tests/testthat/test-point-cloud-analysis.R

In munterfinger/eRTG3D: Empirically Informed Random Trajectory Generation in 3-D

test_that("point-cloud-analysis works", {
  grDevices::pdf(NULL)
  crws <- lapply(X = seq(1:100), FUN = function(X) {
    sim.crw.3d(nStep = 100, rTurn = 0.99, rLift = 0.99, meanStep = 0.1)
  })
  points <- do.call("rbind", crws)
  extent <- raster::extent(c(-10, 10, -10, 10))
  # Voxel count standartize
  ud <- voxelCount(points, extent, xyRes = 5, zMin = -10, zMax = 10, standartize = TRUE)
  saveImageSlices(ud, filename = "saveImageSlices_testthat", dir = tempdir())
  expect_is(ud, "RasterStack")
  # Voxel count
  ud <- voxelCount(points, extent, xyRes = 5, zMin = -10, zMax = 10)
  expect_is(ud, "RasterStack")
  # Chi maps one raster
  chi <- chiMaps(ud)
  expect_is(chi, "RasterStack")
  # Log raster stack
  expect_is(logRasterStack(abs(chi)), "RasterStack")
  expect_is(logRasterStack(abs(chi), standartize = TRUE), "RasterStack")
  # Raster stack plots
  expect_is(plotRaster(chi, centerColorBar = TRUE), c("gtable", "gTree", "grob", "gDesc"))
  expect_is(plotRaster(chi, centerColorBar = FALSE), c("gtable", "gTree", "grob", "gDesc"))
  expect_is(plotRaster(chi, ncol = 1), c("gtable", "gTree", "grob", "gDesc"))
  expect_equal(plotRaster(chi[[1]]), NULL)
  # Chi maps two raster
  chi_two <- chiMaps(ud, ud)
  expect_is(chi_two, "RasterStack")
})