test_dataset.R

require(lightgbm)
require(Matrix)

context("testing lgb.Dataset functionality")

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

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')) == 0)
  expect_true(length(getinfo(dtest, 'init_score')) == 0)

  # 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, 1:42)
  lgb.Dataset.construct(dsub1)
  expect_equal(nrow(dsub1), 42)
  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(1: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 <- 1000
  x <- Matrix::rsparsematrix(nr, 100, 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(1000), ncol = 10)
  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))
})