tests/testthat/test_parallel.R

In kridsadakorn/ipcaps.bioc: Iterative Pruning to Capture Population Structure

context("test diff.xy")

test_that("test diff.xy", {
    res <- diff.xy(2.4, 6.7)
    expect_equal(res, (6.7 - 2.4))

    res <- diff.xy(8.23, 3.5)
    expect_equal(res, (8.23 - 3.5))

    res <- diff.xy(4.3, 4.3)
    expect_equal(res, (4.3 - 4.3))

})



context("test cal.eigen.fit")

test_that("test cal.eigen.fit", {
    X <-
        c(
            2.7668157,
            1.8931580,
            1.8859049,
            1.0575971,
            1.0329016,
            0.9095669,
            0.6395215,
            0.5073142,
            0.3205904,
            0.3125665
        )

    res <- cal.eigen.fit(X)

    expected_vec <-
        c(
            0.379450739,
            0.003838584,
            0.578408288,
            0.023627539,
            0.127158683,
            0.352248264,
            0.231589695,
            0.458966294,
            0.025346914
        )

    expect_length(res, 9)
    expect_equal(round(res, 5), round(expected_vec, 5))
    expect_type(res, "double")

})



context("test diff.eigen.fit")

test_that("test diff.eigen.fit", {
    X <-
        sort(
            c(
                2.7668157,
                1.8931580,
                1.8859049,
                1.0575971,
                1.0329016,
                0.9095669,
                0.6395215,
                0.5073142,
                0.3205904,
                0.3125665
            ),
            decreasing = TRUE
        )

    res <- diff.eigen.fit(X)

    expected_vec <- c(-0.9690304, -5.5626540, -0.5474752, -3.7453432)

    expect_length(res, 4)
    expect_equal(round(res, 5), round(expected_vec, 5))
    expect_type(res, "double")

})



context("test do.glm")

test_that("test do.glm", {
    PC <- matrix(runif(300, min = 0, max = 3), ncol = 3)
    X <- sample(c(0, 1, 2), size = 100, replace = TRUE)

    method <- "linear"
    res <- do.glm(X, PC, method)
    expect_length(res, 100)
    expect_type(res, "double")

    method <- "poisson"
    res <- do.glm(X, PC, method)
    expect_length(res, 100)
    expect_type(res, "double")

    # method <- "negative.binomial"
    # res <- do.glm(X,PC,method)
    # expect_length(res,100)
    # expect_type(res, "double")

})



context("test replace.missing")

test_that("test replace.missing", {
    X <- runif(20, min = 0, max = 3)
    X[c(2, 4, 8, 13, 17)] <- NA
    missing.char <- NA
    replace.char <- rep(0, 20)
    res <- replace.missing(X, missing.char, replace.char)
    expect_length(res, 20)
    expect_type(res, "double")

})