Nothing
library(testthat)
# Create a simple dummy predictors dataset for testing
set.seed(42)
n_obs <- 100
df <- data.frame(
target_series = cumsum(rnorm(n_obs)),
predictor1 = cumsum(rnorm(n_obs)),
predictor2 = cumsum(rnorm(n_obs))
)
# Test for search method "none"
test_that("xpect with 'none' search returns expected structure", {
result <- xpect(predictors = df,
target = "target_series",
future = 2,
search = "none",
seed = 123)
# Expect the result to be a list with the required components.
expect_true(is.list(result))
expect_true(is.na(result$history))
expect_true(is.na(result$best_params))
expect_true(is.list(result$best_model))
expect_s3_class(result$plot, "ggplot")
expect_true(!is.null(result$time_log))
})
# Test for search method "random_search"
test_that("xpect with 'random_search' returns expected structure", {
result <- xpect(predictors = df,
target = "target_series",
future = 2,
past = 5L,
lambda = NULL,
eta = c(0.01, 0.05),
search = "random_search",
n_samples = 3, # small sample size for test speed
seed = 123)
expect_true(is.list(result))
expect_true(is.data.frame(result$history))
expect_true(all(!is.na(result$best_params)))
expect_true(is.list(result$best_model))
expect_s3_class(result$plot, "ggplot")
})
# Test for search method "bayesian"
test_that("xpect with 'bayesian' search returns expected structure", {
result <- xpect(predictors = df,
target = "target_series",
future = 2,
past = 5,
lambda = NULL,
eta = c(0.01, 0.05),
search = "bayesian",
n_samples = 5, # initial sampling points
n_exploration = 1, # number of exploratory evaluations
seed = 123)
expect_true(is.list(result))
expect_true(is.data.frame(result$history))
expect_true(all(!is.na(result$best_params)))
expect_true(is.list(result$best_model))
expect_s3_class(result$plot, "ggplot")
})
test_that("xpect with 'coarse_to_fine' search returns expected structure", {
# Note: Ensure top_k is less than or equal to n_samples.
result <- xpect(predictors = df,
target = "target_series",
future = 2,
past = 5L,
lambda = NULL,
eta = c(0.01, 0.05),
search = "coarse_to_fine",
n_samples = 3,
n_phases = 2,
top_k = 2,
seed = 123)
expect_true(is.list(result))
expect_true(is.data.frame(result$history))
expect_true(all(!is.na(result$best_params)))
expect_true(is.list(result$best_model))
expect_s3_class(result$plot, "ggplot")
})
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