def test(self):
global position
global _winners
if position == 4:
position = 0
main.reset(_records)
self.newWinner(position)
position += 1
def crd_unit_begin(crd):
print( "\n\n*************** Create mode crd test units ***************\n\n")
create(crd)
print( "\n\n*************** Read mode crd test units ***************\n\n")
read(crd)
print( "\n\n*************** Delete mode crd test units ***************\n\n")
delete(crd)
print( "\n\n*************** Reset mode crd test units ***************\n\n")
print(main.reset(crd.client))
print(main.reset("87Lane"))
def evolve():
""" Generate a new population based on the result of the earlier one """
d.next_gen = []
""" Keep the best car """
net_best = copy.deepcopy(d.best_car.neural_net)
d.next_gen.append(Car(net_best))
""" Make strong mutations from the best car """
for _ in range(d.BEST_CAR_MUTATION_HIGH):
net = copy.deepcopy(d.best_car.neural_net)
net = mutate(net, True)
d.next_gen.append(Car(net))
""" Make small mutation from the best car """
for _ in range(d.BEST_CAR_MUTATION_LOW):
net = copy.deepcopy(d.best_car.neural_net)
net = mutate(net, False)
d.next_gen.append(Car(net))
""" Make mutations from the shitty cars """
for i in range(d.SHITTY_CAR_COUNT):
net = copy.deepcopy(d.shitty_cars[i].neural_net)
net = mutate(net, True)
d.next_gen.append(Car(net))
""" Make a few randoms """
for i in range(d.RANDOM_CAR_COUNT):
# A new instance of a NN is always random
net = NeuralNetWork(d.SENSOR_COUNT, d.HIDDEN_LAYERS, 1)
d.next_gen.append(Car(net))
""" Cross-Breed the rest of the population """
children = []
breed_count = d.POPULATION_COUNT - len(d.next_gen)
for _ in range(breed_count):
# Find parents
mom = d.fittest_cars[random.randint(0, len(d.fittest_cars) - 1)]
dad = mom
# Make sure the two parent are different
while dad == mom:
dad = d.fittest_cars[random.randint(0, len(d.fittest_cars) - 1)]
# Make children
net = breed(mom.neural_net, dad.neural_net)
children.append(net)
# Mutate half of the crossed children
for i in range(int(len(children) / 2)):
children[i] = mutate(children[i], True)
# Add the children to the population
for i in range(len(children)):
d.next_gen.append(Car(children[i]))
""" Start a new simulation with the new population """
main.reset()
def test1():
arr_num_nodes = [3600, 4800]
keys = []
b = "set_1000_keys_lookup.txt"
with open(b, 'r') as filedata:
keys = json.load(filedata)
datas = []
for node in arr_num_nodes:
config.NODES = node
b = "set_" + str(node) + "_nodes.txt"
with open(b, 'r') as filedata:
datas = json.load(filedata)
main.load(datas)
result_test = test_lookup(keys['keys'])
name = "topo_" + str(config.NODES) + "_nodes_" + str(
1000) + "_keys_lookup_with_original_chord.json"
with open(name, "w") as fw:
json.dump(result_test, fw)
main.reset()
return json.dumps("ket thuc", indent=3)
def test1():
keys = []
b = "set_2000_keys_lookup.txt"
with open(b, 'r') as filedata:
keys = json.load(filedata)
datas = []
filename = "set_1024_nodes_ring.txt"
with open(filename, 'r') as filedata:
datas = json.load(filedata)
i = 0
for data in datas:
main.load(data)
result_test = test_lookup(keys['keys'])
name = "topo_" + str(
config.NODES) + "_nodes_" + str(2000) + "_keys_lookup_with_" + str(
i) + "%_faulty_nodes_improved_chord.json"
with open(name, "w") as fw:
json.dump(result_test, fw)
main.reset()
i += 10
return json.dumps("ket thuc", indent=3)
def test_insert():
keys = []
b = "set_1000_keys.txt"
with open(b, 'r') as filedata:
keys = json.load(filedata)
a = "data_insert/insert_data_1024nodes.txt"
datas = []
with open(a, 'r') as filedata:
datas = json.load(filedata)
result = []
j = 1
for data in datas:
main.load(data)
result_test = insert(keys['keys'])
a = str(j) + "nd:the_cost_insertion_1000_data_with_" + str(
config.NODES) + "_nodes_and_partition=" + str(config.N) + ".json"
with open(a, "w") as fw:
json.dump(result_test, fw)
main.reset()
j += 1
return json.dumps("ket thuc", indent=3)
def test_finger():
keys = []
b = "set_2000_keys_lookup.txt"
with open(b, 'r') as filedata:
keys = json.load(filedata)
print len(keys)
a = "set_1024_nodes.txt"
datas = []
with open(a, 'r') as filedata:
