metaheuristic_designer.operators.masked_operator module

Operator that applies different operators to disjoint slices of the genotype.

class MaskedOperator(op_list, mask, name=None, **kwargs)

Bases: Operator

Operator that partitions the genotype and applies different operators.

A mask (integer array of length vec_size) specifies which operator (index into op_list) handles each gene. This is used internally by ExtendedOperator to separate the solution from auxiliary parameters.

Parameters:

op_listlist of Operator

Operators to apply, one per mask index.

maskarray of int

Array of length vec_size assigning each gene to an operator.

namestr, optional

Display name; defaults to "Split (op_names)".

**kwargs

Forwarded to Operator.

Attributes:

params

Access parameter values by attribute-style lookup.

Parameters:

• op_list (Iterable[Operator])

• mask (MaskLike)

• name (str)

Methods

__call__(population)	Shorthand for evolve().
evolve(population)	Apply the appropriate operator to each slice of the genotype.
gather_params()	Collect parameters from this operator and all sub-operators.
get_params()	Return a copy of the current parameter dictionary.
get_state()	Gets the current state of the algorithm as a dictionary.
store_kwargs([progress])	Store keyword arguments and evaluate them at the given progress.
update(progress)	Update schedulable parameters and propagate to sub-operators.
update_kwargs([progress])	Add or replace parameters and immediately evaluate them.

gather_params()

Collect parameters from this operator and all sub-operators.

Return type:

dict

Returns:

dict

Flat dictionary with dotted keys.

evolve(population)

Apply the appropriate operator to each slice of the genotype.

Return type:

Population

Parameters:

populationPopulation

The current population.

Returns:

Population

The modified population.

Parameters:

population (Population)

update(progress)

Update schedulable parameters and propagate to sub-operators.

Parameters:

progressfloat

Current progress of the algorithm (0-1).

Parameters:

progress (float)

get_state()

Gets the current state of the algorithm as a dictionary.

Return type:

dict

Returns:

state: dict

The complete state of the operator.