def test_double_evolution():
p = problems.DoubleFrequency()
g = grns.ClassicGRN()
config.POPULATION_SIZE = 30
g.random(p.nin, p.nout, 5)
random_fitness = p.eval(g)
evo = evolution.Evolution(p)
best_fit, best_ind = evo.run(5)
print(random_fitness, ", ", best_fit)
assert best_fit > random_fitness
def test_evolution_boston():
config.POPULATION_SIZE = 5
config.INITIALIZATION_DUPLICATION = 2
config.START_SPECIES_THRESHOLD = 0.05
config.MIN_SPECIES_SIZE = 1
p = problems.Boston()
newgrn = lambda: grns.DiffGRN()
grneat = evolution.Evolution(p, newgrn)
best_fit, _ = grneat.run(2)
assert best_fit >= 0.0
assert best_fit <= 1.0
log_file = os.path.join(log_dir, 'fits_' + args.id + '.log')
grn_dir = os.path.join(args.root_dir, 'grns')
data_dir = os.path.join(args.root_dir, 'data')
log_file = os.path.join(log_dir, 'fits_' + args.id + '.log')
p = eval('problems.' + args.problem)
p = p(args.env, args.nin, args.nout, args.ep_max)
print("..Init GRN..")
newgrn = grns.ClassicGRN() #DiffGRN()
newgrn2 = lambda: grns.ClassicGRN() #DiffGRN()
if args.evo:
print("..Evolv GRN..")
grneat = evolution.Evolution(p,
newgrn2,
run_id=args.id,
grn_dir=grn_dir,
log_dir=log_dir)
grneat.run(args.gens)
else:
for i in range(1):
print("..Init GRN", i, "..")
#grn = grns.ClassicGRN()
if args.grn_file:
print("..Load GRN..")
with open(grn_dir + "/grns_" + str(args.id) + ".log", 'r') as f:
grns = f.readlines()
#print("\t ", grns[-1])
newgrn.from_str(grns[-1])
else:
print("..Gen Random GRN..")
help='Log directory',
default='logs')
args = parser.parse_args()
log_file = os.path.join(args.log_dir, 'fits_' + args.id + '.log')
pclass = eval("problems." + args.problem)
np.random.seed(args.seed)
p = pclass(log_file, args.seed, args.learn, args.env, args.steps, args.warmup)
newgrn = lambda: grns.DiffGRN()
if args.evo:
grneat = evolution.Evolution(p,
newgrn,
args.id,
grn_dir=args.grn_dir,
log_dir=args.log_dir)
if args.grn_file:
with open(args.grn_file, 'r') as f:
pcount = 0
for g in f.readlines():
if pcount < len(grneat.population.offspring):
grn = newgrn()
grn.from_str(g)
ind = evolution.Individual(grn)
grneat.population.offspring[pcount] = ind
pcount += 1
grneat.run(args.gens)
else:
if args.grn_file: