Nothing
context("Base: Print Feature Object")
test_that("FeatureObject Output", {
feat.object = createFeatureObject(iris, objective = "Species")
expect_output(print(feat.object), regexp = paste(
"^Feature Object:",
"- Number of Observations:\\s\\d+",
"- Number of Variables:\\s\\d+",
"- Lower Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Upper Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Name of Variables: [^,\\s]*(, [^,\\s]*)*",
"- Optimization Problem: (minimize|maximize) [^\\s]+?",
sep="\\r?\\n")
)
})
test_that("FeatureObject Output with more than 5 feature dims", {
init = matrix(1, ncol=6, nrow=2)
colnames(init) = c("a1", "a2", "a3", "a4", "a5", "a6")
feat.object = createFeatureObject(init, objective = "a6")
expect_output(print(feat.object), regexp = paste(
"- Lower Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*, ...",
"- Upper Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*, ...",
"- Name of Variables: [^,\\s]*(, [^,\\s]*)*, ...",
sep="\\r?\\n")
)
})
test_that("FeatureObject Output with a function", {
init = matrix(1L, ncol = 6L, nrow = 2L)
colnames(init) = c("a1", "a2", "a3", "a4", "a5", "a6")
feat.object = createFeatureObject(init, objective = "a6", fun = function (x) sum(x^2))
expect_output(print(feat.object),
regexp = "- Function to be Optimized: function \\(x\\) sum\\(x\\^2\\)")
})
test_that("FeatureObject Output with cellmapping and dim < 5", {
init = matrix(1:10, ncol = 5L, nrow = 10L)
colnames(init) = c("a1", "a2", "a3", "a4", "a5")
feat.object = createFeatureObject(init, objective = "a5", blocks = 4L)
expect_output(print(feat.object), regexp = paste(
"- Number of Cells per Dimension: \\d+(, \\d+)*",
"- Size of Cells per Dimension: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Number of Cells:",
"\\s+- total: \\d+",
"\\s+- non-empty: \\d+ \\([0-9e+-.]+%\\)",
"\\s+- empty: \\d+ \\([0-9e+-.]+%\\)",
"- Average Number of Observations per Cell:",
"\\s+- total: [0-9e+-.]+",
"\\s+- non-empty: [0-9e+-.]+",
sep="\\r?\\n")
)
})
test_that("FeatureObject Output with cellmapping and dim >= 5", {
init = matrix(1:10, ncol = 6L, nrow = 10L)
colnames(init) = c("a1", "a2", "a3", "a4", "a5", "a6")
feat.object = createFeatureObject(init, objective = "a6", blocks = 4L)
expect_output(print(feat.object), regexp=paste(
"- Number of Cells per Dimension: \\d+(, \\d+)*, ...",
"- Size of Cells per Dimension: [0-9e+.-]+(, [0-9e+-.]+)*, ...",
sep="\\r?\\n")
)
})
test_that("Usage of regular and smoof functions", {
X = createInitialSample(n.obs = 200, dim = 2)
f1 = smoof::makeBBOBFunction(dimension = 2, fid = 23, iid = 1)
f2 = function(x) sum(x^2 * sin(x^3))
y1 = apply(X, 1, f1)
y2 = apply(X, 1, f2)
feat.object1 = createFeatureObject(X = X, y = y1, fun = f1)
feat.object2 = createFeatureObject(X = X, y = y2, fun = f2)
expect_output(print(feat.object1), regexp = paste(
"^Feature Object:",
"- Number of Observations:\\s\\d+",
"- Number of Variables:\\s\\d+",
"- Lower Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Upper Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Name of Variables: [^,\\s]*(, [^,\\s]*)*",
"- Optimization Problem: (minimize|maximize) [^\\s]+?",
"- Function to be Optimized: smoof-function [(BBOB)]+?",
sep="\\r?\\n")
)
expect_output(print(feat.object2), regexp = paste(
"^Feature Object:",
"- Number of Observations:\\s\\d+",
"- Number of Variables:\\s\\d+",
"- Lower Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Upper Boundaries: [0-9e+.-]+(, [0-9e+-.]+)*",
"- Name of Variables: [^,\\s]*(, [^,\\s]*)*",
"- Optimization Problem: (minimize|maximize) [^\\s]+?",
"- Function to be Optimized: function [\\s]*",
sep="\\r?\\n")
)
})
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