test_that(
 desc = "orsf_vint orders interactions correctly for requested predictors",
 code = {
  skip_on_cran()
  set.seed(329)
  n <- 100
  data <- data.frame(
   x1 = rnorm(100),
   x2 = rnorm(100),
   x3 = rnorm(100)
  )
  data$y = with(data, expr = x1 + x2 + x3 + 1/2*x1*x2 + x2*x3 + rnorm(n))
  forest <- orsf(data, y ~ ., n_tree = 100)
  vints_1 <- orsf_vint(forest)
  vints_2 <- orsf_vint(forest, predictors = c("x1", "x3"))
  expect_equal(vints_1$interaction[1], "x2..x3")
  expect_equal(vints_1$interaction[2], "x1..x2")
  expect_equal(vints_1$interaction[3], "x1..x3")
  expect_equal(nrow(vints_2), 1)
  expect_equal(vints_2$score,
               vints_1$score[vints_1$interaction == 'x1..x3'])
 }
)
test_that(
 desc = "vint succeeds on categorical forests",
 code = {
  skip_on_cran()
  fit <- orsf(species ~ ., data = penguins_orsf)
  vints <- orsf_vint(fit)
  expect_true(all(levels(penguins_orsf$species) %in% vints$class))
  penguins_bnry <- penguins_orsf
  penguins_bnry$species <- factor(penguins_bnry$species == "Adelie",
                                  levels = c(FALSE, TRUE),
                                  labels = c("Other", "adelie"))
  fit <- orsf(species ~ ., data = penguins_bnry)
  vints <- orsf_vint(fit)
  expect_true(all(levels(penguins_bnry$species) %in% vints$class))
 }
)
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