# Compare: https://en.wikipedia.org/wiki/Erlang_distribution
#
# The Erlang distribution is a special case of the gamma distribution wherein
# the shape (k) of the distribution is discretised.
e <- Erlang(k = 3, lambda = 0.5)

test_that("Erlang constructor works", {
  expect_error(Erlang(k = 3.1, lambda = 0.5))
})

test_that("print.Erlang works", {
  expect_output(print(e), regexp = "Erlang")
})

test_that("random.Erlang works correctly", {
  set.seed(123)
  r1 <- random(e, 3)
  set.seed(123)
  r2 <- rgamma(3, shape = 3, rate = 0.5)
  expect_equal(unname(r1), r2)

  expect_length(random(e), 1)
  expect_length(random(e, 100), 100)
  expect_length(random(e[-1], 1), 0)
  expect_length(random(e, 0), 0)
  expect_error(random(e, -2))

  # consistent with base R, using the `length` as number of samples to draw
  expect_length(random(e, c(1, 2, 3)), 3)
  expect_length(random(e, cbind(1, 2, 3)), 3)
  expect_length(random(e, rbind(1, 2, 3)), 3)
})

test_that("pdf.Erlang works correctly", {
  expect_equal(pdf(e, 0), dgamma(0, shape = 3, rate = 0.5))
  expect_equal(pdf(e, 1), dgamma(1, shape = 3, rate = 0.5))

  expect_length(pdf(e, seq_len(0)), 0)
  expect_length(pdf(e, seq_len(1)), 1)
  expect_length(pdf(e, seq_len(10)), 10)
})

test_that("log_pdf.Erlang works correctly", {
  expect_equal(log_pdf(e, 0), log(dgamma(0, shape = 3, rate = 0.5)))
  expect_equal(log_pdf(e, 1), log(dgamma(1, shape = 3, rate = 0.5)))

  expect_length(log_pdf(e, seq_len(0)), 0)
  expect_length(log_pdf(e, seq_len(1)), 1)
  expect_length(log_pdf(e, seq_len(10)), 10)
})

test_that("cdf.Erlang works correctly", {
  expect_equal(cdf(e, 0.3), pgamma(0.3, shape = 3, rate = 0.5))
  expect_equal(cdf(e, 1), pgamma(1, shape = 3, rate = 0.5))

  expect_equal(cdf(e, 0), 0)
  expect_length(cdf(e, seq_len(0)), 0)
  expect_length(cdf(e, seq_len(1)), 1)
  expect_length(cdf(e, seq_len(10)), 10)
})

test_that("quantile.Erlang works correctly", {
  expect_equal(quantile(e, 0.3), qgamma(0.3, shape = 3, rate = 0.5))
  expect_equal(quantile(e, 1), qgamma(1, shape = 3, rate = 0.5))

  expect_equal(quantile(e, 0), 0)
  expect_length(quantile(e, seq_len(1)), 1)
  expect_length(quantile(e, seq(0.1, 0.9, by = 0.1)), 9)
})

test_that("support.Erlang works correctly", {
  expect_equal(unname(support(e)), c(0, Inf))
})

test_that("vectorization of a Erlang distribution work correctly", {
  d <- Erlang(3, c(0.5, 0.8))
  d1 <- d[1]
  d2 <- d[2]

  ## random
  set.seed(123)
  r1 <- random(d)
  set.seed(123)
  r2 <- c(random(d1), random(d2))
  expect_equal(r1, r2)

  ## pdf, log_pdf, cdf
  expect_equal(pdf(d, 0), c(pdf(d1, 0), pdf(d2, 0)))
  expect_equal(log_pdf(d, 0), c(log_pdf(d1, 0), log_pdf(d2, 0)))
  expect_equal(cdf(d, 0.5), c(cdf(d1, 0.5), cdf(d2, 0.5)))

  ## quantile
  expect_equal(quantile(d, 0.5), c(quantile(d1, 0.5), quantile(d2, 0.5)))
  expect_equal(quantile(d, c(0.5, 0.5)), c(quantile(d1, 0.5), quantile(d2, 0.5)))
  expect_equal(
    quantile(d, c(0.1, 0.5, 0.9)),
    matrix(
      rbind(quantile(d1, c(0.1, 0.5, 0.9)), quantile(d2, c(0.1, 0.5, 0.9))),
      ncol = 3, dimnames = list(NULL, c("q_0.1", "q_0.5", "q_0.9"))
    )
  )

  ## elementwise
  expect_equal(
    pdf(d, c(0.25, 0.75), elementwise = TRUE),
    diag(pdf(d, c(0.25, 0.75), elementwise = FALSE))
  )
  expect_equal(
    cdf(d, c(0.25, 0.75), elementwise = TRUE),
    diag(cdf(d, c(0.25, 0.75), elementwise = FALSE))
  )
  expect_equal(
    quantile(d, c(0.25, 0.75), elementwise = TRUE),
    diag(quantile(d, c(0.25, 0.75), elementwise = FALSE))
  )

  ## support
  expect_equal(
    support(d),
    matrix(
      c(support(d1)[1], support(d2)[1], support(d1)[2], support(d2)[2]),
      ncol = 2, dimnames = list(names(d), c("min", "max"))
    )
  )
  expect_true(!any(is_discrete(d)))
  expect_true(all(is_continuous(d)))
  expect_true(is.numeric(support(d1)))
  expect_true(is.numeric(support(d1, drop = FALSE)))
  expect_null(dim(support(d1)))
  expect_equal(dim(support(d1, drop = FALSE)), c(1L, 2L))
})

test_that("named return values for Erlang distribution work correctly", {
  d <- Erlang(3, c(0.5, 0.8))
  names(d) <- LETTERS[1:length(d)]

  expect_equal(names(random(d, 1)), LETTERS[1:length(d)])
  expect_equal(rownames(random(d, 3)), LETTERS[1:length(d)])
  expect_equal(names(pdf(d, 0.5)), LETTERS[1:length(d)])
  expect_equal(names(pdf(d, c(0.5, 0.7))), LETTERS[1:length(d)])
  expect_equal(rownames(pdf(d, c(0.5, 0.7, 0.9))), LETTERS[1:length(d)])
  expect_equal(names(log_pdf(d, 0.5)), LETTERS[1:length(d)])
  expect_equal(names(log_pdf(d, c(0.5, 0.7))), LETTERS[1:length(d)])
  expect_equal(rownames(log_pdf(d, c(0.5, 0.7, 0.9))), LETTERS[1:length(d)])
  expect_equal(names(cdf(d, 0.5)), LETTERS[1:length(d)])
  expect_equal(names(cdf(d, c(0.5, 0.7))), LETTERS[1:length(d)])
  expect_equal(rownames(cdf(d, c(0.5, 0.7, 0.9))), LETTERS[1:length(d)])
  expect_equal(names(quantile(d, 0.5)), LETTERS[1:length(d)])
  expect_equal(names(quantile(d, c(0.5, 0.7))), LETTERS[1:length(d)])
  expect_equal(rownames(quantile(d, c(0.5, 0.7, 0.9))), LETTERS[1:length(d)])
  expect_equal(names(support(d[1])), c("min", "max"))
  expect_equal(colnames(support(d)), c("min", "max"))
  expect_equal(rownames(support(d)), LETTERS[1:length(d)])
})