test_that("Test examples from the example page", {
testthat::skip_on_cran()
local_edition(3)
## load example data and recalculate to Gray
data(ExampleData.DeValues, envir = environment())
ExampleData.DeValues <- ExampleData.DeValues$CA1
## plot the example data straightforward
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues))
## now with linear z-scale
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
log.z = FALSE))
## now with output of the plot parameters
expect_type(plot_AbanicoPlot(data = ExampleData.DeValues,
output = TRUE), "list")
## now with adjusted z-scale limits
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
zlim = c(10, 200)))
## now with adjusted x-scale limits
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
xlim = c(0, 20)))
## now with rug to indicate individual values in KDE part
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
rug = TRUE))
## now with a smaller bandwidth for the KDE plot
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
bw = 0.04))
## now with a histogram instead of the KDE plot
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
hist = TRUE,
kde = FALSE))
## now with a KDE plot and histogram with manual number of bins
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
hist = TRUE,
breaks = 20))
## now with a KDE plot and a dot plot
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
dots = TRUE))
## now with user-defined plot ratio
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
plot.ratio = 0.5))
## now with user-defined central value
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
z.0 = 70))
## now with median as central value
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
z.0 = "median"))
## now with the 17-83 percentile range as definition of scatter
expect_silent(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)
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
line = CAM,
line.col = "darkgreen",
line.label = "CAM"))
## now create plot with legend, colour, different points and smaller scale
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
legend = "Sample 1",
col = "tomato4",
bar.col = "peachpuff",
pch = "R",
cex = 0.8))
## now without 2-sigma bar, polygon, grid lines and central value line
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
bar.col = FALSE,
polygon.col = FALSE,
grid.col = FALSE,
y.axis = FALSE,
lwd = 0))
## now with direct display of De errors, without 2-sigma bar
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
bar.col = FALSE,
ylab = "",
y.axis = FALSE,
error.bars = TRUE))
## now with user-defined axes labels
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
xlab = c("Data error (%)",
"Data precision"),
ylab = "Scatter",
zlab = "Equivalent dose [Gy]"))
## now with minimum, maximum and median value indicated
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
stats = c("min", "max", "median")))
## now with a brief statistical summary as subheader
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
summary = c("n", "in.2s")))
## now with another statistical summary
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
summary = c("mean.weighted", "median"),
summary.pos = "topleft"))
## now a plot with two 2-sigma bars for one data set
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
bar = c(30, 100)))
## now the data set is split into sub-groups, one is manipulated
data.1 <- ExampleData.DeValues[1:30,]
data.2 <- ExampleData.DeValues[31:62,] * 1.3
data.3 <- list(data.1, data.2)
## now the two data sets are plotted in one plot
expect_silent(plot_AbanicoPlot(data = data.3))
## now with some graphical modification
expect_silent(plot_AbanicoPlot(data = data.3,
z.0 = "median",
col = c("steelblue4", "orange4"),
bar.col = c("steelblue3", "orange3"),
polygon.col = c("steelblue1", "orange1"),
pch = c(2, 6),
angle = c(30, 50),
summary = c("n", "in.2s", "median")))
## create Abanico plot with predefined layout definition
expect_silent(plot_AbanicoPlot(data = ExampleData.DeValues,
layout = "journal"))
## now with predefined layout definition and further modifications
expect_silent(plot_AbanicoPlot(data = data.3,
z.0 = "median",
layout = "journal",
col = c("steelblue4", "orange4"),
bar.col = adjustcolor(c("steelblue3", "orange3"),
alpha.f = 0.5),
polygon.col = c("steelblue3", "orange3")))
## for further information on layout definitions see documentation
## of function get_Layout()
## now with manually added plot content
## create empty plot with numeric output
expect_type(plot_AbanicoPlot(data = ExampleData.DeValues,
pch = NA,
output = TRUE), "list")
})
test_that("Cause full function stop", {
testthat::skip_on_cran()
local_edition(3)
##wrong input data
expect_error(plot_AbanicoPlot(data = "Michael"),
regexp = "Input data format is neither 'data.frame' nor 'RLum.Results'")
})
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