datas = json.load(filedata)
result = []
i = 0
for data in datas:
main.load(data)
result_test = test_lookup(keys['keys'])
name = "topo_" + str(
config.NODES) + "_nodes_" + str(2000) + "_keys_lookup_with_" + str(
i) + "%_faulty_nodes_original_chord.json"
with open(name, "w") as fw:
json.dump(result_test, fw)
return json.dumps("ket thuc", indent=3)
main.reset()
i += 10
return json.dumps("ket thuc", indent=3)
def reset():
return main.reset()
def jugarPartida(modo):
pygame.init()
pygame.display.set_caption('Tres en Raya - ' + modo)
screen.fill(bg)
btReiniciar = boton(col.dorado, 170, 305, 80, 40, 'Reiniciar', fontSize=15)
btSalir = boton(col.rojo, 250, 305, 40, 40, 'X', fontSize=15)
# estas variables se inicializan al importar el script, fuera de cualquier funcion
global turnoJ1, jugadasJ1, jugadasJ2, estado
while True:
# Guarda una copia del estado de la partida
copiaEstado = np.copy(estado)
screen.fill(bg)
# Muestra los botones
btReiniciar.draw(screen)
btSalir.draw(screen)
'''
SE MUESTRA SI TERMINO O NO LA PARTIDA Y SI HUBO UN EMPATE/GANADOR
'''
mostrarInfoTurno(modo)
'''
CONTROL DE EVENTOS (CLICKS O TECLAS) + ACTUALIZA LA COPIA DEL ESTADO CON LA NUEVA JUGADA HECHA
'''
# Capturar eventos
ev = pygame.event.get()
for event in ev:
mousePos = pygame.mouse.get_pos()
if event.type == pygame.QUIT:
quit()
# Si se pulsa una tecla
if event.type == pygame.KEYDOWN:
key = pygame.key.get_pressed()
if key == 'r': # TODO -> revisar pq no funciona esto...
reset()
# Si hay un click
if event.type == pygame.MOUSEBUTTONDOWN:
if btReiniciar.mouseIsOver(mousePos):
reset()
elif btSalir.mouseIsOver(mousePos):
quit()
if btReiniciar.mouseIsOver(mousePos):
btReiniciar.color = col.doradoClaro
else:
btReiniciar.color = col.dorado
if btSalir.mouseIsOver(mousePos):
btSalir.color = col.rojoClaro
else:
btSalir.color = col.rojo
mouseclick = pygame.mouse.get_pressed()
# si termino la partida, el bucle continua pq podria darle a "Reiniciar" o a "X"
# si no termino la partida
if not fin:
# si se pulso el raton en 1 VS 1
if modo == "1 VS 1" and sum(mouseclick) > 0:
# posicion del raton (en pixeles)
posX, posY = pygame.mouse.get_pos()
# calculo de celda
celX, celY = int(np.floor(posX / dimCW)), int(np.floor(posY / dimCH))
# Si clicka dentro de el espacio de juego
if posX < width and posY < 300:
# Si la celda no estaba ya "jugada" (elegida)
if copiaEstado[celX, celY] == 0:
# actualiza estado de la celda
copiaEstado[celX, celY] = 1
#print("Se actualizo la casilla ", celX, celY, " con valor = ", copiaEstado[celX, celY])
# Apunta la jugada y cambia el turno
if turnoJ1:
jugadasJ1 += str(celX) + str(celY) + " "
else:
jugadasJ2 += str(celX) + str(celY) + " "
turnoJ1 = not turnoJ1
elif modo == "1 VS PC":
# Si le toca al J1 y se pulso el raton
if turnoJ1 and sum(mouseclick) > 0:
# J1 clicka una casilla y juega
# posicion del raton (en pixeles)
posX, posY = pygame.mouse.get_pos()
# calculo de celda
celX, celY = int(np.floor(posX / dimCW)), int(np.floor(posY / dimCH))
# Si clicka dentro de el espacio de juego
if posX < width and posY < 300:
# Si la celda no estaba ya ocupada
if copiaEstado[celX, celY] == 0:
# actualizar estado de la celda
copiaEstado[celX, celY] = 1
#print("Se actualizo la casilla ", celX, celY, " con valor = ", copiaEstado[celX, celY])
# Apunta la jugada y devuelve el turno al PC
jugadasJ1 += str(celX) + str(celY) + " "
turnoJ1 = False
# Si le toca al PC
elif not turnoJ1:
# PC calcula su jugada y juega
celX, celY = pcCalculaJugada(copiaEstado)
# actualizar estado de la celda
copiaEstado[celX, celY] = 1
# Apunta la jugada y devuelve el turno al J1
jugadasJ2 += str(celX) + str(celY) + " "
turnoJ1 = True
'''
RENDER DEL TABLERO
'''
renderTablero()
# Carga el nuevo estado de la partida
estado = copiaEstado
pygame.display.flip()
async def display(ctx):
await ctx.send(main.generate(main.reset(), "l"))
async def female(ctx):
await ctx.send(main.generate(main.reset(), "f"))
from main import reset reset()
def reset(self):
return main.reset(self.client, filepath=self.filepath)
def setUp(self):
main.reset()
def reset(option):
main.reset(file_name, option)