Nothing
library(mlr)
context("Features: ELA - Levelset")
checkLevelOutput = function(features) {
# test return values
expect_identical(length(features), 20L)
expect_list(features)
expect_identical(as.character(sapply(features, class)),
c(rep("numeric", 18L), "integer", "numeric"))
expect_true(testNumber(features$ela_level.mmce_lda_10, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_qda_10, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_mda_10, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.lda_qda_10, lower = 0L))
expect_true(testNumber(features$ela_level.lda_mda_10, lower = 0L))
expect_true(testNumber(features$ela_level.qda_mda_10, lower = 0L))
expect_true(testNumber(features$ela_level.mmce_lda_25, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_qda_25, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_mda_25, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.lda_qda_25, lower = 0L))
expect_true(testNumber(features$ela_level.lda_mda_25, lower = 0L))
expect_true(testNumber(features$ela_level.qda_mda_25, lower = 0L))
expect_true(testNumber(features$ela_level.mmce_lda_50, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_qda_50, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.mmce_mda_50, lower = 0L, upper = 1L))
expect_true(testNumber(features$ela_level.lda_qda_50, lower = 0L))
expect_true(testNumber(features$ela_level.lda_mda_50, lower = 0L))
expect_true(testNumber(features$ela_level.qda_mda_50, lower = 0L))
expect_identical(features$ela_level.costs_fun_evals, 0L)
expect_true(testNumber(features$ela_level.costs_runtime, lower = 0L))
}
test_that("Expected Output", {
set.seed(2015*03*26)
# (1) create a feature object:
X = t(replicate(n = 2000L, expr = runif(n = 5L, min = -10L, max = 10L)))
feat.object = createFeatureObject(X = X, fun = function(x) sum(x^2))
# (2) compute the levelset features
features = calculateFeatureSet(feat.object, "ela_level")
checkLevelOutput(features)
# (3) compute only a single levelset feature
features = calculateFeatureSet(feat.object, "ela_level",
control = list(ela_level.quantiles = 0.1, ela_level.classif_methods = "lda"))
expect_list(features, types = "numeric", any.missing = FALSE, len = 3L)
})
test_that("Expect Warning", {
feat.object = createFeatureObject(init = iris[,-5], objective = "Petal.Width")
expect_warning(calculateFeatureSet(feat.object, "ela_level",
control = list(ela_level.quantiles = 0.05, ela_level.classif_methods = "lda"))
)
feat.object = createFeatureObject(X = iris[,1:3], y = iris[,4])
expect_warning(calculateFeatureSet(feat.object, "ela_level",
control = list(ela_level.quantiles = 0.1, ela_level.classif_methods = "qda"))
)
})
test_that("Parallelization", {
X = replicate(5, runif(2000))
f = smoof::makeBBOBFunction(dimension = 5, fid = 20, iid = 1)
y = apply(X, 1, f)
feat.object = createFeatureObject(X = X, y = y)
feats = calculateFeatureSet(feat.object, "ela_level",
control = list(ela_level.parallelize = TRUE))
checkLevelOutput(feats)
})
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