# context("test-fit_point_process")
# normal
pattern_random <- fit_point_process(pattern = species_b, n_random = 3,
verbose = FALSE)
# cluster process
pattern_random_cluster <- fit_point_process(pattern = species_b, n_random = 3,
process = "cluster", verbose = FALSE)
# no input
pattern_random_ni <- fit_point_process(pattern = species_a, n_random = 3,
return_input = FALSE, verbose = FALSE)
# simple output
pattern_random_simple <- fit_point_process(pattern = species_a, n_random = 1,
return_input = FALSE, simplify = TRUE,
verbose = FALSE)
# return parameters
pattern_random_para_a <- fit_point_process(pattern = species_b, n_random = 3,
process = "poisson", return_para = TRUE,
verbose = FALSE)
# return parameters
pattern_random_para_b <- fit_point_process(pattern = species_b, n_random = 3,
process = "cluster", return_para = TRUE,
verbose = FALSE)
################################################################################
test_that("Output is a long as n_random for fit_point_process", {
expect_length(pattern_random$randomized, n = 3)
expect_length(pattern_random_cluster$randomized, n = 3)
})
test_that("Output includes randomizations and original pattern for fit_point_process", {
expect_named(pattern_random$randomized, expected = paste0("randomized_", 1:3))
expect_equal(pattern_random$observed, expected = spatstat.geom::unmark(species_b))
expect_named(pattern_random_cluster$randomized, expected = paste0("randomized_", 1:3))
expect_equal(pattern_random_cluster$observed, expected = spatstat.geom::unmark(species_b))
})
test_that("Fitted patterns have same number of points for cluster process", {
expect_true(all(vapply(pattern_random$randomized, FUN.VALUE = logical(1),
function(x) x$n == species_b$n)))
expect_true(all(vapply(pattern_random_cluster$randomized, FUN.VALUE = logical(1),
function(x) x$n == species_b$n)))
})
test_that("Input pattern can not be returned for fit_point_process", {
expect_true(object = is.na(pattern_random_ni$observed))
})
test_that("simplify works for fit_point_process", {
expect_s3_class(pattern_random_simple, "ppp")
})
test_that("Parameters can be returned", {
expect_named(object = pattern_random_para_a$para, expected = c("number_points", "lambda"))
expect_named(object = pattern_random_para_b$para,
expected = c("number_parents", "number_points", "cluster_area"))
expect_true(object = is.na(pattern_random$param))
})
test_that("fit_point_process returns errors", {
expect_error(fit_point_process(pattern = species_b, n_random = -10, verbose = FALSE),
regexp = "n_random must be >= 1.")
expect_error(fit_point_process(pattern = species_b, n_random = 19, process = "not_valid",
verbose = FALSE),
regexp = "Please select either 'poisson' or 'cluster'.")
})
test_that("fit_point_process returns warnings", {
expect_warning(fit_point_process(pattern = species_a, n_random = 3, return_input = FALSE,
simplify = TRUE, verbose = FALSE),
regexp = "'simplify = TRUE' not possible for 'n_random > 1'.")
expect_warning(fit_point_process(pattern = species_a, n_random = 1, simplify = TRUE,
verbose = FALSE),
regexp = "'simplify = TRUE' not possible for 'return_input = TRUE'.")
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.