Recombinator that chooses which operation to perform probabilistically and independently for each component.
The Recombinator wraps two other Recombinators given during construction,
and both of these operators are run. The ultimate result is sampled from the results of these operations independently for each individuum
and component: with probability p (configuration parameter), the result from the Recombinator given to
the recombinator construction argument is used, and with probability p - 1 the one given to recombinator_not is used.
The values of $n_indivs_in and $n_indivs_out is set to the corresponding values of the wrapped Recombinators. Both recombinator and recombinator_not
must currently have the same respective $n_indivs_in and $n_indivs_out values.
This operator has the configuration parameters of the Recombinators that it wraps: The configuration parameters of the operator given to the recombinator construction argument
are prefixed with "cmpmaybe.", the configuration parameters of the operator given to the recombinator_not construction argument are prefixed with "cmpmaybe_not.".
Additional configuration parameters:
p :: numeric(1)
Probability per component with which to use the result of applying the operator given to the recombinator construction argument. Must be set by the user.
Supported Domain classes are the set intersection of supported classes of recombinator and recombinator_not.
This Recombinator can be created with the short access form rec()
(recs() to get a list), or through the the dictionary
dict_recombinators in the following way:
# preferred:
rec("cmpmaybe", <recombinator> [, <recombinator_not>])
recs("cmpmaybe", <recombinator> [, <recombinator_not>]) # takes vector IDs, returns list of Recombinators# long form:
dict_recombinators$get("cmpmaybe", <recombinator> [, <recombinator_not>])
miesmuschel::MiesOperator -> miesmuschel::Recombinator -> RecombinatorCmpMaybe
recombinator(Recombinator)
Recombinator being wrapped. This operator gets run with probability p (configuration parameter).
recombinator_not(Recombinator)
Alternative Recombinator being wrapped. This operator gets run with probability 1 - p (configuration parameter).
new()Initialize the RecombinatorCmpMaybe object.
RecombinatorCmpMaybe$new(recombinator, recombinator_not = NULL)recombinator(Recombinator)
Recombinator to wrap. Component-wise results of this operator are used with probability p (Configuration parameter).
The constructed object gets a clone of this argument.
The $recombinator field will reflect this value.
recombinator_not(Recombinator)
Another Recombinator to wrap. Results from this operator are used when recombinator is not chosen. By
default, this is RecombinatorNull, i.e. no operation, with both n_indivs_in and n_indivs_out set
to match recombinator. This does not work when recombinator has n_indivs_in < n_indivs_out, in which
case this argument must be set explicitly.
With this default, the RecombinatorCmpMaybe object applies the recombinator operation with probability p, and
no operation at all otherwise.
The constructed object gets a clone of this argument.
The $recombinator_not field will reflect this value.
prime()See MiesOperator method. Primes both this operator, as well as the wrapped operators
given to recombinator and recombinator_not during construction.
RecombinatorCmpMaybe$prime(param_set)param_set(ParamSet)
Passed to MiesOperator$prime().
invisible self.
clone()The objects of this class are cloneable with this method.
RecombinatorCmpMaybe$clone(deep = FALSE)deepWhether to make a deep clone.
Other recombinators:
OperatorCombination,
Recombinator,
RecombinatorPair,
dict_recombinators_convex,
dict_recombinators_cvxpair,
dict_recombinators_maybe,
dict_recombinators_null,
dict_recombinators_proxy,
dict_recombinators_sbx,
dict_recombinators_sequential,
dict_recombinators_swap,
dict_recombinators_xonary,
dict_recombinators_xounif
Other recombinator wrappers:
OperatorCombination,
dict_recombinators_maybe,
dict_recombinators_proxy,
dict_recombinators_sequential
set.seed(1)
rm = rec("cmpmaybe", rec("swap"), p = 0.5)
p = ps(x = p_int(1, 8), y = p_dbl(1, 8), z = p_lgl())
data = data.frame(x = 1:8, y = 1:8, z = rep(TRUE, 4))
rm$prime(p)
rm$operate(data)
rm$param_set$values$p = 0.3
rm$operate(data)
# equivalent to rec("cmpmaybe", rec("swap", keep_complement = FALSE), p = 0.7)
rm2 = rec("cmpmaybe",
recombinator = rec("null", 2, 1),
recombinator_not = rec("swap", keep_complement = FALSE),
p = 0.3
)
rm2$prime(p)
rm2$operate(data)
Run the code above in your browser using DataLab