def test_hqsom_noise(noise_std=.1):
test_data = np.array([
[0,0,0,0,0,0,0,0,0],
[1,1,1,0,0,0,0,0,0],
[0,0,0,1,1,1,0,0,0],
[0,0,0,0,0,0,1,1,1],
[1,0,0,1,0,0,1,0,0],
[0,1,0,0,1,0,0,1,0],
[0,0,1,0,0,1,0,0,1]])
# Add in gausian noise
noise = np.random.normal(0.0,noise_std,test_data.shape)
test_data = test_data + noise
g1,g2,s1,s2,a = .1,.1,16,90,.1
# Due to the noise we have to add many more map units
hqsom = HQSOM(9,18,3, use_pure_implementation=use_pure)
def flush(num):
for l in range(num):
hqsom.update(test_data[0], g1,g2,s1,s2,a)
num_cycles, num_repeats = 25, 11
total_run_count, seq_count = num_cycles*num_repeats*9, 0
for j in range(num_cycles):
for i in range(num_repeats):
print "update {}/{}".format(seq_count,total_run_count)
hqsom.reset()
if i %2 == 0:
seq = (1,2,3,1,2,3)
else:
seq = (4,5,6,4,5,6)
for k in seq:
hqsom.update(test_data[k], g1, g2, s1, s2, a)
hqsom.reset()
seq_count += 9
# Re-do the test data to test on different noisy data
print "Generating different test data for activating"
test_data = np.array([
[0,0,0,0,0,0,0,0,0],
[1,1,1,0,0,0,0,0,0],
[0,0,0,1,1,1,0,0,0],
[0,0,0,0,0,0,1,1,1],
[1,0,0,1,0,0,1,0,0],
[0,1,0,0,1,0,0,1,0],
[0,0,1,0,0,1,0,0,1]])
# Add in gausian noise
noise = np.random.normal(0.0,noise_std,test_data.shape)
test_data = test_data + noise
g1,g2,s1,s2,a = .1, .1, 16, 90, .1
c = [hqsom.activation_vector(t) for t in test_data]
print c
assert c[0] != c[1] and c[1] != c[4]
assert c[1] == c[2] and c[2] == c[3]
assert c[4] == c[5] and c[5] == c[6]
assert c[3] != c[4]
def test_hqsom():
""" Tests the hqsom algorithm on horizontal and vertical lines and ensures
that the hqsom can properly differentiate the two patterns """
test_data = np.array([
[0,0,0,0,0,0,0,0,0],
[1,1,1,0,0,0,0,0,0],
[0,0,0,1,1,1,0,0,0],
[0,0,0,0,0,0,1,1,1],
[1,0,0,1,0,0,1,0,0],
[0,1,0,0,1,0,0,1,0],
[0,0,1,0,0,1,0,0,1]])
g1,g2,s1,s2,a = .1,.1,16,90,.1
hqsom = HQSOM(9,18,3, use_pure_implementation=use_pure)
def flush(num):
for l in range(num):
hqsom.update(test_data[0], g1,g2,s1,s2,a)
num_cycles, num_repeats = 25, 11
total_run_count, seq_count = num_cycles*num_repeats*9, 0
for j in range(num_cycles):
for i in range(num_repeats):
print "update {}/{}".format(seq_count,total_run_count)
hqsom.reset()
seq = ()
if i %2 == 0:
seq = (1,2,3,1,2,3)
else:
seq = (4,5,6,4,5,6)
for k in seq:
hqsom.update(test_data[k], g1, g2, s1, s2, a)
hqsom.reset()
seq_count += 9
c = [hqsom.activation_vector(t) for t in test_data]
print c
assert c[0] != c[1] and c[1] != c[4]
assert c[1] == c[2] and c[2] == c[3]
assert c[4] == c[5] and c[5] == c[6]
assert c[3] != c[4]
