tests/testthat/test_AcqOptimizerLbfgsb.R

In mlr3mbo: Flexible Bayesian Optimization

test_that("AcqOptimizerLbfgsb works", {
  skip_if_missing_regr_km()
  instance = oi(OBJ_1D, terminator = trm("evals", n_evals = 5L))
  design = generate_design_grid(instance$search_space, resolution = 4L)$data
  instance$eval_batch(design)

  surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive)
  acqfun = acqf("ei", surrogate = surrogate)
  acqopt = AcqOptimizerLbfgsb$new(acq_function = acqfun)
  acqopt$param_set$set_values(maxeval = 200L, restart_strategy = "none")
  acqfun$surrogate$update()
  acqfun$update()

  expect_data_table(acqopt$optimize(), nrows = 1L)
  expect_list(acqopt$state)
  expect_names(names(acqopt$state), must.include = "iteration_1")
  expect_class(acqopt$state$iteration_1$model, "nloptr")
  expect_true(acqopt$state$iteration_1$model$iterations <= 200L)
})

test_that("AcqOptimizerLbfgsb works with 2D", {
  skip_if_missing_regr_km()
  instance = oi(OBJ_2D, terminator = trm("evals", n_evals = 5L))
  design = generate_design_grid(instance$search_space, resolution = 4L)$data
  instance$eval_batch(design)

  surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive)
  acqfun = acqf("ei", surrogate = surrogate)
  acqopt = AcqOptimizerLbfgsb$new(acq_function = acqfun)
  acqopt$param_set$set_values(maxeval = 200L)
  acqfun$surrogate$update()
  acqfun$update()

  expect_data_table(acqopt$optimize(), nrows = 1L)
  expect_list(acqopt$state)
  expect_names(names(acqopt$state), must.include = "iteration_1")
  expect_class(acqopt$state$iteration_1$model, "nloptr")
  expect_true(acqopt$state$iteration_1$model$iterations <= 200L)
})

test_that("AcqOptimizerLbfgsb works with instance", {
  skip_if_missing_regr_km()
  instance = oi(OBJ_1D, terminator = trm("evals", n_evals = 10L))
  design = generate_design_grid(instance$search_space, resolution = 4L)$data
  instance$eval_batch(design)

  surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive)
  acqfun = acqf("ei", surrogate = surrogate)
  acqopt = AcqOptimizerLbfgsb$new(acq_function = acqfun)
  acqopt$param_set$set_values(maxeval = 10L)

  optimizer = opt("mbo", acq_optimizer = acqopt, acq_function = acqfun, surrogate = surrogate)
  expect_data_table(optimizer$optimize(instance), nrows = 1L)
})

test_that("AcqOptimizerLbfgsb works with random restart", {
  skip_if_missing_regr_km()
  instance = oi(OBJ_2D, terminator = trm("evals", n_evals = 5L))
  design = generate_design_grid(instance$search_space, resolution = 4L)$data
  instance$eval_batch(design)

  surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive)
  acqfun = acqf("ei", surrogate = surrogate)
  acqopt = AcqOptimizerLbfgsb$new(acq_function = acqfun)
  acqopt$param_set$set_values(maxeval = -1, ftol_rel = 1e-6, restart_strategy = "random", max_restarts = 3L)
  acqfun$surrogate$update()
  acqfun$update()

  expect_data_table(acqopt$optimize(), nrows = 1L)
  expect_list(acqopt$state, min.len = 4L)
  expect_names(names(acqopt$state), must.include = c("iteration_1", "iteration_2", "iteration_3", "iteration_4"))
  walk(acqopt$state, function(x) expect_class(x$model, "nloptr"))
  expect_true(all(sapply(acqopt$state, function(x) x$model$iterations) <= 50L))
})