1 | import argparse |
---|
2 | import os |
---|
3 | import sys |
---|
4 | import numpy as np |
---|
5 | |
---|
6 | #TODO add new example: steadystate.py (analogous to standard.py) |
---|
7 | #TODO extend both standard.py and steadystate.py to support >1 criteria (using DEAP's selNSGA2() and selSPEA2()) |
---|
8 | #TODO add comments to all examples in this directory |
---|
9 | #TODO add to standard.py and steadystate.py evaluating each genotype in HOF N (configurable, default 10) times when the evolution ends |
---|
10 | #TODO protect all examples against invalid genotypes (fill population until all genotypes are conrrectly evaluated). And maybe remove invalid.py if it overlaps with (is a subset of) other examples |
---|
11 | |
---|
12 | from FramsticksLib import FramsticksLib |
---|
13 | from evolalg.base.lambda_step import LambdaStep |
---|
14 | from evolalg.dissimilarity.frams_dissimilarity import FramsDissimilarity |
---|
15 | from evolalg.experiment import Experiment |
---|
16 | from evolalg.fitness.fitness_step import FitnessStep |
---|
17 | from evolalg.mutation_cross.frams_cross_and_mutate import FramsCrossAndMutate |
---|
18 | from evolalg.population.frams_population import FramsPopulation |
---|
19 | from evolalg.selection.tournament import TournamentSelection |
---|
20 | from evolalg.statistics.halloffame_stats import HallOfFameStatistics |
---|
21 | from evolalg.statistics.statistics_deap import StatisticsDeap |
---|
22 | from evolalg.base.union_step import UnionStep |
---|
23 | |
---|
24 | |
---|
25 | def ensureDir(string): |
---|
26 | if os.path.isdir(string): |
---|
27 | return string |
---|
28 | else: |
---|
29 | raise NotADirectoryError(string) |
---|
30 | |
---|
31 | |
---|
32 | def parseArguments(): |
---|
33 | parser = argparse.ArgumentParser( |
---|
34 | description='Run this program with "python -u %s" if you want to disable buffering of its output.' % sys.argv[ |
---|
35 | 0]) |
---|
36 | parser.add_argument('-path', type=ensureDir, required=True, help='Path to Framsticks without trailing slash.') |
---|
37 | parser.add_argument('-opt', required=True, |
---|
38 | help='optimization criteria : vertpos, velocity, distance, vertvel, lifespan, numjoints, numparts, numneurons, numconnections. Single or multiple criteria.') |
---|
39 | parser.add_argument('-lib', required=False, help="Filename of .so or .dll with framsticks library") |
---|
40 | parser.add_argument('-genformat', required=False, default="1", |
---|
41 | help='Genetic format for the demo run, for example 4, 9, or B. If not given, f1 is assumed.') |
---|
42 | |
---|
43 | parser.add_argument("-popsize", type=int, default=50, help="Population size, default 50.") |
---|
44 | parser.add_argument('-generations', type=int, default=5, help="Number of generations, default 5.") |
---|
45 | parser.add_argument('-tournament', type=int, default=5, help="Tournament size, default 5.") |
---|
46 | return parser.parse_args() |
---|
47 | |
---|
48 | |
---|
49 | def extract_fitness(ind): |
---|
50 | return ind.fitness |
---|
51 | |
---|
52 | |
---|
53 | def print_population_count(pop): |
---|
54 | print("Current:", len(pop)) |
---|
55 | return pop # Each step must return a population |
---|
56 | |
---|
57 | |
---|
58 | def main(): |
---|
59 | parsed_args = parseArguments() |
---|
60 | frams = FramsticksLib(parsed_args.path, parsed_args.lib, |
---|
61 | "eval-allcriteria.sim") |
---|
62 | |
---|
63 | hall_of_fame = HallOfFameStatistics(100, "fitness") |
---|
64 | statistics_union = UnionStep([ |
---|
65 | hall_of_fame, |
---|
66 | StatisticsDeap([ |
---|
67 | ("avg", np.mean), |
---|
68 | ("stddev", np.std), |
---|
69 | ("min", np.min), |
---|
70 | ("max", np.max), |
---|
71 | ("count", len) |
---|
72 | ], extract_fitness) |
---|
73 | ]) |
---|
74 | |
---|
75 | fitness = FitnessStep(frams, fields={parsed_args.opt: "fitness", }, fields_defaults={}) |
---|
76 | |
---|
77 | init_stages = [FramsPopulation(frams, parsed_args.genformat, 50), |
---|
78 | fitness, |
---|
79 | statistics_union] |
---|
80 | |
---|
81 | selection = TournamentSelection(parsed_args.tournament, copy=True, fit_attr="fitness") |
---|
82 | |
---|
83 | new_generation_steps = [ |
---|
84 | FramsCrossAndMutate(frams, cross_prob=0.2, mutate_prob=0.9), |
---|
85 | fitness, |
---|
86 | ] |
---|
87 | |
---|
88 | generation_modifications = [ |
---|
89 | statistics_union |
---|
90 | ] |
---|
91 | |
---|
92 | experiment = Experiment(init_population=init_stages, |
---|
93 | selection=selection, |
---|
94 | new_generation_steps=new_generation_steps, |
---|
95 | generation_modification=generation_modifications, |
---|
96 | end_steps=[], |
---|
97 | population_size=parsed_args.popsize |
---|
98 | ) |
---|
99 | experiment.init() |
---|
100 | experiment.run(parsed_args.generations) |
---|
101 | for ind in hall_of_fame.halloffame: |
---|
102 | print("%g\t%s" % (ind.fitness, ind.genotype)) |
---|
103 | |
---|
104 | |
---|
105 | if __name__ == '__main__': |
---|
106 | main() |
---|