Container around a data.table::data.table which stores all performed function calls of the Objective.
The data is stored in a private .data field that contains a
data.table::data.table which logs all performed function calls of the Objective.
This data.table::data.table is accessed with the public $data() method. New
values can be added with the $add_evals() method. This however is usually
done through the evaluation of the OptimInstance by the Optimizer.
search_space(paradox::ParamSet) Search space of objective.
codomain(paradox::ParamSet) Codomain of objective function.
start_time(POSIXct).
check_values(logical(1))
n_evals(integer(1))
Number of evaluations stored in the archive.
n_batch(integer(1))
Number of batches stored in the archive.
cols_x(character()).
Column names of search space parameters.
cols_y(character()).
Column names of codomain parameters.
new()Creates a new instance of this R6 class.
Archive$new(search_space, codomain, check_values = TRUE)
search_space(paradox::ParamSet)
Specifies the search space for the Optimizer.
The paradox::ParamSet describes either a subset of the domain of the Objective or it describes a set of parameters together with a trafo function that transforms values from the search space to values of the domain.
Depending on the context, this value defaults to the domain of the objective.
codomain(paradox::ParamSet) Specifies codomain of function. Most importantly the tags of each output "Parameter" define whether it should be minimized or maximized. The default is to minimize each component.
check_values(logical(1))
Should x-values that are added to the archive be checked for validity?
Search space that is logged into archive.
add_evals()Adds function evaluations to the archive table.
Archive$add_evals(xdt, xss_trafoed, ydt)
xdt(data.table::data.table())
Set of untransformed points / points from the search space.
One point per row, e.g. data.table(x1 = c(1, 3), x2 = c(2, 4)).
Column names have to match ids of the search_space.
However, xdt can contain additional columns.
xss_trafoed(list())
Transformed point(s) in the domain space.
ydt(data.table::data.table())
Optimal outcome.
best()Returns the best scoring evaluation. For single-crit optimization, the solution that minimizes / maximizes the objective function. For multi-crit optimization, the Pareto set / front.
Archive$best(m = NULL)
m(integer())
Take only batches m into account. Default is all batches.
data()Returns a data.table::data.table which contains all performed Objective function calls.
Archive$data(unnest = NULL)
unnest(character())
Set of column names for columns to unnest via mlr3misc::unnest().
Unnested columns are stored in separate columns instead of list-columns.
format()Helper for print outputs.
Archive$format()
print()Printer.
Archive$print()
...(ignored).
clear()Clear all evaluation results from archive.
Archive$clear()
clone()The objects of this class are cloneable with this method.
Archive$clone(deep = FALSE)
deepWhether to make a deep clone.