test_that("sugm clime basic call works", {
  set.seed(301)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)

  fit <- sugm(x, nlambda = 3, method = "clime", verbose = FALSE, max.ite = 2000)
  expect_s3_class(fit, "sugm")
  expect_equal(fit$method, "clime")
  expect_equal(fit$nlambda, 3L)
  expect_length(fit$path, 3L)
})

test_that("sugm tiger basic call works", {
  set.seed(302)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)

  fit <- sugm(x, nlambda = 3, method = "tiger", verbose = FALSE, max.ite = 2000)
  expect_s3_class(fit, "sugm")
  expect_equal(fit$method, "tiger")
  expect_length(fit$path, 3L)
})

test_that("sugm clime accepts covariance matrix input", {
  set.seed(303)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)
  S <- cov(x)

  fit <- sugm(S, nlambda = 3, method = "clime", verbose = FALSE, max.ite = 2000)
  expect_s3_class(fit, "sugm")
  expect_true(fit$cov.input)
})

test_that("sugm clime tolerates missing values in raw data", {
  set.seed(304)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)
  x[2, 3] <- NA
  x[10, 1] <- NA

  fit <- sugm(x, nlambda = 3, method = "clime", verbose = FALSE, max.ite = 2000)
  expect_s3_class(fit, "sugm")
})

test_that("sugm tiger rejects missing values", {
  set.seed(305)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)
  x[2, 3] <- NA

  expect_error(
    sugm(x, nlambda = 3, method = "tiger", verbose = FALSE),
    "missing values"
  )
})

test_that("sugm sym='and' is at least as sparse as sym='or'", {
  set.seed(306)
  x <- matrix(rnorm(200), nrow = 40, ncol = 5)

  fit_or <- sugm(x, nlambda = 3, method = "clime", sym = "or", verbose = FALSE, max.ite = 2000)
  fit_and <- sugm(x, nlambda = 3, method = "clime", sym = "and", verbose = FALSE, max.ite = 2000)

  for (i in seq_len(3)) {
    expect_true(sum(fit_and$path[[i]]) <= sum(fit_or$path[[i]]))
  }
})

test_that("sugm tiger rejects d < 3", {
  set.seed(307)
  x <- matrix(rnorm(40), nrow = 20, ncol = 2)

  expect_error(
    sugm(x, nlambda = 3, method = "tiger", verbose = FALSE),
    "d>=3"
  )
})