tests/testthat/test-calculate_energy.R

In mhesselbarth/SHAR: Species-Habitat Associations

# context("test-calculate_energy")

pattern_random_a <- fit_point_process(pattern = species_a, n_random = 3,
                                      verbose = FALSE)

pattern_random_b <- fit_point_process(pattern = species_b, n_random = 3,
                                      return_input = FALSE, verbose = FALSE)

marks_sub <- spatstat.geom::subset.ppp(species_a, select = dbh)

marks_recon <- reconstruct_pattern_marks(pattern_random_a$randomized[[1]], marks_sub,
                                         n_random = 3, max_runs = 10, verbose = FALSE)

marks_recon_na <- marks_recon
marks_recon_na$energy_df <- NA

################################################################################

test_that("calculate_energy returns energy for all randomizations", {

  expect_length(calculate_energy(pattern_random_a, verbose = FALSE), n = 3)

})

test_that("calculate_energy uses weights", {

  unweighted <- calculate_energy(pattern_random_a, return_mean = TRUE, verbose = FALSE)

  weighted <- calculate_energy(pattern_random_a, weights = c(0, 1), return_mean = TRUE,
                               verbose = FALSE)

  expect_false(unweighted == weighted)

})

test_that("calculate_energy returns mean ", {

  mean_energy <- mean(calculate_energy(pattern_random_a, verbose = FALSE))

  expect_equal(calculate_energy(pattern_random_a, return_mean = TRUE,
                                          verbose = FALSE),
                         expected = mean_energy)

})

test_that("calculate_energy returns works for reconstructed marks", {

  expect_length(calculate_energy(marks_recon, verbose = FALSE), n = 3)

  mean_energy <- mean(calculate_energy(marks_recon, verbose = FALSE))

  expect_equal(calculate_energy(marks_recon, return_mean = TRUE,
                                verbose = FALSE), expected = mean_energy)

  expect_length(calculate_energy(marks_recon_na, verbose = FALSE), n = 3)

})

test_that("calculate_energy returns error if observed not included", {

  expect_error(calculate_energy(pattern_random_b, verbose = FALSE),
               regexp = "Input must include 'observed' pattern.")

})

test_that("calculate_energy returns error if wrong class ", {

  expect_error(calculate_energy(list(species_a, species_b), verbose = FALSE),
               regexp = "Class of 'pattern' must be 'rd_pat' or 'rd_mar'.")

})