library(pROC)
data(aSAH)

context("ci.coords")

test_that("ci.coords accepts threshold output with x=best", {
  expect_error(ci.coords(r.wfns, x = "best", input = "specificity", ret = c("threshold", "specificity", "sensitivity"), boot.n = 1), NA)
})

test_that("ci.coords rejects threshold output except with x=best", {
  expect_error(ci.coords(r.wfns, x = 0.9, input = "specificity", ret = c("threshold", "specificity", "sensitivity"), boot.n = 1))
})

test_that("ci.coords accepts threshold output with x=best or if input was threshold", {
  expect_s3_class(ci.coords(r.wfns, x = 2, input = "threshold", ret = c("threshold", "specificity", "sensitivity"), boot.n = 1), "ci.coords")
  expect_s3_class(ci.coords(r.wfns, x = "best", ret = c("threshold", "specificity", "sensitivity"), boot.n = 1), "ci.coords")
})

# Only test whether ci.coords runs and returns without error.
# Uses a very small number of iterations for speed
# Doesn't test whether the results are correct.
valid_coords_input <- coord.is.monotone <- c(
  "threshold", "sensitivity", "specificity", "tn", "tp", "fn", "fp", "tpr",
  "tnr", "fpr", "fnr", "1-specificity", "1-sensitivity", "recall"
)
for (input in valid_coords_input) {
  for (stratified in c(TRUE, FALSE)) {
    for (test.roc in list(r.s100b, smooth(r.s100b))) {
      context(sprintf("input: %s, stratified: %s, class: %s", input, stratified, class(test.roc)))
      test_that("ci.coords accepts one x and one ret", {
        skip_slow()
        obtained <- ci.coords(test.roc,
          x = 0.8, input = input, ret = "sp",
          boot.n = 3, conf.level = .91, boot.stratified = stratified
        )
        expect_equal(attr(obtained, "ret"), "specificity")
        expect_equal(names(obtained), attr(obtained, "ret"))
        for (ci.mat in obtained) {
          expect_equal(dim(ci.mat), c(1, 3))
          expect_equal(colnames(ci.mat), c("4.5%", "50%", "95.5%"))
        }
      })

      test_that("ci.coords accepts one x and multiple ret", {
        skip_slow()
        obtained <- ci.coords(test.roc,
          x = 0.8, input = input, ret = c("sp", "ppv", "tp", "1-sensitivity"),
          boot.n = 3, conf.level = .91, boot.stratified = stratified
        )
        expect_equal(attr(obtained, "ret"), c("specificity", "ppv", "tp", "1-sensitivity"))
        expect_equal(names(obtained), attr(obtained, "ret"))
        for (ci.mat in obtained) {
          expect_equal(dim(ci.mat), c(1, 3))
          expect_equal(colnames(ci.mat), c("4.5%", "50%", "95.5%"))
        }
      })

      test_that("ci.coords accepts multiple x and one ret", {
        skip_slow()
        obtained <- ci.coords(test.roc,
          x = c(0.8, 0.9), input = input, ret = "sp",
          boot.n = 3, conf.level = .91, boot.stratified = stratified
        )
        expect_equal(attr(obtained, "ret"), "specificity")
        expect_equal(names(obtained), attr(obtained, "ret"))
        for (ci.mat in obtained) {
          expect_equal(dim(ci.mat), c(2, 3))
          expect_equal(colnames(ci.mat), c("4.5%", "50%", "95.5%"))
        }
      })

      test_that("ci.coords accepts multiple x and ret", {
        skip_slow()
        obtained <- ci.coords(test.roc,
          x = c(0.9, 0.8), input = input, ret = c("sp", "ppv", "tp", "1-se"),
          boot.n = 3, conf.level = .91, boot.stratified = stratified
        )
        expect_equal(attr(obtained, "ret"), c("specificity", "ppv", "tp", "1-sensitivity"))
        expect_equal(names(obtained), attr(obtained, "ret"))
        for (ci.mat in obtained) {
          expect_equal(dim(ci.mat), c(2, 3))
          expect_equal(colnames(ci.mat), c("4.5%", "50%", "95.5%"))
        }
      })
    }
  }
}