def show_one(hopfield_net, rows_no, cols_no, patterns, args):
# Choose a pattern
original_pattern = choice(patterns)
hopfield_net.reset(original_pattern)
hopfield_net.display_as_matrix(rows_no, cols_no, msg='Original pattern')
# hopfield_net.display_as_image(rows_no, cols_no)
# Apply noise to it
noisy_pattern = apply_noise(original_pattern, args.noise) # apply noise
hopfield_net.reset(noisy_pattern) # The net starts from the noisy pattern
hopfield_net.display_as_matrix(rows_no, cols_no, msg='Noisy pattern')
# hopfield_net.display_as_image(rows_no, cols_no)
# Let the network reach an energetic mimimum
hopfield_net.convergence_test = False
while not hopfield_net.is_energy_minimal():
hopfield_net.single_update()
hopfield_net.display_as_matrix(rows_no, cols_no, msg='After update')
print("Energy: %f" % hopfield_net.energy())
# hopfield_net.display_as_image(rows_no, cols_no)
if original_pattern == HopfieldNetwork.state_to_string(hopfield_net.state):
print("Recovered OK")
else:
print("NOT RECOVERED OK")
print("Done!")
def test_hopfield(hopfield_net, patterns, args):
########################## TASK 2: Testarea retelei #######################
# args.test_no - numarul de sabloane ce vor fi testate
# intoarce acuratetea
count_correct = 0
for original_pattern in patterns:
hopfield_net.reset(original_pattern)
hopfield_net.display_as_matrix(rows_no,
cols_no,
msg='Original pattern')
# hopfield_net.display_as_image(rows_no, cols_no)
# Apply noise to it
noisy_pattern = apply_noise(original_pattern,
args.noise) # apply noise
hopfield_net.reset(
noisy_pattern) # The net starts from the noisy pattern
hopfield_net.display_as_matrix(rows_no, cols_no, msg='Noisy pattern')
# hopfield_net.display_as_image(rows_no, cols_no)
# Let the network reach an energetic mimimum
hopfield_net.convergence_test = False
while not hopfield_net.is_energy_minimal():
hopfield_net.single_update()
hopfield_net.display_as_matrix(rows_no,
cols_no,
msg='After update')
print("Energy: %f" % hopfield_net.energy())
# hopfield_net.display_as_image(rows_no, cols_no)
if original_pattern == HopfieldNetwork.state_to_string(
hopfield_net.state):
count_correct += 1
print("Recovered OK")
return count_correct / len(patterns)
