tests/testthat/test_calc_AliquotSize.R

In Luminescence: Comprehensive Luminescence Dating Data Analysis

test_that("input validation", {
  testthat::skip_on_cran()

  expect_error(calc_AliquotSize(),
               "Please provide the mean grain size or a range of grain sizes")
  expect_error(calc_AliquotSize(grain.size = 1:3),
               "Please provide the mean grain size or a range of grain sizes")
  expect_error(calc_AliquotSize(grain.size = 100, packing.density = 2),
               "'packing.density' expects values between 0 and 1")
  expect_error(calc_AliquotSize(grain.size = 100, packing.density = 1, sample.diameter = -1),
               "'sample.diameter' should be a positive scalar")
  expect_error(calc_AliquotSize(grain.size = 100, sample.diameter = 9.8,
                                MC = TRUE),
               "'grain.size' must be a vector containing the min and max")
  expect_output(calc_AliquotSize(grain.size = 100, packing.density = 1, sample.diameter = 9.8, grains.counted = 30, MC = TRUE),
                regexp = "Monte Carlo simulation is only available for estimating the amount of grains on the sample disc.")
})

test_that("check functionality", {
  testthat::skip_on_cran()

  SW({
  expect_s4_class(
    calc_AliquotSize(
      grain.size = 100, packing.density = "inf", sample.diameter = 9.8, MC = FALSE), "RLum.Results")
  expect_s4_class(
    calc_AliquotSize(
      grain.size = c(100, 150), grains.counted = 1000, sample.diameter = 9.8, MC = FALSE), "RLum.Results")
  expect_warning(calc_AliquotSize(
      grain.size = c(100, 150), grains.counted = c(1000, 1100, 900),
      sample.diameter = 10, MC = FALSE),
      "A sample diameter of 10 mm was specified, but common sample discs are")
  })

  set.seed(1)
  temp <- calc_AliquotSize(
      grain.size = c(100, 150),
      sample.diameter = 1,
      MC.iter = 100,
      plot = FALSE,
      verbose = FALSE)

  expect_equal(is(temp), c("RLum.Results", "RLum"))
  expect_equal(length(temp), 2)
  expect_s3_class(temp$summary, "data.frame")
  expect_type(temp$MC, "list")

  ## summary output
  result <- get_RLum(temp)
  expect_equal(result$grain.size, 125)
  expect_equal(result$sample.diameter, 1)
  expect_equal(result$packing.density, 0.65)
  expect_equal(result$n.grains, 42)
  expect_equal(result$grains.counted, NA)

  ## MC run
  expect_equal(round(temp$MC$statistics$n), 100)
  expect_equal(round(temp$MC$statistics$mean), 43)
  expect_equal(round(temp$MC$statistics$median), 39)
  expect_equal(round(temp$MC$statistics$sd.abs), 19)
  expect_equal(round(temp$MC$statistics$sd.rel), 45)
  expect_equal(round(temp$MC$statistics$se.abs), 2)
  expect_equal(round(temp$MC$statistics$se.rel), 5)
  expect_length(temp$MC$kde$x, 10000)
  expect_length(temp$MC$kde$y, 10000)
})

test_that("snapshot tests", {
  testthat::skip_on_cran()

  set.seed(1)
  snapshot.tolerance <- 1.5e-4

  SW({
  expect_snapshot_RLum(calc_AliquotSize(
      grain.size = c(80, 150),
      sample.diameter = 1,
      MC.iter = 20,
      plot = FALSE,
      verbose = TRUE),
      tolerance = snapshot.tolerance)
  })

  expect_output(
  expect_snapshot_RLum(calc_AliquotSize(
      grain.size = c(100, 200),
      sample.diameter = 8,
      grains.counted = c(2525, 2312, 2880),
      MC.iter = 20,
      plot = FALSE,
      verbose = FALSE),
      tolerance = snapshot.tolerance),
  "Monte Carlo simulation is only available for estimating the amount of")
})