Nothing
context("adaptive infill crits")
test_that("adaptive infill crit works with all termination criteria", {
f = testf.fsphere.1d
f.slow = testf.fsphere.1d.slow
f.max = convertToMaximization(f)
design = testd.fsphere.1d
design.max = design
design$y = apply(design, 1, f)
design.max$y = apply(design.max, 1, f.max)
terminations = list(
iters = list(iters = 4L),
time.budget = list(time.budget = 2),
exec.time.budget = list(exec.time.budget = 1.5, iters = 13, use.for.adaptive.infill = "exec.time.budget"),
target.fun.value = list(target.fun.value = min(design$y)/3, iters = 13, use.for.adaptive.infill = "target.fun.value"),
target.fun.value.max = list(target.fun.value = max(design.max$y)/3, iters = 13, use.for.adaptive.infill = "target.fun.value"),
max.evals = list(max.evals = nrow(design) + 4L)
)
ctrl = makeMBOControl()
ctrl = setMBOControlInfill(ctrl, crit = makeMBOInfillCritAdaCB())
for (i in names(terminations)) {
ctrl2 = do.call(setMBOControlTermination, c(list(control = ctrl), terminations[[i]]))
if (i == "exec.time.budget") {
fun = f.slow
des = design
} else if (i == "target.fun.value.max") {
fun = f.max
des = design.max
} else {
fun = f
des = design
}
or = mbo(fun, des, control = ctrl2)
expect_number(or$y, info = i)
df = as.data.frame(or$opt.path)
expect_true(any(df$lambda > 1), info = i)
expect_true(length(unique(df$lambda)) >= 2, info = i)
expect_true(all(diff(df$lambda[!is.na(df$lambda)])<=0), info = i)
expect_true(all(df$prop.type %in% c("infill_adacb", "initdesign")), info = i)
expect_numeric(df$adacb, info = i)
}
})
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