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Container around a data.table::data.table which stores all performed function calls of the Objective.

S3 Methods

  • as.data.table(archive)
    Archive -> data.table::data.table()
    Returns a tabular view of all performed function calls of the Objective. The x_domain column is unnested to separate columns.

Public fields

search_space

(paradox::ParamSet)
Search space of objective.

codomain

(Codomain)
Codomain of objective function.

start_time

(POSIXct)
Time stamp of when the optimization started. The time is set by the Optimizer.

check_values

(logical(1))
Determines if points and results are checked for validity.

data

(data.table::data.table)
Contains all performed Objective function calls.

Active bindings

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 target parameters.

Methods


Method new()

Creates a new instance of this R6 class.

Usage

Archive$new(search_space, codomain, check_values = TRUE)

Arguments

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.


Method add_evals()

Adds function evaluations to the archive table.

Usage

Archive$add_evals(xdt, xss_trafoed = NULL, ydt)

Arguments

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.


Method best()

Returns the best scoring evaluation(s). For single-crit optimization, the solution that minimizes / maximizes the objective function. For multi-crit optimization, the Pareto set / front.

Usage

Archive$best(batch = NULL, n_select = 1)

Arguments

batch

(integer())
The batch number(s) to limit the best results to. Default is all batches.

n_select

(integer(1L))
Amount of points to select. Ignored for multi-crit optimization.


Method nds_selection()

Calculate best points w.r.t. non dominated sorting with hypervolume contribution.

Usage

Archive$nds_selection(batch = NULL, n_select = 1, ref_point = NULL)

Arguments

batch

(integer())
The batch number(s) to limit the best points to. Default is all batches.

n_select

(integer(1L))
Amount of points to select.

ref_point

(numeric())
Reference point for hypervolume.


Method format()

Helper for print outputs.

Usage

Archive$format()


Method print()

Printer.

Usage

Archive$print()

Arguments

...

(ignored).


Method clear()

Clear all evaluation results from archive.

Usage

Archive$clear()


Method clone()

The objects of this class are cloneable with this method.

Usage

Archive$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.