def CAplot(rule, n, initiate):
ca = CA.CA(rule, n)
if initiate == "single":
ca.start_single()
else:
ca.start_random()
ca.loop(n - 1)
drawer = CADrawer.PyplotDrawer()
drawer.draw(ca)
return 1.0
#2.0,3.0 funny pattern
else:
return cur / 2.0
# return cur/2.000000001
#tipping point, 2.0 -> grid, little more? no grid
else:
if 3 <= t < 4:
return 1.
else:
return 0.
if __name__ == '__main__':
img = array(
I.open('Pics/building.jpg').resize((36 * 5, 48 * 5)).convert('L'))
img = img / float(img.max())
simulator = CA.CA(img, radius=1, rule=life_game_rule)
plt.ion()
simulator.plot()
raw_input('sizing')
iter = 0
while iter < 1000:
plt.clf()
simulator.update()
simulator.plot()
plt.draw()
# raw_input('pause')
for j in range(len(cells[i])):
if [i, j] not in input_data:
test_inputs.append([i, j])
targets.append([cells[i][j]])
return torch.Tensor(np.array(input_data)), torch.Tensor(np.array(output_data)), torch.Tensor(np.array(test_inputs)), torch.Tensor(np.array(targets))
def display_results(x, y):
plt.plot(x, y)
plt.show()
'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
Main
'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
if __name__ == "__main__":
ca = CA(N, N)
for i in range(1000):
ca.generate()
if SHOW_MAP:
plt.imshow(ca.get_cells(), cmap=plt.cm.gray, interpolation='nearest')
plt.pause(0.01)
if ca.check_for_stability():
plt.title("Stable")
plt.imshow(ca.get_cells(), cmap=plt.cm.gray, interpolation='nearest')
plt.show()
print("Generation: {}".format(i))
break
train_x, train_y, test_x, test_y = get_testing_data(ca.get_cells())
runs = []
import CA
from numpy.random import binomial
import matplotlib.pyplot as plt
def life_game_rule(k):
cur = k[len(k)/2]
t = (k==1).sum() - cur
return (cur == 1 and int(t==2 or t==3)) or (cur != 1 and int(t==3))
if __name__ == '__main__':
simulator = CA.CA(binomial(1, 0.15, (20, 40)), 1, life_game_rule, circular = True)
plt.ion()
simulator.plot()
raw_input('sizing')
iter = 0
while iter < 1000:
plt.clf()
simulator.update()
simulator.plot()
plt.draw()
#alpha = .9, portation = .2 is good
ind = acc.flatten().argsort()[::-1]
l, w = arg_grid.shape[:2]
bp = int(l * w * .1)
#.2 no noise, little fuzzy
for i in range(bp):
cur_grid[ind[i]/w, ind[i]%w] = 1.
for i in range(bp, l * w):
cur_grid[ind[i]/w, ind[i]%w] = 0.
return cur_grid
if __name__ == '__main__':
img = array(I.open('Pics/road.jpg').resize((1024, 548)).convert('L'))
img = img/float(img.max())
simulator = CA.CA(img, radius = 1, rule = detector, global_update = True)
plt.ion()
simulator.plot()
raw_input('sizing')
iter = 0
while iter < 1000:
plt.clf()
simulator.update()
simulator.plot()
plt.draw()
raw_input('pause')
return 1.0
#2.0,3.0 funny pattern
else:
return cur / 2.0
# return cur/2.000000001
#tipping point, 2.0 -> grid, little more? no grid
else:
if 3 <= t < 4:
return 1.
else:
return 0.
if __name__ == '__main__':
simulator = CA.CA(binomial(1, 0.15, (40, 40)),
1,
life_game_rule,
circular=False)
plt.ion()
simulator.plot()
raw_input('sizing')
iter = 0
while iter < 1000:
plt.clf()
simulator.update()
simulator.plot()
plt.draw()
# raw_input('pause')
from CA import *
from CADrawer import *
# for i in xrange(256):
rule = 110
n = 300
ca = CA(rule, n)
ca.start_comp()
# ca.start_random()
ca.loop(n - 1)
drawer = PyplotDrawer()
drawer.draw(ca)
drawer.show()
raw_input('')