tests/testthat/test_clusteringmode.R

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

context("test clustering.mode")

test_that("test clustering.mode", {
    PCs <- matrix(runif(300), byrow = TRUE, ncol = 3)
    node <- 0
    no.significant.PC <- 3
    workdir <- tempdir()

    #Interrupt the regular workflow in order to test the function
    targetdir <- file.path(workdir, "RData")
    if (!dir.exists(targetdir)) {
        dir.create(targetdir)
    }

    file1 <- file.path(workdir, "RData", "node0.RData")
    save(PCs,
         node,
         no.significant.PC,
         file = file1,
         compress = "bzip2")

    res <-
        clustering.mode(node, workdir, "clara", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "integer")

    res <- clustering.mode(node, workdir, "pam", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "integer")

    res <-
        clustering.mode(node, workdir, "mixmod", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "double")

    res <-
        clustering.mode(node, workdir, "meanshift", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "double")

    res <-
        clustering.mode(node, workdir, "apcluster", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "double")

    res <-
        clustering.mode(node, workdir, "hclust", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "integer")

    res <-
        clustering.mode(node, workdir, "rubikclust", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "double")

    res <- clustering.mode(node, workdir, "mix", silence.mode = TRUE)
    expect_length(res, 100)
    expect_type(res, "double")

    file.remove(file1)
    file.remove(targetdir)
})