library(testthat)

# Simple test: check if the function runs on the given dataset and returns results
test_that("fit_and_plot_models works without errors", {
  # Use the built-in iris dataset for testing
  data(iris)

  # Create a simple formula to predict Species
  formula <- Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width

  # Call the fit_and_plot_models function and check that it does not error
  result <- fit_and_plot_models(iris, formula, ntree = 500)

  # Check that the returned value is a list containing prediction results
  expect_type(result, "list")
  expect_named(result, c("rf_predictions", "svm_predictions",
                         "decision_tree_predictions", "logistic_predictions"))

  # Check that predictions from each model are not empty
  expect_true(length(result$rf_predictions) > 0)
  expect_true(length(result$svm_predictions) > 0)
  expect_true(length(result$decision_tree_predictions) > 0)
  expect_true(length(result$logistic_predictions) > 0)
})