Base class inheriting from Selector for selection operations that make use of scalar values, generated by Scalor.
SelectorScaling is an abstract base class and should be inherited from. Inheriting classes should implement the private $.select_scalar()
function. During $operate(), the $.select_scalar() function is called, it should have three arguments, similar to Selector's $.select() function.
values and n_select are as given to $.select() of the Selector. The fitnesses argument is first scaled by the associated Scalor
and then passed on as a numeric vector.
Typically, $initialize() should also be overloaded when inheriting.
Other base classes:
FiltorSurrogate,
Filtor,
MiesOperator,
MutatorDiscrete,
MutatorNumeric,
Mutator,
OperatorCombination,
RecombinatorPair,
Recombinator,
Scalor,
Selector
Other selectors:
Selector,
dict_selectors_best,
dict_selectors_maybe,
dict_selectors_null,
dict_selectors_proxy,
dict_selectors_random,
dict_selectors_sequential,
dict_selectors_tournament
miesmuschel::MiesOperator -> miesmuschel::Selector -> SelectorScalar
new()Initialize base class components of the SelectorScalar.
SelectorScalar$new(
scalor = ScalorSingleObjective$new(),
is_deterministic = FALSE,
param_classes = c("ParamLgl", "ParamInt", "ParamDbl", "ParamFct"),
param_set = ps(),
supported = scalor$supported,
packages = character(0),
dict_entry = NULL
)scalor(Scalor)Scalor to use to generate scalar values from multiple objectives, if multi-objective optimization is performed.
Initialized to ScalorSingleObjective: Doing single-objective optimization normally, throwing an error if used
in multi-objective setting: In that case, a Scalor needs to be explicitly chosen.
is_deterministic(logical(1))
Whether the Selector is deterministic. Setting this to TRUE adds a configuration parameter shuffle_selection (initialized to TRUE)
that causes the selection to be shuffled.
param_classes(character)
Classes of parameters that the operator can handle. May contain any of "ParamLgl", "ParamInt", "ParamDbl", "ParamFct".
Default is all of them.
The $param_classes field will reflect this value.
param_set(ParamSet | list of expression)
Strategy parameters of the operator. This should be created by the subclass and given to super$initialize().
If this is a ParamSet, it is used as the MiesOperator's ParamSet
directly. Otherwise it must be a list of expressions e.g. created by alist() that evaluate to ParamSets,
possibly referencing self and private.
These ParamSet are then combined using a ParamSetCollection.
Default is the empty ParamSet.
The $param_set field will reflect this value.
supported(character)
Subset of "single-crit" and "multi-crit", indicating wether single and / or multi-criterion optimization is supported.
Default to the supported set of scalor.
The $supported field will reflect this value.
packages(character)
Packages that need to be loaded for the operator to function. This should
be declared so these packages can be loaded when operators run on parallel
instances. Default is character(0).
The $packages field will reflect this values.
dict_entry(character(1) | NULL)
Key of the class inside the Dictionary (usually one of
dict_mutators, dict_recombinators, dict_selectors), where it can
be retrieved using a short access function. May be NULL if the operator
is not entered in a dictionary.
The $dict_entry field will reflect this value.
prime()See MiesOperator method. Primes both this operator, as well as the wrapped operator
given to scalor during construction.
param_set(ParamSet)
Passed to MiesOperator$prime().
invisible self.