def test_expose_multiple_containers(self):
n = Neuron(S0 = 16, H = 2.0, G = 2.0, C = 3, D1 = 1, D2 = 1)
# Set container assignment manually to remove randomness
n.synapses['container'][ 0:10] = 0
n.synapses['container'][10:14] = 1
n.synapses['container'][14:16] = 2
w = Word([(1,0), (2,0), (6,0)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
w = Word([(1,0), (2,0), (3,0), (4,0), (5,0), (6,0)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 0)
eq_(container, 0)
w = Word([(10,0), (11,0), (12,0), (13,0)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 0)
eq_(container, 1)
w = Word([(14,0), (15,0)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
def test_expose_not_training(self):
n = Neuron(S0 = 16, H = 4.0, G = 2.0, C = 1, D1 = 1, D2 = 1)
w = Word([(1,0), (6,0), (9,0)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
w = Word([(1,0), (3,0), (4,0), (5,0), (6,0), (8,0), (9,0), (14,0)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 0)
eq_(container, 0)
def test_expose_with_delays(self):
n = Neuron(S0 = 16, H = 2.0, G = 2.0, C = 1, D1 = 2, D2 = 3)
# Set delay assignment manually to remove randomness
n.synapses['delay'][ 0:10] = 0
n.synapses['delay'][10:14] = 1
n.synapses['delay'][14:16] = 2
w = Word([(1,0), (2,0), (6,0)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
w = Word([(1,0), (2,0), (3,0), (4,0), (5,0), (6,0)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 0)
eq_(container, 0)
w = Word([(1,1), (2,1), (3,1), (4,1), (5,0), (6,0)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 1)
eq_(container, 0)
w = Word([(1,0), (2,0), (3,0), (4,1), (5,1), (6,1)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
w = Word([(10,1), (11,1), (12,1), (13,1)])
fired, delay, container = n.expose(w)
assert_true(fired)
eq_(delay, 2)
eq_(container, 0)
w = Word([(12,0), (13,0), (14,0), (15,0)])
fired, delay, container = n.expose(w)
assert_false(fired)
assert_is_none(delay)
assert_is_none(container)
def test_train(self):
n = Neuron(S0 = 16, H = 4.0, G = 2.0, C = 1, D1 = 1, D2 = 1)
wA = Word([(1,0), (6,0), (9,0), (14,0)])
wB = Word([(3,0), (4,0), (9,0), (13,0)])
wordset = WordSet(num_words = 2, word_length = 16, num_delays = 1,
num_active = 4)
wordset.words = [wA, wB]
alice = Alice()
alice.train(n, wordset)
# Test recognition
wD = Word([(2,0), (6,0), (12,0), (14,0)])
fired, delay, container = n.expose(wD)
assert_false(fired)
wE = Word([(3,0), (7,0), (9,0), (13,0)])
fired, delay, container = n.expose(wE)
assert_false(fired)
wF = Word([(1,0), (4,0), (9,0), (14,0)])
fired, delay, container = n.expose(wF)
assert_true(fired) # False alarm
def test_train(self):
n = Neuron(S0 = 16, H = 4.0, G = 2.0, C = 1, D1 = 1, D2 = 1)
# Train neuron with 2 patterns
wA = Word([(1,0), (6,0), (9,0), (14,0)])
wB = Word([(3,0), (4,0), (9,0), (13,0)])
n.start_training()
assert_true(n.train(wA))
assert_true(n.train(wB))
n.finish_training()
# Test recognition
wD = Word([(2,0), (6,0), (12,0), (14,0)])
fired, delay, container = n.expose(wD)
assert_false(fired)
wE = Word([(3,0), (7,0), (9,0), (13,0)])
fired, delay, container = n.expose(wE)
assert_false(fired)
wF = Word([(1,0), (4,0), (9,0), (14,0)])
fired, delay, container = n.expose(wF)
assert_true(fired) # False alarm
def test_train_with_delays(self):
n = Neuron(S0 = 16, H = 4.0, G = 2.0, C = 1, D1 = 2, D2 = 2)
# Fix neuron delays manually for the test
n.synapses['delay'] = 1
n.synapses['delay'][1] = 0
n.synapses['delay'][14] = 0
# Train neuron with 2 patterns
wA = Word([(1,1), (6,0), (9,0), (14,1)])
wB = Word([(3,0), (4,0), (9,0), (13,0)])
n.start_training()
assert_true(n.train(wA))
assert_true(n.train(wB))
n.finish_training()
# Recognize
wD = Word([(2,0), (6,0), (12,0), (14,0)])
fired, delay, container = n.expose(wD)
assert_false(fired)
wE = Word([(1,1), (3,0), (9,0), (13,0)])
fired, delay, container = n.expose(wE)
assert_true(fired) # False alarm
wF = Word([(1,0), (4,1), (7,0), (9,0), (11,0), (14,0)])
fired, delay, container = n.expose(wF)
assert_false(fired)
def test_train_not_training(self):
n = Neuron()
w = Word()
assert_false(n.train(w))
def test_expose_index_error(self):
n = Neuron(S0 = 16)
w = Word([(16,0)])
n.expose(w)
