ObjectiveRFun {bbotk} | R Documentation |
Objective interface where the user can pass a custom R function that expects a list as input. If the return of the function is unnamed, it is named with the ids of the codomain.
bbotk::Objective
-> ObjectiveRFun
fun
(function
)
Objective function.
new()
Creates a new instance of this R6 class.
ObjectiveRFun$new( fun, domain, codomain = NULL, id = "function", properties = character(), constants = ps(), check_values = TRUE )
fun
(function
)
R function that encodes objective and expects a list with the input for a single point
(e.g. list(x1 = 1, x2 = 2)
) and returns the result either as a numeric vector or a
list (e.g. list(y = 3)
).
domain
(paradox::ParamSet)
Specifies domain of function.
The paradox::ParamSet should describe all possible input parameters of the objective function.
This includes their id
, their types and the possible range.
codomain
(paradox::ParamSet)
Specifies codomain of function.
Most importantly the tags of each output "Parameter" define whether it should
be minimized or maximized. The default is to minimize each component.
id
(character(1)
).
properties
(character()
).
constants
(paradox::ParamSet)
Changeable constants or parameters that are not subject to tuning can be stored and accessed here.
check_values
(logical(1)
)
Should points before the evaluation and the results be checked for
validity?
eval()
Evaluates input value(s) on the objective function. Calls the R function supplied by the user.
ObjectiveRFun$eval(xs)
xs
Input values.
clone()
The objects of this class are cloneable with this method.
ObjectiveRFun$clone(deep = FALSE)
deep
Whether to make a deep clone.
# define objective function
fun = function(xs) {
-(xs[[1]] - 2)^2 - (xs[[2]] + 3)^2 + 10
}
# set domain
domain = ps(
x1 = p_dbl(-10, 10),
x2 = p_dbl(-5, 5)
)
# set codomain
codomain = ps(y = p_dbl(tags = "maximize"))
# create Objective object
obfun = ObjectiveRFun$new(
fun = fun,
domain = domain,
codomain = codomain,
properties = "deterministic"
)