tests/testthat/test_cluster.R

In SilviaTerra/forestsamplr: Standard Forest Sampling Design Workups

context("Forest sampling statistics calculations: cluster sample")

clusterClean <- clusterBaData %>%
  filter(!is.na(bapa))
# test clusters
clusterFalse <- data.frame(
  clusterID = c(1, 2, 3, 4, 5), clusterElements = c(4, 2, 1, 5, 4),
  sumAttr = c(1039, 1125, 950, 1001, 1039), isUsed = c(T, T, T, T, F)
)

clusterTrue <- data.frame(
  clusterID = c(1, 2, 3, 4, 5), clusterElements = c(4, 2, 1, 5, 4),
  sumAttr = c(1000, 1250, 950, 900, 1005), isUsed = c(T, T, T, T, T)
)

clusterNone <- data.frame(
  clusterID = c(NA), clusterElements = c(NA),
  sumAttr = c(NA), isUsed = c(NA)
)

clusterOne <- data.frame(
  clusterID = c(1), clusterElements = c(4),
  sumAttr = c(1000), isUsed = c(T)
)

clusterTwo <- data.frame(
  clusterID = c(1, 2), clusterElements = c(4, 2),
  sumAttr = c(1000, 1250), isUsed = c(T, T)
)

# test plots
plotLevelFalse <- clusterClean
plotLevelTrue <- clusterClean %>% mutate(isUsed = TRUE)

test_that("cluster sample isUsed functions correctly", {
  expect_equal(summarize_cluster(clusterFalse, F)[[1]], c(43.8), tolerance = 0.1)
  expect_false(identical(
    summarize_cluster(clusterTrue, F),
    summarize_cluster(clusterFalse, F)
  ))
  expect_false(identical(
    summarize_cluster(plotLevelTrue, T, attr = "bapa"),
    summarize_cluster(plotLevelFalse, T, attr = "bapa")
  ))
})


test_that("cluster sample handles input with no, one, or two clusters correctly", {
  expect_error(summarize_cluster(clusterNone, F))
  expect_error(summarize_cluster(clusterOne, F))
  expect_false(any(is.na(summarize_cluster(clusterTwo, F))))
})


test_that("cluster sample handles input data with NA values", {
  expect_error(summarize_cluster(clusterBaData, T))
})


test_that("cluster sample handles attribute", {
  expect_equal(
    summarize_cluster(clusterClean, T, "bapa"),
    summarize_cluster(clusterClean %>% rename(attr = bapa), T)
  )
})