if (interactive()) {

  context("Binder tests, part 1")

  # Defining the relative path to current inst ---------------------------------

  notebook_data_path <- system.file("notebook", package = "DIscBIO")

  FileName <- "CTCdataset"

  load(file.path(notebook_data_path, paste0(FileName, ".rda")))

  load(file.path(notebook_data_path, "SC.RData"))

  load(file.path(notebook_data_path, "Ndata.RData"))

  load(file.path(notebook_data_path, "expdata.RData"))

  DataSet <- get(FileName)

  test_that("Loading CTC dataset", {

    expect_equal(length(DataSet[, 1]), 13181)

    expect_equal(length(DataSet[1, ]), 1462)

  })

  sc <- DISCBIO(DataSet)

  S1 <- summary(colSums(DataSet, na.rm = TRUE))

  S2 <- summary(rowMeans(DataSet, na.rm = TRUE))

  minexpr <- S2[3]

  minnumber <- round(length(DataSet[1, ]) / 10)

  test_that("Handling datasets", {

    expect_true(is(sc, "DISCBIO"))

    expect_output(str(S1), " 'summaryDefault' Named num")

    expect_equal(minnumber, 146)

  })

  sc <- Normalizedata(

    sc,

    minexpr = minexpr, minnumber = minnumber, rseed = 17000

  )

  sc <- suppressMessages(FinalPreprocessing(sc, GeneFlitering = "ExpF"))

  sc <- SC

  sc@ndata <- Ndata

  sc@expdata <- expdata

  # Removing the unneeded objects

  rm(Ndata)

  rm(expdata)

  rm(DataSet)

  rm(SC)

  gc()

  long_test <- FALSE # switching to true runs slow tests below

  if (long_test) {

    sc <- Clustexp(sc, 4, bootnr = 2, B.gap = 2, quiet = TRUE, rseed = 17000)

    outlg <- round(length(sc@fdata[, 1]) * 0.05)

    Outliers <- FindOutliers(sc, 4, outlg = outlg, plot = FALSE, quiet = TRUE)

    jcrd <- Jaccard(sc, K = 4, plot = FALSE, R = 2)

    sc <- pseudoTimeOrdering(sc, quiet = TRUE)

    test_that("Post-processing", {

      expect_equivalent(jcrd, c(.422, .649, .335, .605))

      expect_output(

        object = str(sc, max.level = 1),

        expected = 'Formal class \'DISCBIO\' [package "DIscBIO"] with 21 slots'

      )

    })

  }

}