Set termination options.

Extends an MBO control object with infill criteria and infill optimizer options.

setMBOControlTermination(
  control,
  iters = NULL,
  time.budget = NULL,
  exec.time.budget = NULL,
  target.fun.value = NULL,
  max.evals = NULL,
  more.termination.conds = list(),
  use.for.adaptive.infill = NULL
)

Arguments

control	[`MBOControl`] Control object for mbo.
iters	[`integer(1)`] Number of sequential optimization steps.
time.budget	[`numeric(1)` \| NULL] Running time budget in seconds. Note that the actual mbo run can take more time since the condition is checked after each iteration. The default `NULL` means: There is no time budget.
exec.time.budget	[`numeric(1)` \| NULL] Execution time (time spent executing the function passed to `mbo`) budget in seconds. Note that the actual mbo run can take more time since the condition is checked after each iteration. The default `NULL` means: There is no execution time budget.
target.fun.value	[`numeric(1)`] \| NULL] Termination criterion for single-objective optimization: Stop if a function evaluation is better than this given target.value. The default `NULL` means: The function value won't be taken into account for termination.
max.evals	[`integer(1) \| NULL`] Maximal number of function evaluations. The default `NULL` means: The total number of evaluations won't be taken into account for termination.
more.termination.conds	[`list`] Optional list of termination conditions. Each condition needs to be a function of a single argument `opt.state` of type `OptState` and should return a list with the following elements: term [`logical(1)`] Logical value indicating whether the termination condition is met. message [`character(1)`] Termination message. At the moment we just allow `term.custom`.
use.for.adaptive.infill	[`character(1)`\|NULL] Which termination criterion should determine the progress that is used for adaptive infill criteria like [`makeMBOInfillCritAdaCB`]. The default is `NULL` which means, that the first supplied argument is taken, following the order of the function signature. Other values can be `"iters"`, `"time.budget"`, etc. If you want to to use it together with a criterion you supplied in `more.termination.conds`, `more.termination.conds` has to be a named list and the function further has to return a list element `progress` with values between 0 and 1.

Value

[MBOControl].

Examples

fn = smoof::makeSphereFunction(1L)
ctrl = makeMBOControl()

# custom termination condition (stop if target function value reached)
# We neglect the optimization direction (min/max) in this example.
yTargetValueTerminator = function(y.val) {
  force(y.val)
  function(opt.state) {
    opt.path = opt.state$opt.path
    current.best = getOptPathEl(opt.path, getOptPathBestIndex((opt.path)))$y
    term = (current.best <= y.val)
    message = if (!term) NA_character_ else sprintf("Target function value %f reached.", y.val)
    return(list(term = term, message = message))
  }
}

# assign custom termination condition
ctrl = setMBOControlTermination(ctrl, more.termination.conds = list(yTargetValueTerminator(0.05)))
res = mbo(fn, control = ctrl)
#> Computing y column(s) for design. Not provided.
#> [mbo] 0: x=-3.7 : y = 13.7 : 0.0 secs : initdesign
#> [mbo] 0: x=2.08 : y = 4.33 : 0.0 secs : initdesign
#> [mbo] 0: x=-2.49 : y = 6.22 : 0.0 secs : initdesign
#> [mbo] 0: x=2.63 : y = 6.91 : 0.0 secs : initdesign
#> [mbo] 1: x=1.82 : y = 3.3 : 0.0 secs : infill_cb
#> [mbo] 2: x=0.955 : y = 0.912 : 0.0 secs : infill_cb
#> [mbo] 3: x=-0.385 : y = 0.148 : 0.0 secs : infill_cb
#> [mbo] 4: x=0.144 : y = 0.0206 : 0.0 secs : infill_cb
print(res)
#> Recommended parameters:
#> x=0.144
#> Objective: y = 0.021
#> 
#> Optimization path
#> 4 + 4 entries in total, displaying last 10 (or less):
#>            x           y dob eol error.message exec.time         cb error.model
#> 1 -3.6953594 13.65568112   0  NA          <NA>         0         NA        <NA>
#> 2  2.0814326  4.33236157   0  NA          <NA>         0         NA        <NA>
#> 3 -2.4934847  6.21746596   0  NA          <NA>         0         NA        <NA>
#> 4  2.6296002  6.91479717   0  NA          <NA>         0         NA        <NA>
#> 5  1.8167531  3.30059200   1  NA          <NA>         0  2.9284423        <NA>
#> 6  0.9548314  0.91170306   2  NA          <NA>         0  1.1170946        <NA>
#> 7 -0.3845713  0.14789507   3  NA          <NA>         0 -1.7860681        <NA>
#> 8  0.1436811  0.02064425   4  NA          <NA>         0 -0.4403414        <NA>
#>   train.time  prop.type propose.time        se       mean lambda
#> 1         NA initdesign           NA        NA         NA     NA
#> 2         NA initdesign           NA        NA         NA     NA
#> 3         NA initdesign           NA        NA         NA     NA
#> 4         NA initdesign           NA        NA         NA     NA
#> 5      0.039  infill_cb        0.212 2.4141499 5.34259219      1
#> 6      0.036  infill_cb        0.239 2.9398519 4.05694646      1
#> 7      0.096  infill_cb        0.231 2.0162487 0.23018064      1
#> 8      0.051  infill_cb        0.229 0.4823983 0.04205684      1

Arguments

Value

See also

Examples