test_that("read and write json works", {
  skip_if_not_installed("recipes")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("workflows")
  rec_spec <- recipes::recipe(mpg ~ ., data = mtcars) |>
    recipes::step_normalize(recipes::all_numeric_predictors())

  lm_spec <- parsnip::linear_reg()

  wf_spec <- workflows::workflow(rec_spec, lm_spec)

  wf_fit <- parsnip::fit(wf_spec, mtcars)

  orbital_obj <- orbital(wf_fit)

  tmp_file <- tempfile()

  orbital_json_write(orbital_obj, tmp_file)

  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("read and write json works - backwards from version 1", {
  skip_if_not_installed("recipes")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("workflows")
  rec_spec <- recipes::recipe(mpg ~ ., data = mtcars) |>
    recipes::step_normalize(recipes::all_numeric_predictors())

  lm_spec <- parsnip::linear_reg()

  wf_spec <- workflows::workflow(rec_spec, lm_spec)

  wf_fit <- parsnip::fit(wf_spec, mtcars)

  orbital_obj <- orbital(wf_fit)

  tmp_file <- tempfile()

  orbital_json_write(orbital_obj, tmp_file)

  # Fake version 1
  fake_json <- jsonlite::read_json(tmp_file)
  fake_json$pred_names <- NULL
  fake_json$version <- 1
  fake_json <- jsonlite::toJSON(fake_json, pretty = TRUE, auto_unbox = TRUE)
  writeLines(fake_json, tmp_file)

  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("json round-trip works for glmnet classification", {
  skip_if_not_installed("parsnip")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("glmnet")

  mtcars$vs <- factor(mtcars$vs)
  spec <- parsnip::logistic_reg(penalty = 0.01, engine = "glmnet")
  fit <- parsnip::fit(spec, vs ~ disp + mpg + hp, mtcars)

  orbital_obj <- orbital(fit, type = c("class", "prob"))

  tmp_file <- tempfile()
  orbital_json_write(orbital_obj, tmp_file)
  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("json round-trip works for glmnet multiclass", {
  skip_if_not_installed("parsnip")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("glmnet")

  spec <- parsnip::multinom_reg(penalty = 0.01, engine = "glmnet")
  fit <- parsnip::fit(spec, Species ~ ., iris)

  orbital_obj <- orbital(fit, type = c("class", "prob"))

  tmp_file <- tempfile()
  orbital_json_write(orbital_obj, tmp_file)
  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("json round-trip works for earth classification", {
  skip_if_not_installed("parsnip")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("earth")

  mtcars$vs <- factor(mtcars$vs)
  spec <- parsnip::mars(mode = "classification", engine = "earth")

  suppressWarnings(
    fit <- parsnip::fit(spec, vs ~ disp + mpg + hp, mtcars)
  )

  orbital_obj <- orbital(fit, type = c("class", "prob"))

  tmp_file <- tempfile()
  orbital_json_write(orbital_obj, tmp_file)
  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("json round-trip works for randomForest classification", {
  skip_if_not_installed("parsnip")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("randomForest")

  mtcars$vs <- factor(mtcars$vs)
  spec <- parsnip::rand_forest(
    trees = 5,
    mode = "classification",
    engine = "randomForest"
  )

  set.seed(123)
  fit <- parsnip::fit(spec, vs ~ disp + mpg + hp, mtcars)

  orbital_obj <- orbital(fit, type = c("class", "prob"))

  tmp_file <- tempfile()
  orbital_json_write(orbital_obj, tmp_file)
  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})

test_that("json round-trip works for ranger classification", {
  skip_if_not_installed("parsnip")
  skip_if_not_installed("tidypredict")
  skip_if_not_installed("jsonlite")
  skip_if_not_installed("ranger")

  mtcars$vs <- factor(mtcars$vs)
  spec <- parsnip::rand_forest(
    trees = 5,
    mode = "classification",
    engine = "ranger"
  )

  set.seed(123)
  fit <- parsnip::fit(spec, vs ~ disp + mpg + hp, mtcars)

  orbital_obj <- orbital(fit, type = c("class", "prob"))

  tmp_file <- tempfile()
  orbital_json_write(orbital_obj, tmp_file)
  new <- orbital_json_read(tmp_file)

  expect_identical(new, orbital_obj)
})