Nothing

```
# evals the points proposed by proposePoints
# (called by mboTemplate)
#
# @param opt.state
# @param prop: result of proposePoints
# @return [\code{numeric} | \code{matrix}] Numeric vector of y-vals or matrix
# (for multi-objective problems).
#
# gets the getExtras, converts point data.frame to a list, repairs points out-of-bounds
# then call evalTargetFun
evalProposedPoints.OptState = function(opt.state, prop, train.time = NULL) {
if (is.null(train.time)) {
train.time = getOptStateModels(opt.state)$train.time
}
opt.problem = getOptStateOptProblem(opt.state)
par.set = getOptProblemParSet(opt.problem)
extras = getExtras(
n = nrow(prop$prop.points),
prop = prop,
train.time = train.time,
control = getOptProblemControl(opt.problem)
)
xs = dfRowsToList(prop$prop.points, par.set)
xs = lapply(xs, repairPoint, par.set = par.set)
evalTargetFun.OptState(opt.state, xs = xs, extras = extras)
}
```

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