context("check accuracy of flex.test binomial")
set.seed(16)
data(nydf)
data(nyw)
coords <- cbind(nydf$longitude, nydf$latitude)
cases <- floor(nydf$cases)
pop <- nydf$population
outb <- flex.test(
  coords = coords, cases = cases, pop = pop,
  w = nyw, k = 10, nsim = 99, alpha = 1,
  type = "binomial"
)

# results taken from flex_test_ny_binomial_10nn_cartesian
test_that("check accuracy for flex.test binomial", {
  expect_equal(
    sort(outb$clusters[[1]]$locids),
    c(85, 86, 88, 89, 90, 92, 93)
  )
  expect_equal(round(outb$clusters[[1]]$max_dist, 6), 0.245662)
  expect_equal(outb$clusters[[1]]$cases, 39)
  expect_equal(outb$clusters[[1]]$pop, 31420)
  expect_equal(round(outb$clusters[[1]]$smr, 5), 2.37832)
  expect_equal(round(outb$clusters[[1]]$test_statistic, 4), 11.6797)
  # p-values are tough to test, make sure results don't change
  # in future versions since these were manually checked
  expect_equal(outb$clusters[[1]]$pvalue, 0.01)

  expect_equal(
    sort(outb$clusters[[2]]$locids),
    c(1, 2, 13, 15, 47, 49, 51)
  )
  expect_equal(round(outb$clusters[[2]]$max_dist, 7), 0.0507453)
  expect_equal(outb$clusters[[2]]$cases, 31)
  expect_equal(outb$clusters[[2]]$pop, 25764)
  expect_equal(round(outb$clusters[[2]]$smr, 5), 2.30548)
  expect_equal(round(outb$clusters[[2]]$test_statistic, 5), 8.63552)
  # p-values are tough to test, make sure results don't change
  # in future versions since these were manually checked
  expect_equal(outb$clusters[[2]]$pvalue, 0.05)

  expect_equal(
    sort(outb$clusters[[9]]$locids),
    c(102, 103, 106)
  )
  expect_equal(round(outb$clusters[[9]]$max_dist, 6), 0.194769)
  expect_equal(outb$clusters[[9]]$cases, 11)
  expect_equal(outb$clusters[[9]]$pop, 9125)
  expect_equal(round(outb$clusters[[9]]$smr, 5), 2.30979)
  expect_equal(round(outb$clusters[[9]]$test_statistic, 5), 3.00889)
  # p-values are tough to test, make sure results don't change
  # in future versions since these were manually checked
  expect_equal(outb$clusters[[9]]$pvalue, 1)
})