tests/testthat/test_server_uploadOMLDataSet.R

In openml/openml-r: Open Machine Learning and Open Data Platform

# test_that("uploadOMLDataSet", {
#   # download a run and reupload it
#   with_test_cache({
#     ds = getOMLDataSet(10L)
#     mlr.task = convertOMLDataSetToMlr(ds)
# 
#     data.id = uploadOMLDataSet(ds)
#     expect_s3_class(data.id, "integer")
#     deleteOMLObject(data.id, object = "data")
# 
#     data.id = uploadOMLDataSet(mlr.task)
#     expect_s3_class(data.id, "integer")
#     deleteOMLObject(data.id, object = "data")
# 
#     # upload multilabel
#     ds$desc$target.features = ds$desc$default.target.attribute = c("bl_of_lymph_c", "bl_of_lymph_s")
#     ds$data$bl_of_lymph_c = as.logical(as.numeric(ds$data$bl_of_lymph_c) - 1)
#     ds$data$bl_of_lymph_s = as.logical(as.numeric(ds$data$bl_of_lymph_s) - 1)
#     data.id = uploadOMLDataSet(ds)
#     expect_s3_class(data.id, "integer")
#     deleteOMLObject(data.id, object = "data")
# 
#     # upload multivariate regression data
#     iris = getTaskData(iris.task)
#     desc = makeOMLDataSetDescription(
#       name = "iris",
#       description = "iris with ignored features Sepal.Width and Petal.Length",
#       default.target.attribute = c("Sepal.Width", "Petal.Length")
#     )
#     d = makeOMLDataSet(desc, data = iris)
#     did = uploadOMLDataSet(d)
#     expect_warning(d2 <- getOMLDataSet(did), "preparation") # nolint
# 
#     # upload data with multiple ignore attributes
#     iris = getTaskData(iris.task)
#     desc = makeOMLDataSetDescription(
#       name = "iris",
#       description = "iris with ignored features Sepal.Width and Petal.Length",
#       ignore.attribute = c("Sepal.Width", "Petal.Length"),
#       default.target.attribute = "Species"
#     )
#     d = makeOMLDataSet(desc, data = iris)
#     did = uploadOMLDataSet(d)
#     expect_warning(d2 <- getOMLDataSet(did), "preparation") # nolint
#     expect_s3_class(convertOMLDataSetToMlr(d2), "Task")
#   })
# })