class World:
def __init__(self, inp):
self.image_data = pygame.image.load("worldbigger.png").convert_alpha()
self.width = self.image_data.get_width()
self.height = self.image_data.get_height()
if AI_DRIVE:
self.population = Population(self, 20)
else:
self.car = Car(self, inp)
def update(self):
if AI_DRIVE:
self.population.update()
else:
self.car.update()
def render(self, display):
display.blit(self.image_data, (0, 0))
if AI_DRIVE:
self.population.render(display)
else:
self.car.render(display)
def get_terrain(self, point):
if point[0] < 0 or point[0] >= self.width:
return True
if point[1] < 0 or point[1] >= self.height:
return True
p_alpha = self.image_data.get_at((int(point[0]), int(point[1])))
return p_alpha == (255, 0, 0)
def __init__(self, inp):
self.image_data = pygame.image.load("worldbigger.png").convert_alpha()
self.width = self.image_data.get_width()
self.height = self.image_data.get_height()
if AI_DRIVE:
self.population = Population(self, 20)
else:
self.car = Car(self, inp)
def test_get_fittest_pair(self):
population = Population(
members=[Genome([1, 2, 3, 4, 5, 6, 7, 8]),
Genome([8, 7, 6, 5, 4, 3, 2, 1]),
Genome([4, 3, 2, 1, 8, 7, 6, 5])])
fittest_pair = population.get_fittest_pair(self._fitness_function)
expected_fittest_pair = (
Genome([8, 7, 6, 5, 4, 3, 2, 1]),
Genome([4, 3, 2, 1, 8, 7, 6, 5]))
self.assertEqual(fittest_pair, expected_fittest_pair)
def beatYourElders(self,
ancestry=1,
plot=True,
point_reset=True,
threaded=False,
n_threads=-1,
config_tag=''):
pops = [
pop for pop in self.populations
if self.generations - pop.generation < ancestry
]
Population.everybodyCompetes(pops, point_reset, threaded, n_threads)
if plot:
self.plotScorePerGeneration(pops, config_tag)
self.plotMeanAndMaxPerGeneration(pops, config_tag)
def main(pol_n, len_i, len_g, lin_n, regen, n_threads, show, config_tag):
THREADED = n_threads > 0
THREADS = n_threads
def lineageName(pol_n, gen_n):
return "test/BernBase{}gen{}.lineage".format(pol_n, gen_n)
#********** Generate the asked number of generations *********
# check
if(regen):
lin_n = pol_n
lins = []
# l is an int here
individuals = [ Individual([Chromosome(), Chromosome()], pol_n-1) for _ in range(len_i) ]
for indiv in individuals:
for c in indiv.chromosomes:
# generate a random set of weights for the chromosome
weights_compressed = [[0]*pol_n]* (len(HEURISTICS)-1)
for W_h in weights_compressed:
tmp_w = [0]*pol_n
for i in range(pol_n):
W_h[i] = max(0,1 -random.random() -tmp_w[i])
tmp_w[i] = tmp_w[i] + W_h[i]
c.set_genes(numpy.array(weights_compressed))
pop = Population(individuals, 1)
print("First generation created for lineage number ", lin_n)
lins.append(Lineage([pop], "0"))
fname = lineageName(pol_n, lins[0].generations)
print("saving to file : ", fname)
lins[0].toFile(fname)
# l is a lineage here
for l in lins:
while l.generations < len_g:
print("Creating generation ",l.generations+1)
l.nextGeneration(THREADED, THREADS)
fname = lineageName(pol_n, l.generations)
print("saving to file : ", fname)
l.toFile(fname)
lin = lins[-1]
else:
for g in range(len_g, 0, -1):
try:
fname = lineageName(pol_n, g)
fh = open(fname, 'r')
# Store configuration file values
lin = Lineage.fromFile(fname)
break
except FileNotFoundError:
if(g <= 1):
print("No previous generations were found, please add the -r or --regenerate flag")
exit("no files found : "+lineageName("<Bernstein base>", "<generationNumber>"))
# print(lin)
lin.beatYourElders(show, True, True, True, n_threads, config_tag)
def nextGeneration(self, threaded=False, n_threads=-1):
popul = Population(self.populations[-1].individuals,
self.generations + 1)
t1 = time.time()
popul.compete(True, threaded, n_threads)
delta = time.time() - t1
print("duration of competition: {} seconds".format(int(delta)))
deaths = popul.naturalySelect()
popul.naturalyRenew(deaths)
self.populations.append(popul)
self.updtLen()
return popul
