar.box    : num [1:4] 0 16.1 -20.5 12.2
 $ cartesian.box: num [1:4] 16.6 20.4 -20.5 12.2
 $ plot.ratio   : num 0.788
 $ data         :List of 1
  ..$ :'data.frame':	62 obs. of  10 variables:
  .. ..$ De               : num [1:62] 19.7 26.2 31.5 31.9 36.2 ...
  .. ..$ error            : num [1:62] 2.14 2.04 2.34 2.34 2.95 3.15 8.22 3.23 4.43 4.43 ...
  .. ..$ z                : num [1:62] 2.98 3.27 3.45 3.46 3.59 ...
  .. ..$ se               : num [1:62] 0.1086 0.0779 0.0743 0.0732 0.0816 ...
  .. ..$ z.central        : num [1:62] 4.13 4.13 4.13 4.13 4.13 ...
  .. ..$ precision        : num [1:62] 9.21 12.84 13.45 13.65 12.26 ...
  .. ..$ std.estimate     : num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ...
  .. ..$ std.estimate.plot: num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ...
  .. ..$ weights          : num [1:62] 0.0161 0.0161 0.0161 0.0161 0.0161 ...
  .. ..$ data.in.2s       : logi [1:62] FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ data.global  :'data.frame':	62 obs. of  10 variables:
  ..$ De               : num [1:62] 19.7 26.2 31.5 31.9 36.2 ...
  ..$ error            : num [1:62] 2.14 2.04 2.34 2.34 2.95 3.15 8.22 3.23 4.43 4.43 ...
  ..$ z                : num [1:62] 2.98 3.27 3.45 3.46 3.59 ...
  ..$ se               : num [1:62] 0.1086 0.0779 0.0743 0.0732 0.0816 ...
  ..$ z.central        : num [1:62] 4.13 4.13 4.13 4.13 4.13 ...
  ..$ precision        : num [1:62] 9.21 12.84 13.45 13.65 12.26 ...
  ..$ std.estimate     : num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ...
  ..$ std.estimate.plot: num [1:62] -10.58 -11.1 -9.15 -9.09 -6.64 ...
  ..$ weights          : num [1:62] 0.0161 0.0161 0.0161 0.0161 0.0161 ...
  ..$ data set         : num [1:62] 1 1 1 1 1 1 1 1 1 1 ...
 $ KDE          :List of 1
  ..$ : num [1:514, 1:2] 2.86 2.86 2.86 2.87 2.87 ...
 $ par          :List of 66
  ..$ xlog     : logi FALSE
  ..$ ylog     : logi FALSE
  ..$ adj      : num 0.5
  ..$ ann      : logi TRUE
  ..$ ask      : logi FALSE
  ..$ bg       : chr "transparent"
  ..$ bty      : chr "o"
  ..$ cex      : num 1
  ..$ cex.axis : num 1
  ..$ cex.lab  : num 1
  ..$ cex.main : num 1.2
  ..$ cex.sub  : num 1
  ..$ col      : chr "black"
  ..$ col.axis : chr "black"
  ..$ col.lab  : chr "black"
  ..$ col.main : chr "black"
  ..$ col.sub  : chr "black"
  ..$ crt      : num 0
  ..$ err      : int 0
  ..$ family   : chr ""
  ..$ fg       : chr "black"
  ..$ fig      : num [1:4] 0 1 0 1
  ..$ fin      : num [1:2] 7 7
  ..$ font     : int 1
  ..$ font.axis: int 1
  ..$ font.lab : int 1
  ..$ font.main: int 2
  ..$ font.sub : int 1
  ..$ lab      : int [1:3] 5 5 7
  ..$ las      : int 0
  ..$ lend     : chr "round"
  ..$ lheight  : num 1
  ..$ ljoin    : chr "round"
  ..$ lmitre   : num 10
  ..$ lty      : chr "solid"
  ..$ lwd      : num 1
  ..$ mai      : num [1:4] 0.9 0.9 0.7 1.4
  ..$ mar      : num [1:4] 4.5 4.5 3.5 7
  ..$ mex      : num 1
  ..$ mfcol    : int [1:2] 1 1
  ..$ mfg      : int [1:4] 1 1 1 1
  ..$ mfrow    : int [1:2] 1 1
  ..$ mgp      : num [1:3] 3 1 0
  ..$ mkh      : num 0.001
  ..$ new      : logi FALSE
  ..$ oma      : num [1:4] 0 0 0 0
  ..$ omd      : num [1:4] 0 1 0 1
  ..$ omi      : num [1:4] 0 0 0 0
  ..$ pch      : int 1
  ..$ pin      : num [1:2] 4.7 5.4
  ..$ plt      : num [1:4] 0.129 0.8 0.129 0.9
  ..$ ps       : int 12
  ..$ pty      : chr "m"
  ..$ smo      : num 1
  ..$ srt      : num 0
  ..$ tck      : num NA
  ..$ tcl      : num -0.5
  ..$ usr      : num [1:4] 0 20.4 -36.8 15.9
  ..$ xaxp     : num [1:3] 0 20 4
  ..$ xaxs     : chr "r"
  ..$ xaxt     : chr "s"
  ..$ xpd      : logi TRUE
  ..$ yaxp     : num [1:3] -30 10 4
  ..$ yaxs     : chr "r"
  ..$ yaxt     : chr "s"
  ..$ ylbias   : num 0.2
> plot1$zlim
[1]  17.41711 132.85700
> 
> ## now with adjusted z-scale limits
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  zlim = c(10, 200))
> 
> ## now with adjusted x-scale limits
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  xlim = c(0, 20))
> 
> ## now with rug to indicate individual values in KDE part
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  rug = TRUE)
> 
> ## now with a smaller bandwidth for the KDE plot
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  bw = 0.04)
> 
> ## now with a histogram instead of the KDE plot
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  hist = TRUE,
+                  kde = FALSE)
> 
> ## now with a KDE plot and histogram with manual number of bins
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  hist = TRUE,
+                  breaks = 20)
> 
> ## now with a KDE plot and a dot plot
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  dots = TRUE)
> 
> ## now with user-defined plot ratio
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  plot.ratio = 0.5)
> ## now with user-defined central value
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  z.0 = 70)
> 
> ## now with median as central value
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  z.0 = "median")
> 
> ## now with the 17-83 percentile range as definition of scatter
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  z.0 = "median",
+                  dispersion = "p17")
> 
> ## now with user-defined green line for minimum age model
> CAM <- calc_CentralDose(ExampleData.DeValues,
+                         plot = FALSE)

 [calc_CentralDose]

----------- meta data ----------------
 n:                       62
 log:                     TRUE
----------- dose estimate ------------
 abs. central dose:       65.71
 abs. SE:                 3.05
 rel. SE [%]:             4.65
----------- overdispersion -----------
 abs. OD:                 22.79
 abs. SE:                 2.27
 OD [%]:                  34.69
 SE [%]:                  3.46
-------------------------------------

> 
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  line = CAM,
+                  line.col = "darkgreen",
+                  line.label = "CAM")
> 
> ## now create plot with legend, colour, different points and smaller scale
> plot_AbanicoPlot(data = ExampleData.DeValues,
+                  legend = "Sample 1",
+                  col = "tomato4",
+                  bar.col = "peachpuff",
+                  pch = "R",
+                  cex = 0.8)
Error in abs(mapply(strwidth, legend, cex = cex, font = text.font, MoreArgs = list(units = "user"))) : 
  non-numeric argument to mathematical function
Calls: plot_AbanicoPlot -> legend
Execution halted