#-------------------------------------------------------------------------------
# Copyright (c) 2019-2022 University of Newcastle upon Tyne. All rights reserved.
# Copyright (c) 2022 Arjuna Technologies, Newcastle upon Tyne. All rights reserved.
#
# This program and the accompanying materials
# are made available under the terms of the GNU Public License v3.0.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#-------------------------------------------------------------------------------
#
# Set up
#
context("ds.listClientsideFunctions::smk::setup")
connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_HDL"))
test_that("setup", {
ds_expect_variables(c("D"))
})
#
# Tests
#
context("ds.listClientsideFunctions::smk::check results")
test_that("check results", {
output <- list(
"ds.abs",
"ds.asCharacter",
"ds.asDataMatrix",
"ds.asFactor",
"ds.asFactorSimple",
"ds.asInteger",
"ds.asList",
"ds.asLogical",
"ds.asMatrix",
"ds.asNumeric",
"ds.assign",
"ds.Boole",
"ds.boxPlot",
"ds.c",
"ds.cbind",
"ds.changeRefGroup",
"ds.class",
"ds.colnames",
"ds.completeCases",
"ds.contourPlot",
"ds.cor",
"ds.corTest",
"ds.cov",
"ds.dataFrame",
"ds.dataFrameFill",
"ds.dataFrameSort",
"ds.dataFrameSubset",
"ds.densityGrid",
"ds.dim",
"ds.dmtC2S",
"ds.elspline",
"ds.exists",
"ds.exp",
"ds.forestplot",
"ds.getWGSR",
"ds.glm",
"ds.glmerSLMA",
"ds.glmPredict",
"ds.glmSLMA",
"ds.glmSummary",
"ds.heatmapPlot",
"ds.hetcor",
"ds.histogram",
"ds.isNA",
"ds.isValid",
"ds.kurtosis",
"ds.length",
"ds.levels",
"ds.lexis",
"ds.list",
"ds.listClientsideFunctions",
"ds.listDisclosureSettings",
"ds.listOpals",
"ds.listServersideFunctions",
"ds.lmerSLMA",
"ds.log",
"ds.look",
"ds.ls",
"ds.lspline",
"ds.make",
"ds.matrix",
"ds.matrixDet",
"ds.matrixDet.report",
"ds.matrixDiag",
"ds.matrixDimnames",
"ds.matrixInvert",
"ds.matrixMult",
"ds.matrixTranspose",
"ds.mean",
"ds.meanByClass",
"ds.meanSdGp",
"ds.merge",
"ds.message",
"ds.metadata",
"ds.names",
"ds.numNA",
"ds.qlspline",
"ds.quantileMean",
"ds.ranksSecure",
"ds.rbind",
"ds.rBinom",
"ds.recodeLevels",
"ds.recodeValues",
"ds.rep",
"ds.replaceNA",
"ds.reShape",
"ds.rm",
"ds.rNorm",
"ds.rowColCalc",
"ds.rPois",
"ds.rUnif",
"ds.sample",
"ds.scatterPlot",
"ds.seq",
"ds.setDefaultOpals",
"ds.setSeed",
"ds.skewness",
"ds.sqrt",
"ds.subset",
"ds.subsetByClass",
"ds.summary",
"ds.table",
"ds.table1D",
"ds.table2D",
"ds.tapply",
"ds.tapply.assign",
"ds.testObjExists",
"ds.unique",
"ds.unList",
"ds.var",
"ds.vectorCalc"
)
expect_output(res <- ds.listClientsideFunctions(), "*")
for (func.name in output) {
expect_true(func.name %in% res, info = func.name)
}
})
#
# Done
#
context("ds.listClientsideFunctions::smk::shutdown")
test_that("shutdown", {
ds_expect_variables(c("D"))
})
disconnect.studies.dataset.cnsim()
context("ds.listClientsideFunctions::smk::done")
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