def test_3output_dimensions(self):
nn=NN((2,2,3),verbose=0)
inputs=([1,0],[0,1],[1,1],[0,0])
for i in inputs:
nn.forward(i)
self.assertEqual(nn.outputs[0].shape,(3,1))
self.assertEqual(nn.outputs[1].shape,(3,1))
self.assertEqual(nn.outputs[2].shape,(3,1))
self.assertEqual(nn.get_output().shape,(3,))
def test_3output_dimensions(self):
nn = NN((2, 2, 3), verbose=0)
inputs = ([1, 0], [0, 1], [1, 1], [0, 0])
for i in inputs:
nn.forward(i)
self.assertEqual(nn.outputs[0].shape, (3, 1))
self.assertEqual(nn.outputs[1].shape, (3, 1))
self.assertEqual(nn.outputs[2].shape, (3, 1))
self.assertEqual(nn.get_output().shape, (3, ))
def test_backward(self):
X=[[0,0],[0,1],[1,0],[1,1]]
Y=[[0],[1],[1],[0]]
nn=NN([2,2,1],verbose=0)
for i in range(4):
nn.forward(X[i])
nn.backward(Y[i])
self.assertEqual(nn.outputs[0].shape,(3,1))
self.assertEqual(nn.outputs[1].shape,(3,1))
self.assertEqual(nn.outputs[2].shape,(1,1))
self.assertEqual(nn.get_output().shape,(1,))
def test_backward(self):
X = [[0, 0], [0, 1], [1, 0], [1, 1]]
Y = [[0], [1], [1], [0]]
nn = NN([2, 2, 1], verbose=0)
for i in range(4):
nn.forward(X[i])
nn.backward(Y[i])
self.assertEqual(nn.outputs[0].shape, (3, 1))
self.assertEqual(nn.outputs[1].shape, (3, 1))
self.assertEqual(nn.outputs[2].shape, (1, 1))
self.assertEqual(nn.get_output().shape, (1, ))
class NNPaddle(object):
def __init__(self, x_pos, y_pos, ball, game, four_player=False):
self.bounds = pygame.Rect(x_pos, y_pos, 15, 100)
self.ball = ball
self.game = game
self.four_player = four_player
# self.net = NeuralNet(4, 1, 3)
self.net = NeuralNet(3, 1, 3)
self.generation = 0
self.score = 0
self.fitness = 0
self.contacts_ball = 0
self.name = self.random_name()
self.parents = []
self.colors = None
self.color_ndx = 0
self.seizure_reduction = 0
self.seize_rate = random.uniform(0, 15)
self.set_colors()
def __repr__(self):
return str(self.name) + ' score: ' + str(self.score) + ' contacts: ' + str(self.contacts_ball) + \
' gen: ' + str(self.generation)
def __gt__(self, other):
return self.fitness > other.fitness
def draw(self, display):
random.seed()
if self.colors is None:
self.set_colors()
self.seizure_reduction += 1
if self.seizure_reduction > self.seize_rate:
self.color_ndx = int(random.uniform(0, 4))
self.seizure_reduction = 0
pygame.draw.rect(display, (self.colors[self.color_ndx]), self.bounds)
def set_colors(self):
color_1 = (random.uniform(0, 255), random.uniform(0, 255),
random.uniform(0, 255))
color_2 = (random.uniform(0, 255), random.uniform(0, 255),
random.uniform(0, 255))
color_3 = (random.uniform(0, 255), random.uniform(0, 255),
random.uniform(0, 255))
color_4 = (random.uniform(0, 255), random.uniform(0, 255),
random.uniform(0, 255))
self.colors = [color_1, color_2, color_3, color_4]
self.color_ndx = 0
self.color_ndx = int(random.uniform(0, 4))
def move_up(self, delta):
self.bounds = self.bounds.move(0, -250 * delta)
def move_down(self, delta):
self.bounds = self.bounds.move(0, 250 * delta)
def follow_ball(self, delta):
y_pos = self.bounds.y + self.bounds.height
ball_y = self.ball.bounds.y
ball_speed = math.sqrt(self.ball.vel_x**2 + self.ball.vel_y**2)
inputs = [y_pos, ball_y, ball_speed]
output = self.net.get_output(inputs)
if not self.four_player:
if output > 0.5:
if self.bounds.y + self.bounds.height < self.game.window_height:
self.move_down(delta)
else:
if self.bounds.y > 0:
self.move_up(delta)
else:
if output > 0.5:
if self.bounds.y + self.bounds.height < self.game.window_height - 50:
self.move_down(delta)
else:
if self.bounds.y > 50:
self.move_up(delta)
def reset(self, x_pos, y_pos, ball):
self.ball = ball
self.bounds = pygame.Rect(x_pos, y_pos, 15, 100)
def save_genome(self, file_path='./genomes/'):
path = file_path + str(self.name)
f = open(path, 'w+')
for synapse in self.net.synapses:
f.write(str(synapse) + '\n')
f.write(self.name + '\n')
f.write(str(self.generation) + '\n')
f.close()
def load_genomes(self, file):
try:
f = open('./final_genomes/' + file)
except FileNotFoundError:
try:
f = open('./genomes/' + file)
except FileNotFoundError:
print(FileNotFoundError)
return
layer_number = 0
synapses = []
name, gen = False, False
for line in f:
if len(line) > 0 and line[
0] == '[' and layer_number <= self.net.num_hidden_layers:
gene = []
synapse = line.split(',')
for s in synapse:
if '[' in s:
gene.append(float(s.strip('[')))
elif '\n' in s:
gene.append(float(s.strip(']\n')))
else:
gene.append(float(s))
synapses.append(gene)
layer_number += 1
elif not name:
self.name = line.strip('\n')
name = True
elif not gen:
self.generation = int(line.strip('\n'))
gen = True
for i in range(len(self.net.synapses)):
for j in range(len(self.net.synapses[i])):
self.net.synapses[i][j].weight = synapses[i][j]
print('Loaded genome:', self)
@staticmethod
def random_name():
names = [
'Cheenis', 'Garreth', 'Baxter', 'Slidey', 'McPong', 'Jeeves',
'Jacob', 'Bool', 'Don', 'Cheedle', 'Don', 'Cheedle', 'Stanley',
'Alexa', 'The Pacer Test', 'Finn', 'Daniel', 'Dan the Man', 'Dad',
'The Alamo', 'Grobgobbler', 'Gavin', 'Doyle', '@RealGavin', 'Juul',
'Bruul', 'Dr.', 'Bichael', 'Flats', 'Andrew', 'Farquaad', 'Blanch',
'Son of', 'Dreyfuss', 'Chad', 'Donald', 'Chump', 'Too Many',
'Bocephus', 'Diengklurg', 'Antwaun', 'Dart', 'Joe', 'Szymczyk',
'Stratton', 'Go', 'Bears', 'Jabarbwire', 'Barbara', 'Bush',
'Dante', 'Soldavini', 'Rick'
]
if random.uniform(0, 1) > 0.5:
return random.choice(names)
else:
temp_names = list(names)
f_name = random.choice(temp_names)
temp_names.remove(f_name)
l_name = random.choice(temp_names)
return f_name + ' ' + l_name
