tests/testthat/test-partition_metrics.R

In bioRgeo/bioRgeo: Bioregionalisation Methods in R

# Preamble code ----------------------------------------------------------------
comat <- matrix(sample(0:1000, size = 500, replace = TRUE, prob = 1/1:1001),
                20, 25)
rownames(comat) <- paste0("Site", 1:20)
colnames(comat) <- paste0("Species", 1:25)

simil <- similarity(comat, metric = "all")
dissimilarity <- similarity_to_dissimilarity(simil)

comat_df <- mat_to_net(comat, weight = TRUE, remove_zeroes = TRUE)

tree1 <- hclu_hierarclust(dissimilarity, n_clust = 2:20,
                          index = "Simpson")

# Tests for valid outputs -----------------------------------------------------
test_that("class list and bioRgeo.clusters", {
  a <- partition_metrics(tree1,
                         dissimilarity = dissimilarity,
                         net = comat_df,
                         site_col = "Node1",
                         species_col = "Node2",
                         eval_metric = c("tot_endemism",
                                         "avg_endemism",
                                         "pc_distance",
                                         "anosim"))
  
  
  expect_identical(class(a)[1], "bioRgeo.partition.metrics")
  expect_identical(class(a)[2], "list")
  
})

# Tests for invalid inputs ----------------------------------------------------
test_that("error messages with wrong inputs", {
  expect_error(
    partition_metrics(NULL,
                      dissimilarity = dissimilarity,
                      net = comat_df,
                      site_col = "Node1",
                      species_col = "Node2",
                      eval_metric = c("tot_endemism",
                                      "avg_endemism",
                                      "pc_distance",
                                      "anosim")),
    "This function is designed to work either on bioRgeo.clusters objects
         (outputs from clustering functions)", fixed = TRUE)
})