R/proposePointsMSPOT.R

In mlr-org/mlrMBO: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions

proposePointsMSPOT = function(opt.state, ...) {

  opt.problem = getOptStateOptProblem(opt.state)
  models = getOptStateModels(opt.state)$models
  designs = getOptStateDesigns(opt.state)
  par.set = getOptProblemParSet(opt.problem)
  control = getOptProblemControl(opt.problem)
  opt.path = getOptStateOptPath(opt.state)
  iter = getOptStateLoop(opt.state)

  n = control$propose.points
  ch = checkFailedModels(models, par.set, n, control = control)
  if (!ch$ok)
    return(ch$prop)

  infill.crit.id = getMBOInfillCritId(control$infill.crit)
  infill.opt.fun = getInfillOptFunction(control$infill.opt)

  # store time to propose single point
  secs = measureTime({
    prop.points = infill.opt.fun(control$infill.crit$fun, models, control, par.set, opt.path, designs, iter, ...)
  })

  ppoints = prop.points$prop.points
  crit.vals = evalCritFunForMultiObjModels(control$infill.crit$fun, ppoints, models, control,
    par.set, designs, iter)
  crit.vals = cbind(crit.vals, prop.points$prop.hv.contrs)
  prop.type = rep(paste0("infill_", infill.crit.id), n)

  makeProposal(
    control = control,
    prop.points = ppoints,
    propose.time = secs,
    crit.vals = crit.vals,
    prop.type = prop.type
  )
}