# This test file validates the helper functions in utils.R, which are used for plotting.
# We check if the functions can be called with valid data without throwing an error.

# Load the testthat library for unit testing.
library(testthat)

# The plotting functions rely on these packages.
# They should be loaded for the tests to run.
library(lattice)
library(gridExtra)

# Create mock data that simulates the input for the plotting functions.
# This data mimics the structure of what the main plot methods would pass.
set.seed(123)
n <- 50
d <- 2
q <- 3

# Mock input data (X) and responses (y, Y)
X <- matrix(runif(n * d, -1, 1), ncol = d)
y_bin <- rbinom(n, 1, 0.5)
Y_multi <- t(sapply(1:n, function(i) rmultinom(1, size = 1, prob = c(0.2, 0.5, 0.3))))

# Mock grid data, simulating the output from a 'predict' function.
# This data contains columns for the plot's variables (e.g., Mean, Variance).
grid_data <- data.frame(
  x1 = runif(n),
  x2 = runif(n),
  Mean = runif(n),
  Upper = runif(n, 0.5, 1),
  Lower = runif(n, 0, 0.5),
  Variance = runif(n, 0, 0.1),
  class = max.col(Y_multi),
  max_prob = apply(Y_multi, 1, max)
)


test_that("my_2D_plot_fun generates plot without error", {
  # This test verifies that the function for binary/continuous plots runs correctly.
  expect_no_error({
    my_2D_plot_fun(
      var = "Mean",
      title = "Binary Predictive Mean Test",
      data = grid_data,
      X = X,
      y = y_bin
    )
  })
})


test_that("my_2D_plot_fun_class generates plot without error", {
  # This test verifies that the function for multiclass plots runs correctly.
  # It tests both classification and probability plotting modes.
  expect_no_error({
    # Test with multiclass classification data (classification = TRUE)
    my_2D_plot_fun_class(
      var = "class",
      title = "Multiclass Classification Test",
      data = grid_data,
      X = X,
      Y = Y_multi,
      classification = TRUE
    )
  })

  expect_no_error({
    # Test with multiclass probability data (classification = FALSE)
    my_2D_plot_fun_class(
      var = "max_prob",
      title = "Multiclass Max Probability Test",
      data = grid_data,
      X = X,
      Y = Y_multi,
      classification = FALSE
    )
  })
})