def test_test(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)])
train_wordset = WordSet(num_words = 2, word_length = 16,
num_delays = 1, num_active = 4)
train_wordset.words = [wA, wB]
alice = Alice()
alice.train(n, train_wordset)
wD = Word([(2,0), (6,0), (12,0), (14,0)])
wE = Word([(3,0), (7,0), (9,0), (13,0)])
wF = Word([(1,0), (4,0), (9,0), (14,0)]) # False alarm
test_wordset = WordSet(num_words = 3, word_length = 16,
num_delays = 1, num_active = 4)
test_wordset.words = [wD, wE, wF]
bob = Bob()
bob.test(n, train_wordset, test_wordset)
eq_(bob.true_true, 2)
eq_(bob.true_false, 0)
eq_(bob.false_true, 1)
eq_(bob.false_false, 2)
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
