tests/testthat/test-balanced_cv.R

In sysbiomed/glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

context("Balanced cv folds")

test_that("Only one set", {
    set1 <- c(
        TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE,
        TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE
    )
    result <- balancedCvFolds(set1, nfolds = 10)

    result$train |>
        checkmate::expect_list() |>
        expect_failure()
    result$test |>
        checkmate::expect_list() |>
        expect_failure()
})

test_that("Creates nice cv folds", {
    result <- balancedCvFolds(seq(10), 1:3, nfolds = 2)
    #
    resultC <- table(result$output[[1]])
    expect_equal(length(resultC), 2)
    expect_equal(as.vector(resultC), c(5, 5))
    #
    resultC <- table(result$output[[2]])
    expect_equal(length(resultC), 2)
    expect_equal(as.vector(resultC), c(2, 1))
    #
    #
    result <- balancedCvFolds(seq(10), 1:3, nfolds = 3)
    #
    resultC <- table(result$output[[1]])
    expect_equal(length(resultC), 3)
    expect_equal(as.vector(resultC), c(4, 3, 3))
    #
    resultC <- table(result$output[[2]])
    expect_equal(length(resultC), 3)
    expect_equal(as.vector(resultC), c(1, 1, 1))
    #
    expect_warning(
        balancedCvFolds(seq(10), 1:3, nfolds = 10),
        paste0(
            "Number of elements in vector [(][0-9]+[)] is",
            " less than 'nfolds' [(][0-9]+[)]"
        )
    )
})