def test_if_returns_best_phenotype(): pop = Population(mock_params, mock_judge, 1, 5) ph1 = Phenotype(3) ph2 = Phenotype(3) ph3 = Phenotype(3) ph1.genes = [True, True, True] ph2.genes = [True, False, False] ph3.genes = [False, False, False] mock_judge.goal_eval(1, 5, ph1) mock_judge.goal_eval(1, 5, ph2) mock_judge.goal_eval(1, 5, ph3) pop.push_phenotype(ph1) pop.push_phenotype(ph2) pop.push_phenotype(ph3) assert pop.get_the_best_error() == [True, False, False]
def test_if_creates_next_population_of_given_size(): pop = Population(mock_params, mock_judge, 1, 5) pop.generate_random_population() pop.create_next_epoch() assert len(pop.parents) == mock_params['mi']
def test_if_correctly_pushes_new_phenotype():
pop = Population(mock_params, mock_judge, 10, 10)
ph = Phenotype(3)
pop.push_phenotype(ph)
assert len(pop.parents) == 1
def test_if_raises_typeerror_on_incorrect_B_param():
with pytest.raises(TypeError):
pop = Population(mock_params, mock_judge, 10, '10')
def test_if_creates_empty_population():
pop = Population(mock_params, mock_judge, 10, 10)
assert len(pop.parents) == 0
import csound_adapter
from genetics import Population
from instrument import Instrument
IMAGE_VIEWER = 'eog'
graph_filename = 'graph.jpg'
iterations = 0
print '\n*** SOUND-EVOLUTION ***\n\nPress\n\n[1]\tto run option "population"'\
'\n[2]\tto run option "mutation"\n[3]\tto run option "make love"'
a = int(raw_input('\n:- '))
if a == 3:
P = Population(4, Instrument, {'const_prob': 0.7, 'max_children': 3})
while not raw_input(
'\nPress return to continue, anything else to quit:- '):
for n, i in enumerate(P.individuals):
try:
print i.to_instr()
print '\nPlaying Sound #{}'.format(n + 1)
i.to_graph(graph_filename)
os.system("%s %s &" % (IMAGE_VIEWER, graph_filename))
csd = csound_adapter.CSD()
csd.orchestra(i)
csd.score('i 1 0 2')
csd.play()
except OSError:
print '\nSkipping this iteration:- Csound crashed'
n = int(
def fromStr(str):
Str = str.split('\n\n')
name = Str.pop(0).split(' ')[1]
pops = [Population.fromStr(s) for s in Str]
return Lineage(pops, name)
lins = []
# l is an int here
for l in range(args.l):
individuals = [
Individual([Chromosome(), Chromosome()], args.n)
for _ in range(args.i)
]
for indiv in individuals:
for c in indiv.chromosomes:
# generate a random set of weights for the chromosome
weights_compressed = [[0] * pol_n] * (len(HEURISTICS) - 1)
for W_h in weights_compressed:
tmp_w = [0] * pol_n
for i in range(pol_n):
W_h[i] = max(0, 1 - random.random() - tmp_w[i])
tmp_w[i] = tmp_w[i] + W_h[i]
c.set_genes(numpy.array(weights_compressed))
pop = Population(individuals, 1)
print("First generation created for lineage number ", l)
lins.append(Lineage([pop], str(l)))
# l is a lineage here
for l in lins:
while l.generations < args.g:
print("Creating generation ", l.generations + 1)
l.nextGeneration(True)
fname = "lin{}gen{}.lineage".format(l.name, l.generations)
print("saving to file : ", "test/" + fname)
l.toFile("test/" + fname)
def test_init_with_no_parameters(self):
random_population = Population()
self.assertEqual(random_population.size(), 50)
from instrument import *
from genetics import Individual
from genetics import Population
import os
IMAGE_VIEWER = "eog"
graph_filename = "graph.jpg"
iterations = 0
print '\n*** SOUND-EVOLUTION ***\n\nPress\n\n[1]\tto run option "population"\n[2]\tto run option "mutation"\n[3]\tto run option "make love"'
a = int(raw_input('\n:- '))
if a==3:
P = Population(4, Instrument, {'const_prob':0.7, 'max_children':3})
while not raw_input('\nPress return to continue, anything else to quit:- '):
for n,i in enumerate(P.individuals):
try:
print i.to_instr()
print '\nPlaying Sound #%d' %(n+1)
i.to_graph(graph_filename)
os.system("%s %s &" % (IMAGE_VIEWER, graph_filename))
csd = csound_adapter.CSD()
csd.orchestra(i)
csd.score('i 1 0 2')
csd.play()
except OSError:
print '\nSkipping this iteration:- Csound crashed'
n = int(raw_input('\nWhich sound did you like best: 1, 2, 3 or 4?:- '))-1
m = int(raw_input('Which sound did you like 2nd best: 1, 2, 3 or 4?:- '))-1