pg.evolution.recombinators.Sample

Accessible via pg.evolution.recombinators.Sample.

class Sample(weights, where=All(), seed=None)

Bases: pg.evolution.recombinators.PointWise

Point-wise crossover that sample values from parents by weights.

The Sample recombinator works similarly as the Uniform recombinator, except that it takes a user function to compute the weights, based on which each parent’s decision will be sampled. Uniform can be represented as Sample(lambda xs: [1] * len(xs)), whose weights function generates the sampling weights in uniform distribution.

Methods:

merge(decision_point, parent_decisions)

Implementation of point-wise decision making.

merge(decision_point, parent_decisions)

Implementation of point-wise decision making.

Return type:

Union[int, List[int], float]

Parameters:

• decision_point – Decision point for recombination.

• parent_decisions – A list of parent’s decisions. Each item should be an int as an active single-choice decision, a list of int as active multi- choice decisions, a float as an active float decision, or None for inactive decision point (whose parent space is not chosen).

• global_state – An optional keyword argument as the global state. Subclass can omit.

• step – An optional keyword argument as the current step. Subclass can omit.

Returns:

An int, list of int or float as the decision made for the decision point.