tests/testthat/test-lsm-c-te.R

In r-spatialecology/landscapemetrics: Landscape Metrics for Categorical Map Patterns

landscapemetrics_class_landscape_value <- lsm_c_te(landscape)

test_lsm <- matrix(data = NA, nrow = 25, ncol = 30)

test_lsm[c(5:7), c(5:7)] <- 1
test_lsm[4, 6] <- 1
test_lsm[6, 8] <- 1
test_lsm[8, 6] <- 1
test_lsm[6, 4] <- 1
test_lsm[6, 6] <- 2

test_lsm <- terra::rast(test_lsm)

test_that("lsm_c_te is typestable", {
    expect_s3_class(lsm_c_te(landscape), "tbl_df")
    expect_s3_class(lsm_c_te(landscape_stack), "tbl_df")
    expect_s3_class(lsm_c_te(landscape_list), "tbl_df")
})

test_that("lsm_c_te returns the desired number of columns", {
    expect_equal(ncol(landscapemetrics_class_landscape_value), 6)
})

test_that("lsm_c_te returns in every column the correct type", {
    expect_type(landscapemetrics_class_landscape_value$layer, "integer")
    expect_type(landscapemetrics_class_landscape_value$level, "character")
    expect_type(landscapemetrics_class_landscape_value$class, "integer")
    expect_type(landscapemetrics_class_landscape_value$id, "integer")
    expect_type(landscapemetrics_class_landscape_value$metric, "character")
    expect_type(landscapemetrics_class_landscape_value$value, "double")
})

test_that("lsm_l_te equals 0 if only one patch is present",  {
    result <- lsm_c_te(landscape_uniform, count_boundary = FALSE)
    expect_equal(result$value, 0)
})

test_that("lsm_c_te can handle raster with different xy resolution", {
    expect_s3_class(lsm_c_te(landscape_diff_res), "tbl_df")
})

test_that("lsm_c_te is the same if count_boundary = FALSE and vice versa", {

    result_cbF <- lsm_c_te(test_lsm, count_boundary = FALSE)
    result_cbT <- lsm_c_te(test_lsm, count_boundary = TRUE)

    expect_true(result_cbF$value[[1]] == result_cbF$value[[2]])
    expect_true(result_cbT$value[[1]] != result_cbF$value[[2]])
})

test_that("lsm_c_te equals FRAGSTATS", {
    lsm_landscape <- lsm_c_te(landscape) |> dplyr::pull(value)
    lsm_augusta <- lsm_c_te(augusta_nlcd) |> dplyr::pull(value)

    fs_landscape <- dplyr::filter(fragstats_class, LID == "landscape", metric == "te") |> dplyr::pull(value)
    fs_augusta <- dplyr::filter(fragstats_class, LID == "augusta_nlcd", metric == "te") |> dplyr::pull(value)

    expect_true(test_relative(obs = lsm_landscape, exp = fs_landscape, tolerance = tol_rel))
    expect_true(test_relative(obs = lsm_augusta, exp = fs_augusta, tolerance = tol_rel))
})