#
eckity.breeders.simple_breeder

1from eckity.breeders.breeder import Breeder 2from eckity.genetic_operators.selections.elitism_selection import ElitismSelection 3 4 5class SimpleBreeder(Breeder): 6 def __init__(self, 7 events=None): 8 super().__init__(events=events) 9 self.selected_individuals = [] # TODO why do we need this field? what about applied_individuals? 10 self.best_of_run = [] # TODO this field isn't used 11 12 def apply_breed(self, population): 13 """ 14 Apply elitism, selection method and the sub-population's operator sequence on each sub-population. 15 In simple case, the operator sequence is applied on the one and only sub-population. 16 17 Parameters 18 ---------- 19 population: 20 Population of sub-populations of individuals. The operators will be applied on those individuals. 21 22 Returns 23 ------- 24 None. 25 """ 26 for subpopulation in population.sub_populations: 27 nextgen_population = [] 28 29 num_elites = subpopulation.n_elite 30 if num_elites > 0: 31 elitism_sel = ElitismSelection(num_elites=num_elites, higher_is_better=subpopulation.higher_is_better) 32 elitism_sel.apply_operator((subpopulation.individuals, nextgen_population)) 33 34 self.selected_individuals = subpopulation.get_selection_methods()[0][0] \ 35 .select(subpopulation.individuals, nextgen_population) 36 37 # then runs all operators on next_gen 38 nextgen_population = self._apply_operators(subpopulation.get_operators_sequence(), 39 self.selected_individuals) 40 # TODO assert simple operators the has %0 with pop size 41 42 subpopulation.individuals = nextgen_population 43 44 def _apply_operators(self, operator_seq, individuals_to_apply_on): 45 """ 46 Apply a given operator sequence on a given list of individuals. 47 The operators are done sequentially. 48 49 Parameters 50 ---------- 51 operator_seq: list of operators 52 Operator sequence. The operators will be applied sequentially on the given individuals. 53 individuals_to_apply_on: list of individuals 54 The individuals to apply the operator sequence on. 55 56 Returns 57 ------- 58 list of individuals 59 The individuals list after the operators were applied on them. 60 """ 61 for operator in operator_seq: 62 operator_arity = operator.get_operator_arity() 63 for i in range(0, len(individuals_to_apply_on), operator_arity): 64 op_res = operator.apply_operator(individuals_to_apply_on[i:i + operator_arity]) 65 individuals_to_apply_on[i:i + operator_arity] = op_res 66 return individuals_to_apply_on 67 68 def event_name_to_data(self, event_name): 69 if event_name == "after_selection": 70 return {"selected_individuals": self.selected_individuals, 71 "best_of_run": self.best_of_run}

6class SimpleBreeder(Breeder): 7 def __init__(self, 8 events=None): 9 super().__init__(events=events) 10 self.selected_individuals = [] # TODO why do we need this field? what about applied_individuals? 11 self.best_of_run = [] # TODO this field isn't used 12 13 def apply_breed(self, population): 14 """ 15 Apply elitism, selection method and the sub-population's operator sequence on each sub-population. 16 In simple case, the operator sequence is applied on the one and only sub-population. 17 18 Parameters 19 ---------- 20 population: 21 Population of sub-populations of individuals. The operators will be applied on those individuals. 22 23 Returns 24 ------- 25 None. 26 """ 27 for subpopulation in population.sub_populations: 28 nextgen_population = [] 29 30 num_elites = subpopulation.n_elite 31 if num_elites > 0: 32 elitism_sel = ElitismSelection(num_elites=num_elites, higher_is_better=subpopulation.higher_is_better) 33 elitism_sel.apply_operator((subpopulation.individuals, nextgen_population)) 34 35 self.selected_individuals = subpopulation.get_selection_methods()[0][0] \ 36 .select(subpopulation.individuals, nextgen_population) 37 38 # then runs all operators on next_gen 39 nextgen_population = self._apply_operators(subpopulation.get_operators_sequence(), 40 self.selected_individuals) 41 # TODO assert simple operators the has %0 with pop size 42 43 subpopulation.individuals = nextgen_population 44 45 def _apply_operators(self, operator_seq, individuals_to_apply_on): 46 """ 47 Apply a given operator sequence on a given list of individuals. 48 The operators are done sequentially. 49 50 Parameters 51 ---------- 52 operator_seq: list of operators 53 Operator sequence. The operators will be applied sequentially on the given individuals. 54 individuals_to_apply_on: list of individuals 55 The individuals to apply the operator sequence on. 56 57 Returns 58 ------- 59 list of individuals 60 The individuals list after the operators were applied on them. 61 """ 62 for operator in operator_seq: 63 operator_arity = operator.get_operator_arity() 64 for i in range(0, len(individuals_to_apply_on), operator_arity): 65 op_res = operator.apply_operator(individuals_to_apply_on[i:i + operator_arity]) 66 individuals_to_apply_on[i:i + operator_arity] = op_res 67 return individuals_to_apply_on 68 69 def event_name_to_data(self, event_name): 70 if event_name == "after_selection": 71 return {"selected_individuals": self.selected_individuals, 72 "best_of_run": self.best_of_run}

The Breeder is responsible to activate the genetic operators (selection, crossover, mutation) on the existing population

###### Parameters

**events**(dict(str, dict(object, function))): dictionary of event names to dictionary of subscribers to callback methods

def
apply_breed(self, population):

13 def apply_breed(self, population): 14 """ 15 Apply elitism, selection method and the sub-population's operator sequence on each sub-population. 16 In simple case, the operator sequence is applied on the one and only sub-population. 17 18 Parameters 19 ---------- 20 population: 21 Population of sub-populations of individuals. The operators will be applied on those individuals. 22 23 Returns 24 ------- 25 None. 26 """ 27 for subpopulation in population.sub_populations: 28 nextgen_population = [] 29 30 num_elites = subpopulation.n_elite 31 if num_elites > 0: 32 elitism_sel = ElitismSelection(num_elites=num_elites, higher_is_better=subpopulation.higher_is_better) 33 elitism_sel.apply_operator((subpopulation.individuals, nextgen_population)) 34 35 self.selected_individuals = subpopulation.get_selection_methods()[0][0] \ 36 .select(subpopulation.individuals, nextgen_population) 37 38 # then runs all operators on next_gen 39 nextgen_population = self._apply_operators(subpopulation.get_operators_sequence(), 40 self.selected_individuals) 41 # TODO assert simple operators the has %0 with pop size 42 43 subpopulation.individuals = nextgen_population

Apply elitism, selection method and the sub-population's operator sequence on each sub-population. In simple case, the operator sequence is applied on the one and only sub-population.

###### Parameters

**population:**: Population of sub-populations of individuals. The operators will be applied on those individuals.

###### Returns

**None.**