test_dataset.R

require(lightgbm)
require(Matrix)

context("testing lgb.Dataset functionality")

data(agaricus.test, package = "lightgbm")
test_data <- agaricus.test$data[1L:100L, ]
test_label <- agaricus.test$label[1L:100L]

test_that("lgb.Dataset: basic construction, saving, loading", {
  # from sparse matrix
  dtest1 <- lgb.Dataset(test_data, label = test_label)
  # from dense matrix
  dtest2 <- lgb.Dataset(as.matrix(test_data), label = test_label)
  expect_equal(getinfo(dtest1, "label"), getinfo(dtest2, "label"))

  # save to a local file
  tmp_file <- tempfile("lgb.Dataset_")
  lgb.Dataset.save(dtest1, tmp_file)
  # read from a local file
  dtest3 <- lgb.Dataset(tmp_file)
  lgb.Dataset.construct(dtest3)
  unlink(tmp_file)
  expect_equal(getinfo(dtest1, "label"), getinfo(dtest3, "label"))
})

test_that("lgb.Dataset: getinfo & setinfo", {
  dtest <- lgb.Dataset(test_data)
  dtest$construct()

  setinfo(dtest, "label", test_label)
  labels <- getinfo(dtest, "label")
  expect_equal(test_label, getinfo(dtest, "label"))

  expect_true(length(getinfo(dtest, "weight")) == 0L)
  expect_true(length(getinfo(dtest, "init_score")) == 0L)

  # any other label should error
  expect_error(setinfo(dtest, "asdf", test_label))
})

test_that("lgb.Dataset: slice, dim", {
  dtest <- lgb.Dataset(test_data, label = test_label)
  lgb.Dataset.construct(dtest)
  expect_equal(dim(dtest), dim(test_data))
  dsub1 <- slice(dtest, seq_len(42L))
  lgb.Dataset.construct(dsub1)
  expect_equal(nrow(dsub1), 42L)
  expect_equal(ncol(dsub1), ncol(test_data))
})

test_that("lgb.Dataset: colnames", {
  dtest <- lgb.Dataset(test_data, label = test_label)
  expect_equal(colnames(dtest), colnames(test_data))
  lgb.Dataset.construct(dtest)
  expect_equal(colnames(dtest), colnames(test_data))
  expect_error({
    colnames(dtest) <- "asdf"
  })
  new_names <- make.names(seq_len(ncol(test_data)))
  expect_silent(colnames(dtest) <- new_names)
  expect_equal(colnames(dtest), new_names)
})

test_that("lgb.Dataset: nrow is correct for a very sparse matrix", {
  nr <- 1000L
  x <- Matrix::rsparsematrix(nr, 100L, density = 0.0005)
  # we want it very sparse, so that last rows are empty
  expect_lt(max(x@i), nr)
  dtest <- lgb.Dataset(x)
  expect_equal(dim(dtest), dim(x))
})

test_that("lgb.Dataset: Dataset should be able to construct from matrix and return non-null handle", {
  rawData <- matrix(runif(1000L), ncol = 10L)
  handle <- NA_real_
  ref_handle <- NULL
  handle <- lightgbm:::lgb.call(
    "LGBM_DatasetCreateFromMat_R"
    , ret = handle
    , rawData
    , nrow(rawData)
    , ncol(rawData)
    , lightgbm:::lgb.params2str(params = list())
    , ref_handle
  )
  expect_false(is.na(handle))
})