source: framspy/evolalg/base/experiment_islands_model_abc.py

Last change on this file was 1297, checked in by Maciej Komosinski, 10 months ago

Removed unused "static" fields

File size: 4.4 KB
Line 
1import time
2from abc import ABC
3from typing import List
4
5from ..structures.individual import Individual
6from ..structures.population import PopulationStructures
7from .experiment_abc import ExperimentABC
8
9
10class ExperimentIslands(ExperimentABC, ABC):
11
12    def __init__(self, popsize, hof_size, number_of_populations, migration_interval, save_only_best) -> None:
13        super().__init__(popsize=popsize, hof_size=hof_size, save_only_best=save_only_best)
14        self.populations=[]
15        self.number_of_populations=number_of_populations
16        self.migration_interval=migration_interval
17
18    def migrate_populations(self):
19        print("Performing base migration")
20        pool_of_all_individuals = []
21        for p in self.populations:
22            pool_of_all_individuals.extend(p.population)
23        print(f"Pool of individuals: {len(pool_of_all_individuals)}")
24        sorted_individuals = sorted(
25            pool_of_all_individuals, key=lambda x: x.rawfitness)
26        print("Best individual for new islands:")
27        for i in range(self.number_of_populations):
28            shift = i*self.popsize
29            self.populations[i].population = sorted_individuals[shift:shift+self.popsize]
30            print(i, self.populations[i].population[-1].rawfitness)
31
32    def initialize_evolution(self, initialgenotype):
33        self.current_generation = 0
34        self.time_elapsed = 0
35        self.stats = []  # stores the best individuals, one from each generation
36        initial_individual = Individual()
37        initial_individual.set_and_evaluate(initialgenotype, self.evaluate)
38        self.stats.append(initial_individual.rawfitness)
39        [self.populations.append(PopulationStructures(initial_individual=initial_individual,
40                                                      popsize=self.popsize))
41         for _ in range(self.number_of_populations)]
42
43    def get_state(self):
44        return [self.time_elapsed, self.current_generation, self.populations, self.hof, self.stats]
45
46    def set_state(self, state):
47        self.time_elapsed, self.current_generation, self.populations, hof_, self.stats = state
48        # sorting: ensure that we add from worst to best so all individuals are added to HOF
49        for h in sorted(hof_, key=lambda x: x.rawfitness):
50            self.hof.add(h)
51
52    def evolve(self, hof_savefile, generations, initialgenotype, pmut, pxov, tournament_size):
53        file_name = self.get_state_filename(hof_savefile)
54        state = self.load_state(file_name)
55        if state is not None:  # loaded state from file
56            # saved generation has been completed, start with the next one
57            self.current_generation += 1
58            print("...Resuming from saved state: population size = %d, hof size = %d, stats size = %d, generation = %d/%d" % (len(self.populations[0].population), len(
59                self.hof), len(self.stats), self.current_generation, generations))  # self.current_generation (and g) are 0-based, parsed_args.generations is 1-based
60        else:
61            self.initialize_evolution(initialgenotype)
62        time0 = time.process_time()
63        for g in range(self.current_generation, generations):
64            for p in self.populations:
65                p.population = self.make_new_population(
66                    p.population, pmut, pxov, tournament_size)
67
68            if g % self.migration_interval == 0:
69                print("---------Start of migration-------")
70                self.migrate_populations()
71                print("---------End of migration---------")
72
73            pool_of_all_individuals = []
74            [pool_of_all_individuals.extend(p.population)
75             for p in self.populations]
76            self.update_stats(g, pool_of_all_individuals)
77            if hof_savefile is not None:
78                self.current_generation = g
79                self.time_elapsed += time.process_time() - time0
80                self.save_state(file_name)
81
82        if hof_savefile is not None:
83            self.save_genotypes(hof_savefile)
84
85        return self.hof, self.stats
86
87    @staticmethod
88    def get_args_for_parser():
89        parser = ExperimentABC.get_args_for_parser()
90
91        parser.add_argument("-islands",type=int, default=5,
92                            help="Number of subpopulations (islands)")
93        parser.add_argument("-generations_migration",type=int, default=10,
94                            help="Number of generations separating migration events when genotypes migrate between subpopulations (islands)")
95        return parser
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