test_that("Integration L", {
  data <- integration.testdata1()
  prob1 <- gaussint(
    Q.chol = data$L, a = data$a, b = data$b,
    seed = data$seed, max.threads = 1
  )
  expect_equal(prob1$P[1], 0.9680023, tolerance = 1e-7)
  expect_equal(prob1$E[1], 5.914764e-06, tolerance = 1e-6)
})

test_that("Integration Q", {
  data <- integration.testdata1()
  prob1 <- gaussint(
    Q = data$Q, a = data$a, b = data$b,
    seed = data$seed, max.threads = 1
  )
  expect_equal(prob1$P[1], 0.9680023, tolerance = 1e-7)
  expect_equal(prob1$E[1], 5.914764e-06, tolerance = 1e-6)
})

test_that("Integration mu", {
  data <- integration.testdata1()
  prob1 <- gaussint(
    Q = data$Q, mu = data$mu, a = data$a + data$mu,
    b = data$b + data$mu, seed = data$seed,
    max.threads = 1
  )
  expect_equal(prob1$P[1], 0.9680023, tolerance = 1e-7)
  expect_equal(prob1$E[1], 5.914764e-06, tolerance = 1e-6)
})

test_that("Integration limit", {
  data <- integration.testdata1()
  prob1 <- gaussint(
    Q = data$Q, a = data$a, b = data$b,
    seed = data$seed, lim = 0.97,
    max.threads = 1
  )

  prob2 <- gaussint(
    Q = data$Q, a = data$a, b = data$b,
    seed = data$seed, lim = 0.9,
    max.threads = 1
  )

  expect_equal(prob1$P[1], 0.0, tolerance = 1e-7)
  expect_equal(prob2$P[1], 0.9680023, tolerance = 1e-6)
})

test_that("Integration reordering", {
  data <- integration.testdata1()
  prob1 <- gaussint(
    Q = data$Q, mu = data$mu, a = data$a + data$mu,
    b = data$b + data$mu, seed = data$seed,
    max.threads = 1, use.reordering = "sparsity"
  )
  expect_equal(prob1$P[1], 0.9680023, tolerance = 1e-5)
  expect_equal(prob1$E[1], 5.914764e-06, tolerance = 1e-5)
})