tests/testthat/test_GitHub_issues.R

context("GitHub issues")

test_that("Issue 54 is fixed", {
  # NOTE: This is a slow-ish test, so don't test when running tests with small
  #       block size.
  skip_if(getAutoBlockSize() == 8)

  # Small normal matrix
  m1 <- DelayedArray(as.matrix(iris[, 1:4]))
  expect_equal(
    rowsum(as.matrix(m1), iris$Species),
    rowsum(m1, iris$Species))

  # Large sparse matrix
  x <- Matrix::rsparsematrix(800000, ncol = 50, density = 0.1)

  # Large normal matrix
  m2 <- DelayedArray(as.matrix(x))
  S <- sample(1:1000, nrow(m2), replace = TRUE)
  expect_equal(
    rowsum(as.matrix(m2), S),
    rowsum(m2, S))

  # dgCMatrix
  m4 <- DelayedArray(x)
  S <- sample(1:1000, nrow(m4), replace = TRUE)
  expect_equal(
    rowsum(as.matrix(m4), S),
    rowsum(m4, S))

  # RleMatrix
  # NOTE: This test fails on 32-bit Windows because it can't allocate a ~150 Mb
  #       vector.
  skip_on_os("windows")
  m3 <- as(m2, "RleMatrix")
  S <- sample(1:1000, nrow(m3), replace = TRUE)
  expect_equal(
    rowsum(as.matrix(m3), S),
    rowsum(m3, S)
  )
})
PeteHaitch/DelayedMatrixStats documentation built on May 6, 2024, 10:25 p.m.