library(testthat)
library(QuantRegGLasso)
tol <- 1e-4

# Test case for qrglasso function
test_that("qrglasso returns expected results", {
  # Create sample data for testing
  set.seed(123)
  n <- 100
  p <- 2
  L <- 5
  pL <- 2 * 5
  Y <- matrix(rnorm(n), n, 1)
  W <- matrix(rnorm(n * pL), n, pL)
  
  # Call the qrglasso function
  result <- qrglasso(Y = Y, W = W, p)
  
  # Perform assertions
  expect_s3_class(result, "qrglasso")
  expect_true(all(names(result) %in% c("gamma", "xi", "phi", "BIC", "lambda", "L", "omega")))
})

test_that("qrglasso with omega", {
  # Generate some example data
  set.seed(123)
  n <- 100
  p <- 100
  L <- 3
  Y <- matrix(rnorm(n), n, 1)
  W <- matrix(runif(n * p, min = 0, max = 5), nrow = n)
  omega <- matrix(runif(p * L), ncol = L)
  
  # Call qrglasso with omega
  result <- qrglasso(
    Y = Y,
    W = W,
    p = p,
    omega = omega,
    tau = 0.7,
    qn = 1.5,
    lambda = c(0.01, 0.1, 1),
    maxit = 500,
    thr = 1e-05
  )
  
  # Perform assertions based on your expectations
  expect_true(is.list(result))
  expect_equal(dim(result$BIC)[1], 3)
  expect_lte(min(result$phi[,3]) + 0.1345752,  tol)
  expect_lte(min(result$xi[,3]) + 1.99916,  tol)
  expect_lte(min(result$gamma[,3]) + 0.1345752, tol)
})

# Mock qrglasso class object for testing
mock_qrglasso <- structure(list(
  L = 6,
  gamma = matrix(rnorm(400), nrow = 5),
  BIC = matrix(runif(10), nrow = 5),
  omega = matrix(runif(120), nrow = 6)
), class = "qrglasso")

test_that("predict coefficient functions", {
  # Valid parameters
  expect_silent(predict(mock_qrglasso))
  
  # Invalid object
  expect_error(predict(list()))
  
  # Negative top_k
  expect_error(predict(mock_qrglasso, "BIC", -2))
  
  # Negative degree
  expect_error(predict(mock_qrglasso, "BIC", 3, -1))
  
  # Incorrect boundaries size
  expect_error(predict(mock_qrglasso, "BIC", 3, 2, c(0, 1, 2)))
  
  # Invalid boundaries order
  expect_error(predict(mock_qrglasso, "BIC", 3, 2, c(1, 0)))
  
  # Invalid metric_type
  expect_error(predict(mock_qrglasso, "invalid_metric"))
})