Nothing
## load data
obj <- set_RLum(class = "RLum.Results",
data = list(vn_values = rep(x = c(1,2), each = 50)))
test_that("input validation", {
testthat::skip_on_cran()
expect_error(plot_MoranScatterplot("error"),
"'object' should be of class 'RLum.Results', 'numeric' or")
expect_error(plot_MoranScatterplot(obj, df_neighbours = "error"),
"'df_neighbours' should be of class 'data.frame'")
expect_error(plot_MoranScatterplot(obj, df_neighbours = data.frame()),
"'df_neighbours' should be a data frame with 3 columns")
expect_error(plot_MoranScatterplot(obj, str_y_def = "error"),
"'str_y_def' should be one of 'mean_neighbours' or")
expect_error(plot_MoranScatterplot(1:10),
"'object' should have length 100")
})
test_that("check functionality", {
testthat::skip_on_cran()
expect_silent(plot_MoranScatterplot(obj))
expect_silent(plot_MoranScatterplot(1:100,
pch = "show_location_ids"))
expect_silent(plot_MoranScatterplot(1:100,
pch = "show_n_neighbours"))
expect_silent(plot_MoranScatterplot(obj, str_y_def = "weighted_sum",
pch = 16))
## problematic values for the log transform
expect_warning(plot_MoranScatterplot(1:100 - 1, log = "xy",
legend = FALSE),
"x-axis values rescaled because of log transform")
expect_warning(plot_MoranScatterplot(1:100 - 2, log = "xy",
legend = FALSE),
"x-axis values rescaled because of log transform")
expect_warning(plot_MoranScatterplot((1:100) - 20, log = "y",
legend = FALSE),
"y-axis values rescaled because of log transform \\(also in return df\\)")
expect_silent(plot_MoranScatterplot((1:100) - 2, log = "y",
legend = FALSE))
obj.na <- obj
obj.na@data$vn_values[c(24, 73)] <- NA
expect_warning(plot_MoranScatterplot(obj.na, legend = TRUE),
"Grain observations removed from plot because no neighbours")
})
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