context("filter proposed points")
test_that("filter proposed points", {
lrn = makeLearner("regr.km", predict.type = "se")
# now check min dist, set to "inf" so we always replace
ctrl = makeMBOControl(propose.points = 2L)
ctrl = setMBOControlTermination(ctrl, iters = 1L)
ctrl = setMBOControlInfill(ctrl, crit = crit.cb1,
filter.proposed.points = TRUE, filter.proposed.points.tol = 1000,
opt = "focussearch", opt.focussearch.points = 100L, opt.focussearch.maxit = 1L)
ctrl = setMBOControlMultiPoint(ctrl, method = "cb")
res = mbo(testf.fsphere.1d, testd.fsphere.1d, learner = lrn, control = ctrl)
op = as.data.frame(res$opt.path)
expect_true(all(op$prop.type[seq_row(testd.fsphere.1d)] != "random_filter"))
expect_true(all(op$prop.type[-seq_row(testd.fsphere.1d)] == "random_filter"))
})
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