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Objective interface for basic R functions.

Source: R/ObjectiveRFunDt.R
ObjectiveRFunDt.Rd

Objective interface where user can pass an R function that works on an data.table().

See also

ObjectiveRFun, ObjectiveRFunMany

Super class

bbotk::Objective -> ObjectiveRFunDt

Active bindings

fun

(function)
Objective function.

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

ObjectiveRFunDt$new(
  fun,
  domain,
  codomain = NULL,
  id = "function",
  properties = character(),
  constants = ps(),
  packages = character(),
  check_values = TRUE
)

Arguments

fun

(function)
R function that encodes objective and expects an data.table() as input whereas each point is represented by one row.

domain

(paradox::ParamSet)
Specifies domain of function. The paradox::ParamSet should describe all possible input parameters of the objective function. This includes their id, their types and the possible range.

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.

id

(character(1)).

properties

(character()).

constants

(paradox::ParamSet)
Changeable constants or parameters that are not subject to tuning can be stored and accessed here.

packages

(character())
Set of required packages to run the objective function.

check_values

(logical(1))
Should points before the evaluation and the results be checked for validity?

Method eval_many()

Evaluates multiple input values received as a list, converted to a data.table() on the objective function. Missing columns in xss are filled with NAs in xdt.

Usage

ObjectiveRFunDt$eval_many(xss)

Arguments

xss

(list())
A list of lists that contains multiple x values, e.g. list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)).

Returns

data.table::data.table() that contains one y-column for single-criteria functions and multiple y-columns for multi-criteria functions, e.g. data.table(y = 1:2) or data.table(y1 = 1:2, y2 = 3:4).

Method eval_dt()

Evaluates multiple input values on the objective function supplied by the user.

Usage

ObjectiveRFunDt$eval_dt(xdt)

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.

Returns

data.table::data.table()] that contains one y-column for single-criteria functions and multiple y-columns for multi-criteria functions, e.g. data.table(y = 1:2) or data.table(y1 = 1:2, y2 = 3:4).

Method clone()

The objects of this class are cloneable with this method.

Usage

ObjectiveRFunDt$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# define objective function
fun = function(xdt) {
  data.table::data.table(y = xdt$x1 + xdt$x2)
}

# set domain
domain = ps(
  x1 = p_dbl(-10, 10),
  x2 = p_dbl(-5, 5)
)

# set codomain
codomain = ps(
  y = p_dbl(tags = "maximize")
)

# create objective
objective = ObjectiveRFunDt$new(
  fun = fun,
  domain = domain,
  codomain = codomain,
  properties = "deterministic"
)

# evaluate objective function
objective$eval(list(x1 = 1, x2 = 2))
#> $y
#> [1] 3
#> 

# evaluate multiple input values
objective$eval_many(list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4)))
#>        y
#>    <num>
#> 1:     3
#> 2:     7

# evaluate multiple input values as data.table
objective$eval_dt(data.table::data.table(x1 = 1:2, x2 = 3:4))
#>        y
#>    <int>
#> 1:     4
#> 2:     6